Publications

Michael Seufert is now a Professor at University of Augsburg.

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E-Mail	michael.seufert@uni-a.de
Homepage	https://www.uni-augsburg.de/de/fakultaet/fai/informatik/prof/netcom/ www.mseufert.de
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Anschrift	Lehrstuhl für Vernetzte Eingebettete Systeme und Kommunikationssysteme Universität Augsburg Eichleitnerstr. 30 D-86159 Augsburg

Contents: Overview | Research Group | Projects | Publications | Teaching

Dissertation

Quality of Experience and Access Network Traffic Management of HTTP Adaptive Video Streaming. Technical Report (PhD dissertation), . Seufert, Michael. PhD dissertation. University of Wuerzburg, 2017, October.
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- [ EndNote ]
@phdthesis{info3-dissertation-2017-3, author = {Seufert, Michael}, keywords = {sys:hidden:supervisor:phuoc.tran-gia}, month = 10, school = {University of Wuerzburg}, title = {Quality of Experience and Access Network Traffic Management of HTTP Adaptive Video Streaming}, year = 2017 }

%0 Thesis %1 info3-dissertation-2017-3 %A Seufert, Michael %D 2017 %T Quality of Experience and Access Network Traffic Management of HTTP Adaptive Video Streaming

Book Chapter

Socially-Aware Traffic Management. Seufert, Michael; Darzanos, George; Papafili, Ioanna; Łapacz, Roman; Burger, Valentin; Hoßfeld, Tobias. In Socioinformatics - The Social Impact of Interactions between Humans and IT, K. Zweig, W. Neuser, V. Pipek, M. Rohde, I. Scholtes (eds.). Springer International Publishing, 2014.
- [ Abstract ]
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Socially-aware traffic management utilizes social information to optimize traffic management in the Internet in terms of traffic load, energy consumption, or end user satisfaction. Several use cases can benefit from socially-aware traffic management and the performance of overlay applications can be enhanced. We present existing use cases and their socially-aware approaches and solutions, but also raise discussions on additional benefits from the integration of social information into traffic management as well as practical aspects in this domain.

@incollection{info3-incollection-2014-25, abstract = {Socially-aware traffic management utilizes social information to optimize traffic management in the Internet in terms of traffic load, energy consumption, or end user satisfaction. Several use cases can benefit from socially-aware traffic management and the performance of overlay applications can be enhanced. We present existing use cases and their socially-aware approaches and solutions, but also raise discussions on additional benefits from the integration of social information into traffic management as well as practical aspects in this domain.}, author = {Seufert, Michael and Darzanos, George and Papafili, Ioanna and Łapacz, Roman and Burger, Valentin and Hoßfeld, Tobias}, booktitle = {Socioinformatics - The Social Impact of Interactions between Humans and IT}, editor = {Zweig, Katharina and Neuser, Wolfgang and Pipek, Volkmar and Rohde, Markus and Scholtes, Ingo}, keywords = {smartenit}, month = {08}, publisher = {Springer International Publishing}, title = {Socially-Aware Traffic Management}, year = 2014 }

%0 Book Section %1 info3-incollection-2014-25 %A Seufert, Michael %A Darzanos, George %A Papafili, Ioanna %A Łapacz, Roman %A Burger, Valentin %A Hoßfeld, Tobias %B Socioinformatics - The Social Impact of Interactions between Humans and IT %D 2014 %E Zweig, Katharina %E Neuser, Wolfgang %E Pipek, Volkmar %E Rohde, Markus %E Scholtes, Ingo %I Springer International Publishing %T Socially-Aware Traffic Management %X Socially-aware traffic management utilizes social information to optimize traffic management in the Internet in terms of traffic load, energy consumption, or end user satisfaction. Several use cases can benefit from socially-aware traffic management and the performance of overlay applications can be enhanced. We present existing use cases and their socially-aware approaches and solutions, but also raise discussions on additional benefits from the integration of social information into traffic management as well as practical aspects in this domain.
Social Network Analysis in the Enterprise: Challenges and Opportunities. Burger, Valentin; Hock, David; Scholtes, Ingo; Hoßfeld, Tobias; Garcia, David; Seufert, Michael. In Socioinformatics - The Social Impact of Interactions between Humans and IT, K. Zweig, W. Neuser, V. Pipek, M. Rohde, I. Scholtes (eds.). Springer International Publishing, 2014.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
- [ Download ]
Enterprise social software tools are increasingly being used to support the communication and collaboration between employees, as well as to facilitate the collaborative organisation of information and knowledge within companies. Not only do these tools help to develop and maintain an efficient social organisation, they also produce massive amounts of fine-grained data on collaborations, communication and other forms of social relationships within an enterprise. In this chapter, we argue that the availability of these data provides unique opportunities to monitor and analyse social structures and their impact on the success and performance of individuals, teams, communities and organisations. We further review methods from the planning, design and optimisation of telecommunication networks and discuss challenges arising when wanting to apply them to optimise the structure of enterprise social networks.

@incollection{info3-incollection-2014-24, abstract = {Enterprise social software tools are increasingly being used to support the communication and collaboration between employees, as well as to facilitate the collaborative organisation of information and knowledge within companies. Not only do these tools help to develop and maintain an efficient social organisation, they also produce massive amounts of fine-grained data on collaborations, communication and other forms of social relationships within an enterprise. In this chapter, we argue that the availability of these data provides unique opportunities to monitor and analyse social structures and their impact on the success and performance of individuals, teams, communities and organisations. We further review methods from the planning, design and optimisation of telecommunication networks and discuss challenges arising when wanting to apply them to optimise the structure of enterprise social networks.}, author = {Burger, Valentin and Hock, David and Scholtes, Ingo and Hoßfeld, Tobias and Garcia, David and Seufert, Michael}, booktitle = {Socioinformatics - The Social Impact of Interactions between Humans and IT}, editor = {Zweig, Katharina and Neuser, Wolfgang and Pipek, Volkmar and Rohde, Markus and Scholtes, Ingo}, keywords = {myown}, month = {08}, publisher = {Springer International Publishing}, title = {Social Network Analysis in the Enterprise: Challenges and Opportunities}, year = 2014 }

%0 Book Section %1 info3-incollection-2014-24 %A Burger, Valentin %A Hock, David %A Scholtes, Ingo %A Hoßfeld, Tobias %A Garcia, David %A Seufert, Michael %B Socioinformatics - The Social Impact of Interactions between Humans and IT %D 2014 %E Zweig, Katharina %E Neuser, Wolfgang %E Pipek, Volkmar %E Rohde, Markus %E Scholtes, Ingo %I Springer International Publishing %T Social Network Analysis in the Enterprise: Challenges and Opportunities %X Enterprise social software tools are increasingly being used to support the communication and collaboration between employees, as well as to facilitate the collaborative organisation of information and knowledge within companies. Not only do these tools help to develop and maintain an efficient social organisation, they also produce massive amounts of fine-grained data on collaborations, communication and other forms of social relationships within an enterprise. In this chapter, we argue that the availability of these data provides unique opportunities to monitor and analyse social structures and their impact on the success and performance of individuals, teams, communities and organisations. We further review methods from the planning, design and optimisation of telecommunication networks and discuss challenges arising when wanting to apply them to optimise the structure of enterprise social networks.

Journal Articles

COBIRAS: Offering a Continuous Bit Rate Slide to Maximize DASH Streaming Bandwidth Utilization. Seufert, Michael; Spangenberger, Marius; Poignée, Fabian; Wamser, Florian; Robitza, Werner; Timmerer, Christian; Hoßfeld, Tobias. In ACM Transactions on Multimedia Computing, Communications, and Applications. 2024.
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@article{info3-article-2024-5, author = {Seufert, Michael and Spangenberger, Marius and Poignée, Fabian and Wamser, Florian and Robitza, Werner and Timmerer, Christian and Hoßfeld, Tobias}, journal = {ACM Transactions on Multimedia Computing, Communications, and Applications}, keywords = {ucn}, month = {07}, title = {COBIRAS: Offering a Continuous Bit Rate Slide to Maximize DASH Streaming Bandwidth Utilization}, year = 2024 }

%0 Journal Article %1 info3-article-2024-5 %A Seufert, Michael %A Spangenberger, Marius %A Poignée, Fabian %A Wamser, Florian %A Robitza, Werner %A Timmerer, Christian %A Hoßfeld, Tobias %D 2024 %J ACM Transactions on Multimedia Computing, Communications, and Applications %T COBIRAS: Offering a Continuous Bit Rate Slide to Maximize DASH Streaming Bandwidth Utilization
The Missing Link in Network Intrusion Detection: Taking AI/ML Research Efforts to Users. Dietz, Katharina; Mühlhauser, Michael; Kögel, Jochen; Schwinger, Stephan; Sichermann, Marleen; Seufert, Michael; Herrmann, Dominik; Hoßfeld, Tobias. In IEEE Access. 2024.
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@article{info3-article-2024-4, author = {Dietz, Katharina and Mühlhauser, Michael and Kögel, Jochen and Schwinger, Stephan and Sichermann, Marleen and Seufert, Michael and Herrmann, Dominik and Hoßfeld, Tobias}, journal = {IEEE Access}, keywords = {sys:hidden:article}, month = {05}, title = {The Missing Link in Network Intrusion Detection: Taking AI/ML Research Efforts to Users}, year = 2024 }

%0 Journal Article %1 info3-article-2024-4 %A Dietz, Katharina %A Mühlhauser, Michael %A Kögel, Jochen %A Schwinger, Stephan %A Sichermann, Marleen %A Seufert, Michael %A Herrmann, Dominik %A Hoßfeld, Tobias %D 2024 %J IEEE Access %T The Missing Link in Network Intrusion Detection: Taking AI/ML Research Efforts to Users
Machine Learning with Computer Networks: Techniques, Datasets and Models. Afifi, Haitham; Pochaba, Sabrina; Boltres, Andreas; Laniewski, Dominic; Haberer, Janek; Paeleke, Leonard; Poorzare, Reza; Stolpmann, Daniel; Wehner, Nikolas; Redder, Adrian; Samikwa, Eric; Seufert, Michael. In IEEE Access. 2024.
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@article{info3-article-2024-2, author = {Afifi, Haitham and Pochaba, Sabrina and Boltres, Andreas and Laniewski, Dominic and Haberer, Janek and Paeleke, Leonard and Poorzare, Reza and Stolpmann, Daniel and Wehner, Nikolas and Redder, Adrian and Samikwa, Eric and Seufert, Michael}, journal = {IEEE Access}, keywords = {sys:hidden:article}, month = {04}, title = {Machine Learning with Computer Networks: Techniques, Datasets and Models}, year = 2024 }

%0 Journal Article %1 info3-article-2024-2 %A Afifi, Haitham %A Pochaba, Sabrina %A Boltres, Andreas %A Laniewski, Dominic %A Haberer, Janek %A Paeleke, Leonard %A Poorzare, Reza %A Stolpmann, Daniel %A Wehner, Nikolas %A Redder, Adrian %A Samikwa, Eric %A Seufert, Michael %D 2024 %J IEEE Access %T Machine Learning with Computer Networks: Techniques, Datasets and Models
Marina: Realizing ML-Driven Real-Time Network Traffic Monitoring at Terabit Scale. Seufert, Michael; Dietz, Katharina; Wehner, Nikolas; Geißler, Stefan; Schüler, Joshua; Wolz, Manuel; Hotho, Andreas; Casas, Pedro; Hoßfeld, Tobias; Feldmann, Anja. In Transactions on Network and Service Management (TNSM). 2024.
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@article{info3-article-2024-1, author = {Seufert, Michael and Dietz, Katharina and Wehner, Nikolas and Geißler, Stefan and Schüler, Joshua and Wolz, Manuel and Hotho, Andreas and Casas, Pedro and Hoßfeld, Tobias and Feldmann, Anja}, journal = {Transactions on Network and Service Management (TNSM)}, keywords = {ucn}, month = {03}, title = {Marina: Realizing ML-Driven Real-Time Network Traffic Monitoring at Terabit Scale}, year = 2024 }

%0 Journal Article %1 info3-article-2024-1 %A Seufert, Michael %A Dietz, Katharina %A Wehner, Nikolas %A Geißler, Stefan %A Schüler, Joshua %A Wolz, Manuel %A Hotho, Andreas %A Casas, Pedro %A Hoßfeld, Tobias %A Feldmann, Anja %D 2024 %J Transactions on Network and Service Management (TNSM) %T Marina: Realizing ML-Driven Real-Time Network Traffic Monitoring at Terabit Scale
Want more WANs? Comparison of Traditional and GAN-based Generation of Wide Area Network Topologies via Graph and Performance Metrics. Dietz, Katharina; Seufert, Michael; Hoßfeld, Tobias. In Transactions on Network and Service Management (TNSM). 2023.
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@article{info3-article-2023-5, author = {Dietz, Katharina and Seufert, Michael and Hoßfeld, Tobias}, journal = {Transactions on Network and Service Management (TNSM)}, keywords = {ucn}, month = {07}, title = {Want more WANs? Comparison of Traditional and GAN-based Generation of Wide Area Network Topologies via Graph and Performance Metrics}, year = 2023 }

%0 Journal Article %1 info3-article-2023-5 %A Dietz, Katharina %A Seufert, Michael %A Hoßfeld, Tobias %D 2023 %J Transactions on Network and Service Management (TNSM) %T Want more WANs? Comparison of Traditional and GAN-based Generation of Wide Area Network Topologies via Graph and Performance Metrics
Share and Multiply: Modeling Communication and Generated Traffic in Private WhatsApp Groups. Seufert, Anika; Poignée, Fabian; Seufert, Michael; Hoßfeld, Tobias. In IEEE Access, 11, pp. 25401–25414. 2023.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
Group-based communication is a highly popular communication paradigm, which is especially prominent in mobile instant messaging (MIM) applications, such as WhatsApp. Chat groups in MIM applications facilitate the sharing of various types of messages (e.g., text, voice, image, video) among a large number of participants. As each message has to be transmitted to every other member of the group, which multiplies the traffic, this has a massive impact on the underlying communication networks. However, most chat groups are private and network operators cannot obtain deep insights into MIM communication via network measurements due to end-to-end encryption. Thus, the generation of traffic is not well understood, given that it depends on sizes of communication groups, speed of communication, and exchanged message types. In this work, we provide a huge data set of 5,956 private WhatsApp chat histories, which contains over 76 million messages from more than 117,000 users. We describe and model the properties of chat groups and users, and the communication within these chat groups, which gives unprecedented insights into private MIM communication. In addition, we conduct exemplary measurements for the most popular message types, which empower the provided models to estimate the traffic over time in a chat group.

@article{info3-article-2023-2, abstract = {Group-based communication is a highly popular communication paradigm, which is especially prominent in mobile instant messaging (MIM) applications, such as WhatsApp. Chat groups in MIM applications facilitate the sharing of various types of messages (e.g., text, voice, image, video) among a large number of participants. As each message has to be transmitted to every other member of the group, which multiplies the traffic, this has a massive impact on the underlying communication networks. However, most chat groups are private and network operators cannot obtain deep insights into MIM communication via network measurements due to end-to-end encryption. Thus, the generation of traffic is not well understood, given that it depends on sizes of communication groups, speed of communication, and exchanged message types. In this work, we provide a huge data set of 5,956 private WhatsApp chat histories, which contains over 76 million messages from more than 117,000 users. We describe and model the properties of chat groups and users, and the communication within these chat groups, which gives unprecedented insights into private MIM communication. In addition, we conduct exemplary measurements for the most popular message types, which empower the provided models to estimate the traffic over time in a chat group.}, author = {Seufert, Anika and Poignée, Fabian and Seufert, Michael and Hoßfeld, Tobias}, journal = {IEEE Access}, keywords = {ucn}, month = {03}, pages = {25401 - 25414}, title = {Share and Multiply: Modeling Communication and Generated Traffic in Private WhatsApp Groups}, volume = 11, year = 2023 }

%0 Journal Article %1 info3-article-2023-2 %A Seufert, Anika %A Poignée, Fabian %A Seufert, Michael %A Hoßfeld, Tobias %D 2023 %J IEEE Access %P 25401 - 25414 %T Share and Multiply: Modeling Communication and Generated Traffic in Private WhatsApp Groups %V 11 %X Group-based communication is a highly popular communication paradigm, which is especially prominent in mobile instant messaging (MIM) applications, such as WhatsApp. Chat groups in MIM applications facilitate the sharing of various types of messages (e.g., text, voice, image, video) among a large number of participants. As each message has to be transmitted to every other member of the group, which multiplies the traffic, this has a massive impact on the underlying communication networks. However, most chat groups are private and network operators cannot obtain deep insights into MIM communication via network measurements due to end-to-end encryption. Thus, the generation of traffic is not well understood, given that it depends on sizes of communication groups, speed of communication, and exchanged message types. In this work, we provide a huge data set of 5,956 private WhatsApp chat histories, which contains over 76 million messages from more than 117,000 users. We describe and model the properties of chat groups and users, and the communication within these chat groups, which gives unprecedented insights into private MIM communication. In addition, we conduct exemplary measurements for the most popular message types, which empower the provided models to estimate the traffic over time in a chat group.
Do you Agree? Contrasting Google’s Core Web Vitals and the Impact of Cookie Consent Banners with Actual Web QoE. Wehner, Nikolas; Seufert, Michael; Schatz, Raimund; Hoßfeld, Tobias. In Quality and User Experience. 2023.
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Providing sophisticated web Quality of Experience (QoE) has become paramount for web service providers and network operators alike. Due to advances in web technologies (HTML5, respon- sive design, etc.), traditional web QoE models focusing mainly on loading times have to be refined and improved. In this work, we relate Google’s Core Web Vitals, a set of metrics for improving user experience, to the loading time aspects of web QoE, and investigate whether the Core Web Vitals and web QoE agree on the perceived experience. To this end, we first perform objective measurements in the web using Google’s Lighthouse. To close the gap be- tween metrics and experience, we complement these objective measurements with subjective assessment by performing multiple crowdsourcing QoE studies. For this purpose, we developed CWeQS, a customized framework to emulate the entire web page loading process, and ask users for their experience while controlling the Core Web Vitals, which is available to the public. To properly configure CWeQS for the planned QoE study and the crowdsourcing setup, we conduct pre-studies, in which we evaluate the importance of the loading strategy of a web page and the impor- tance of the user task. The obtained insights allow us to conduct the desired QoE studies for each of the Core Web Vitals. Furthermore, we assess the impact of cookie consent banners, which have become ubiquitous due to regulatory demands, on the Core Web Vitals and investigate their influence on web QoE. Our results suggest that the Core Web Vitals are much less predictive for web QoE than expected and that page loading times remain the main metric and influence factor in this context. We further observe that unobtrusive and acentric cookie consent banners are preferred by end-users and that addi- tional delays caused by interacting with consent banners in order to agree to or reject cookies should be accounted along with the actual page load time to reduce waiting times and thus to improve web QoE.

@article{info3-article-2023-3, abstract = {Providing sophisticated web Quality of Experience (QoE) has become paramount for web service providers and network operators alike. Due to advances in web technologies (HTML5, respon- sive design, etc.), traditional web QoE models focusing mainly on loading times have to be refined and improved. In this work, we relate Google’s Core Web Vitals, a set of metrics for improving user experience, to the loading time aspects of web QoE, and investigate whether the Core Web Vitals and web QoE agree on the perceived experience. To this end, we first perform objective measurements in the web using Google’s Lighthouse. To close the gap be- tween metrics and experience, we complement these objective measurements with subjective assessment by performing multiple crowdsourcing QoE studies. For this purpose, we developed CWeQS, a customized framework to emulate the entire web page loading process, and ask users for their experience while controlling the Core Web Vitals, which is available to the public. To properly configure CWeQS for the planned QoE study and the crowdsourcing setup, we conduct pre-studies, in which we evaluate the importance of the loading strategy of a web page and the impor- tance of the user task. The obtained insights allow us to conduct the desired QoE studies for each of the Core Web Vitals. Furthermore, we assess the impact of cookie consent banners, which have become ubiquitous due to regulatory demands, on the Core Web Vitals and investigate their influence on web QoE. Our results suggest that the Core Web Vitals are much less predictive for web QoE than expected and that page loading times remain the main metric and influence factor in this context. We further observe that unobtrusive and acentric cookie consent banners are preferred by end-users and that addi- tional delays caused by interacting with consent banners in order to agree to or reject cookies should be accounted along with the actual page load time to reduce waiting times and thus to improve web QoE.}, author = {Wehner, Nikolas and Seufert, Michael and Schatz, Raimund and Hoßfeld, Tobias}, journal = {Quality and User Experience}, keywords = {ucn}, title = {Do you Agree? Contrasting Google’s Core Web Vitals and the Impact of Cookie Consent Banners with Actual Web QoE}, year = 2023 }

%0 Journal Article %1 info3-article-2023-3 %A Wehner, Nikolas %A Seufert, Michael %A Schatz, Raimund %A Hoßfeld, Tobias %D 2023 %J Quality and User Experience %T Do you Agree? Contrasting Google’s Core Web Vitals and the Impact of Cookie Consent Banners with Actual Web QoE %X Providing sophisticated web Quality of Experience (QoE) has become paramount for web service providers and network operators alike. Due to advances in web technologies (HTML5, respon- sive design, etc.), traditional web QoE models focusing mainly on loading times have to be refined and improved. In this work, we relate Google’s Core Web Vitals, a set of metrics for improving user experience, to the loading time aspects of web QoE, and investigate whether the Core Web Vitals and web QoE agree on the perceived experience. To this end, we first perform objective measurements in the web using Google’s Lighthouse. To close the gap be- tween metrics and experience, we complement these objective measurements with subjective assessment by performing multiple crowdsourcing QoE studies. For this purpose, we developed CWeQS, a customized framework to emulate the entire web page loading process, and ask users for their experience while controlling the Core Web Vitals, which is available to the public. To properly configure CWeQS for the planned QoE study and the crowdsourcing setup, we conduct pre-studies, in which we evaluate the importance of the loading strategy of a web page and the impor- tance of the user task. The obtained insights allow us to conduct the desired QoE studies for each of the Core Web Vitals. Furthermore, we assess the impact of cookie consent banners, which have become ubiquitous due to regulatory demands, on the Core Web Vitals and investigate their influence on web QoE. Our results suggest that the Core Web Vitals are much less predictive for web QoE than expected and that page loading times remain the main metric and influence factor in this context. We further observe that unobtrusive and acentric cookie consent banners are preferred by end-users and that addi- tional delays caused by interacting with consent banners in order to agree to or reject cookies should be accounted along with the actual page load time to reduce waiting times and thus to improve web QoE.
An Introduction to Online Video Game QoS and QoE Influencing Factors. Metzger, Florian; Geißler, Stefan; Grigorjew, Alexej; Loh, Frank; Moldovan, Christian; Seufert, Michael; Hoßfeld, Tobias. In IEEE Communications Surveys & Tutorials. 2022.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
- [ Download ]
Online video games and cloud gaming are rapidly growing in pervasiveness. Their resource demands can put significant stress on the global communication infrastructure. And network conditions are amongst the chief factors that influence one's enjoyment while playing games. This makes it imperative for video games to be considered for network dimensioning, server placement or protocol development. For that reason, in this work we provide an introduction to the technical aspects of video games in general and of their network aspects in particular. This understanding forms the basis for a rich taxonomy of factors that influence and provide context to a video game's Quality of Service (QoS) and Quality of Experience (QoE). The taxonomy covers influence factors from all aspects involved in a video game, from the subjective player and game influence factors to the system and networking influence factors. Finally, this work gives an overview of conducted and ongoing research as well as future research opportunities while taking into account lessons learned from past approaches.

@article{info3-article-2022-16, abstract = {Online video games and cloud gaming are rapidly growing in pervasiveness. Their resource demands can put significant stress on the global communication infrastructure. And network conditions are amongst the chief factors that influence one's enjoyment while playing games. This makes it imperative for video games to be considered for network dimensioning, server placement or protocol development. For that reason, in this work we provide an introduction to the technical aspects of video games in general and of their network aspects in particular. This understanding forms the basis for a rich taxonomy of factors that influence and provide context to a video game's Quality of Service (QoS) and Quality of Experience (QoE). The taxonomy covers influence factors from all aspects involved in a video game, from the subjective player and game influence factors to the system and networking influence factors. Finally, this work gives an overview of conducted and ongoing research as well as future research opportunities while taking into account lessons learned from past approaches.}, author = {Metzger, Florian and Geißler, Stefan and Grigorjew, Alexej and Loh, Frank and Moldovan, Christian and Seufert, Michael and Hoßfeld, Tobias}, journal = {IEEE Communications Surveys & Tutorials}, keywords = {sys:hidden:article}, month = {05}, title = {An Introduction to Online Video Game QoS and QoE Influencing Factors}, year = 2022 }

%0 Journal Article %1 info3-article-2022-16 %A Metzger, Florian %A Geißler, Stefan %A Grigorjew, Alexej %A Loh, Frank %A Moldovan, Christian %A Seufert, Michael %A Hoßfeld, Tobias %D 2022 %J IEEE Communications Surveys & Tutorials %T An Introduction to Online Video Game QoS and QoE Influencing Factors %X Online video games and cloud gaming are rapidly growing in pervasiveness. Their resource demands can put significant stress on the global communication infrastructure. And network conditions are amongst the chief factors that influence one's enjoyment while playing games. This makes it imperative for video games to be considered for network dimensioning, server placement or protocol development. For that reason, in this work we provide an introduction to the technical aspects of video games in general and of their network aspects in particular. This understanding forms the basis for a rich taxonomy of factors that influence and provide context to a video game's Quality of Service (QoS) and Quality of Experience (QoE). The taxonomy covers influence factors from all aspects involved in a video game, from the subjective player and game influence factors to the system and networking influence factors. Finally, this work gives an overview of conducted and ongoing research as well as future research opportunities while taking into account lessons learned from past approaches.
Pandemic in the Digital Age: Analyzing WhatsApp Communication Behavior before, during, and after the COVID-19 Lockdown. Seufert, Anika; Poignée, Fabian; Hoßfeld, Tobias; Seufert, Michael. In Humanities and Social Sciences Communications, 9(1), pp. 140 (1–9). 2022.
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The strict restrictions introduced by the COVID-19 lockdowns, which started from March 2020, changed people’s daily lives and habits on many different levels. In this work, we investigate the impact of the lockdown on the communication behavior in the mobile instant messaging application WhatsApp. Our evaluations are based on a large dataset of 2577 private chat histories with 25,378,093 messages from 51,973 users. The analysis of the one-to-one and group conversations confirms that the lockdown severely altered the communication in WhatsApp chats compared to pre-pandemic time ranges. In particular, we observe short-term effects, which caused an increased message frequency in the first lockdown months and a shifted communication activity during the day in March and April 2020. Moreover, we also see long-term effects of the ongoing pandemic situation until February 2021, which indicate a change of communication behavior towards more regular messaging, as well as a persisting change in activity during the day. The results of our work show that even anonymized chat histories can tell us a lot about people’s behavior and especially behavioral changes during the COVID-19 pandemic and thus are of great relevance for behavioral researchers. Furthermore, looking at the pandemic from an Internet provider perspective, these insights can be used during the next pandemic, or if the current COVID-19 situation worsens, to adapt communication networks to the changed usage behavior early on and thus avoid network congestion.

@article{info3-article-2022-14, abstract = {The strict restrictions introduced by the COVID-19 lockdowns, which started from March 2020, changed people’s daily lives and habits on many different levels. In this work, we investigate the impact of the lockdown on the communication behavior in the mobile instant messaging application WhatsApp. Our evaluations are based on a large dataset of 2577 private chat histories with 25,378,093 messages from 51,973 users. The analysis of the one-to-one and group conversations confirms that the lockdown severely altered the communication in WhatsApp chats compared to pre-pandemic time ranges. In particular, we observe short-term effects, which caused an increased message frequency in the first lockdown months and a shifted communication activity during the day in March and April 2020. Moreover, we also see long-term effects of the ongoing pandemic situation until February 2021, which indicate a change of communication behavior towards more regular messaging, as well as a persisting change in activity during the day. The results of our work show that even anonymized chat histories can tell us a lot about people’s behavior and especially behavioral changes during the COVID-19 pandemic and thus are of great relevance for behavioral researchers. Furthermore, looking at the pandemic from an Internet provider perspective, these insights can be used during the next pandemic, or if the current COVID-19 situation worsens, to adapt communication networks to the changed usage behavior early on and thus avoid network congestion.}, author = {Seufert, Anika and Poignée, Fabian and Hoßfeld, Tobias and Seufert, Michael}, journal = {Humanities and Social Sciences Communications}, keywords = {ucn}, month = {04}, number = 1, pages = {140 (1-9)}, title = {Pandemic in the Digital Age: Analyzing WhatsApp Communication Behavior before, during, and after the COVID-19 Lockdown}, volume = 9, year = 2022 }

%0 Journal Article %1 info3-article-2022-14 %A Seufert, Anika %A Poignée, Fabian %A Hoßfeld, Tobias %A Seufert, Michael %D 2022 %J Humanities and Social Sciences Communications %N 1 %P 140 (1-9) %T Pandemic in the Digital Age: Analyzing WhatsApp Communication Behavior before, during, and after the COVID-19 Lockdown %V 9 %X The strict restrictions introduced by the COVID-19 lockdowns, which started from March 2020, changed people’s daily lives and habits on many different levels. In this work, we investigate the impact of the lockdown on the communication behavior in the mobile instant messaging application WhatsApp. Our evaluations are based on a large dataset of 2577 private chat histories with 25,378,093 messages from 51,973 users. The analysis of the one-to-one and group conversations confirms that the lockdown severely altered the communication in WhatsApp chats compared to pre-pandemic time ranges. In particular, we observe short-term effects, which caused an increased message frequency in the first lockdown months and a shifted communication activity during the day in March and April 2020. Moreover, we also see long-term effects of the ongoing pandemic situation until February 2021, which indicate a change of communication behavior towards more regular messaging, as well as a persisting change in activity during the day. The results of our work show that even anonymized chat histories can tell us a lot about people’s behavior and especially behavioral changes during the COVID-19 pandemic and thus are of great relevance for behavioral researchers. Furthermore, looking at the pandemic from an Internet provider perspective, these insights can be used during the next pandemic, or if the current COVID-19 situation worsens, to adapt communication networks to the changed usage behavior early on and thus avoid network congestion.
Delivering User Experience over Networks: Towards a Quality of Experience Centered Design Cycle for Improved Design of Networked Applications. Seufert, Anika; Schröder, Svenja; Seufert, Michael. In SN Computer Science, 2. 2021.
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To deliver the best user experience (UX), the human-centered design cycle (HCDC) serves as a well-established guideline to application developers. However, it does not yet cover network-specific requirements, which become increasingly crucial, as most applications deliver experience over the Internet. The missing network-centric view is provided by Quality of Experience (QoE), which could team up with UX towards an improved overall experience. By considering QoE aspects during the development process, it can be achieved that applications become network-aware by design. In this paper, the Quality of Experience Centered Design Cycle (QoE-CDC) is proposed, which provides guidelines on how to design applications with respect to network-specific requirements and QoE. Its practical value is showcased for popular application types and validated by outlining the design of a new smartphone application. We show that combining HCDC and QoE-CDC will result in an application design, which reaches a high UX and avoids QoE degradation.

@article{info3-article-2021-6, abstract = {To deliver the best user experience (UX), the human-centered design cycle (HCDC) serves as a well-established guideline to application developers. However, it does not yet cover network-specific requirements, which become increasingly crucial, as most applications deliver experience over the Internet. The missing network-centric view is provided by Quality of Experience (QoE), which could team up with UX towards an improved overall experience. By considering QoE aspects during the development process, it can be achieved that applications become network-aware by design. In this paper, the Quality of Experience Centered Design Cycle (QoE-CDC) is proposed, which provides guidelines on how to design applications with respect to network-specific requirements and QoE. Its practical value is showcased for popular application types and validated by outlining the design of a new smartphone application. We show that combining HCDC and QoE-CDC will result in an application design, which reaches a high UX and avoids QoE degradation.}, author = {Seufert, Anika and Schröder, Svenja and Seufert, Michael}, journal = {SN Computer Science}, keywords = {sys:hidden:article}, month = {09}, title = {Delivering User Experience over Networks: Towards a Quality of Experience Centered Design Cycle for Improved Design of Networked Applications}, volume = 2, year = 2021 }

%0 Journal Article %1 info3-article-2021-6 %A Seufert, Anika %A Schröder, Svenja %A Seufert, Michael %D 2021 %J SN Computer Science %T Delivering User Experience over Networks: Towards a Quality of Experience Centered Design Cycle for Improved Design of Networked Applications %V 2 %X To deliver the best user experience (UX), the human-centered design cycle (HCDC) serves as a well-established guideline to application developers. However, it does not yet cover network-specific requirements, which become increasingly crucial, as most applications deliver experience over the Internet. The missing network-centric view is provided by Quality of Experience (QoE), which could team up with UX towards an improved overall experience. By considering QoE aspects during the development process, it can be achieved that applications become network-aware by design. In this paper, the Quality of Experience Centered Design Cycle (QoE-CDC) is proposed, which provides guidelines on how to design applications with respect to network-specific requirements and QoE. Its practical value is showcased for popular application types and validated by outlining the design of a new smartphone application. We show that combining HCDC and QoE-CDC will result in an application design, which reaches a high UX and avoids QoE degradation.
Performance Evaluation of Hybrid Crowdsensing and Fixed Sensor Systems for Event Detection in Urban Environments. Hirth, Matthias; Seufert, Michael; Lange, Stanislav; Meixner, Markus; Tran-Gia, Phuoc. In Sensors, 21(17), pp. 5880 (1–19). 2021.
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- [ BibTeX ]
- [ EndNote ]
Crowdsensing offers a cost-effective way to collect large amounts of environmental sensor data. However, the spatial distribution of crowdsensing sensors can hardly be influenced, as the participants carry the sensors, and, additionally, the quality of the crowdsensed data can vary significantly. Hybrid systems that use mobile users in conjunction with fixed sensors might help to overcome these limitations, as such system allow assessing the quality of the submitted crowdsensed data and provide sensor values where no crowdsensing data is available. In this work, we use a simulation study to first analyze a simple crowdsensing system concerning the detection performance of spatial events to highlight the potential and limitations of a pure crowdsourcing system. The results indicate that even if only a small share of inhabitants participates in crowdsensing, events that have locations correlated with the population density can be easily and quickly detected using such a system. On the contrary, events with uniformly randomly distributed locations are much harder to detect using a simple crowdsensing-based approach. A second evaluation shows that hybrid systems improve the detection probability and time. Finally, we illustrate how to compute the minimum number of fixed sensors for given detection time thresholds in our exemplary scenario.

@article{info3-article-2021-4, abstract = {Crowdsensing offers a cost-effective way to collect large amounts of environmental sensor data. However, the spatial distribution of crowdsensing sensors can hardly be influenced, as the participants carry the sensors, and, additionally, the quality of the crowdsensed data can vary significantly. Hybrid systems that use mobile users in conjunction with fixed sensors might help to overcome these limitations, as such system allow assessing the quality of the submitted crowdsensed data and provide sensor values where no crowdsensing data is available. In this work, we use a simulation study to first analyze a simple crowdsensing system concerning the detection performance of spatial events to highlight the potential and limitations of a pure crowdsourcing system. The results indicate that even if only a small share of inhabitants participates in crowdsensing, events that have locations correlated with the population density can be easily and quickly detected using such a system. On the contrary, events with uniformly randomly distributed locations are much harder to detect using a simple crowdsensing-based approach. A second evaluation shows that hybrid systems improve the detection probability and time. Finally, we illustrate how to compute the minimum number of fixed sensors for given detection time thresholds in our exemplary scenario.}, author = {Hirth, Matthias and Seufert, Michael and Lange, Stanislav and Meixner, Markus and Tran-Gia, Phuoc}, journal = {Sensors}, keywords = {ucn}, month = {08}, number = 17, pages = {5880 (1-19)}, title = {Performance Evaluation of Hybrid Crowdsensing and Fixed Sensor Systems for Event Detection in Urban Environments}, volume = 21, year = 2021 }

%0 Journal Article %1 info3-article-2021-4 %A Hirth, Matthias %A Seufert, Michael %A Lange, Stanislav %A Meixner, Markus %A Tran-Gia, Phuoc %D 2021 %J Sensors %N 17 %P 5880 (1-19) %T Performance Evaluation of Hybrid Crowdsensing and Fixed Sensor Systems for Event Detection in Urban Environments %V 21 %X Crowdsensing offers a cost-effective way to collect large amounts of environmental sensor data. However, the spatial distribution of crowdsensing sensors can hardly be influenced, as the participants carry the sensors, and, additionally, the quality of the crowdsensed data can vary significantly. Hybrid systems that use mobile users in conjunction with fixed sensors might help to overcome these limitations, as such system allow assessing the quality of the submitted crowdsensed data and provide sensor values where no crowdsensing data is available. In this work, we use a simulation study to first analyze a simple crowdsensing system concerning the detection performance of spatial events to highlight the potential and limitations of a pure crowdsourcing system. The results indicate that even if only a small share of inhabitants participates in crowdsensing, events that have locations correlated with the population density can be easily and quickly detected using such a system. On the contrary, events with uniformly randomly distributed locations are much harder to detect using a simple crowdsensing-based approach. A second evaluation shows that hybrid systems improve the detection probability and time. Finally, we illustrate how to compute the minimum number of fixed sensors for given detection time thresholds in our exemplary scenario.
Cumulative Quality Modeling for HTTP Adaptive Streaming. Tran, Huyen TT; Pham Ngoc, Nam; Hoßfeld, Tobias; Seufert, Michael; Thang, Truong Cong. In ACM Transactions on Multimedia Computing, Communications, and Applications, 17(1), pp. 22 (1–24). 2021.
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@article{info3-article-2021-1, author = {Tran, Huyen TT and Pham Ngoc, Nam and Hoßfeld, Tobias and Seufert, Michael and Thang, Truong Cong}, journal = {ACM Transactions on Multimedia Computing, Communications, and Applications}, keywords = {ucn}, month = {04}, number = 1, pages = {22 (1-24)}, title = {Cumulative Quality Modeling for HTTP Adaptive Streaming}, volume = 17, year = 2021 }

%0 Journal Article %1 info3-article-2021-1 %A Tran, Huyen TT %A Pham Ngoc, Nam %A Hoßfeld, Tobias %A Seufert, Michael %A Thang, Truong Cong %D 2021 %J ACM Transactions on Multimedia Computing, Communications, and Applications %N 1 %P 22 (1-24) %T Cumulative Quality Modeling for HTTP Adaptive Streaming %V 17
Improving Web QoE Monitoring for Encrypted Network Traffic through Time Series Modeling. Wehner, Nikolas; Seufert, Michael; Schüler, Joshua; Wassermann, Sarah; Casas, Pedro; Hoßfeld, Tobias. In ACM SIGMETRICS Performance Evaluation Review, 48(4), pp. 37–40. 2021.
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- [ EndNote ]
This paper addresses the problem of Quality of Experience (QoE) monitoring for web browsing. In particular, the inference of common Web QoE metrics such as Speed Index (SI) is investigated. Based on a large dataset collected with open web-measurement platforms on different device-types, a unique feature set is designed and used to estimate the RUMSI -- an efficient approximation to SI, with machine-learning based regression and classification approaches. Results indicate that it is possible to estimate the RUMSI accurately, and that in particular, recurrent neural networks are highly suitable for the task, as they capture the network dynamics more precisely.

@article{info3-article-2020-4, abstract = {This paper addresses the problem of Quality of Experience (QoE) monitoring for web browsing. In particular, the inference of common Web QoE metrics such as Speed Index (SI) is investigated. Based on a large dataset collected with open web-measurement platforms on different device-types, a unique feature set is designed and used to estimate the RUMSI – an efficient approximation to SI, with machine-learning based regression and classification approaches. Results indicate that it is possible to estimate the RUMSI accurately, and that in particular, recurrent neural networks are highly suitable for the task, as they capture the network dynamics more precisely.}, author = {Wehner, Nikolas and Seufert, Michael and Schüler, Joshua and Wassermann, Sarah and Casas, Pedro and Hoßfeld, Tobias}, journal = {ACM SIGMETRICS Performance Evaluation Review}, keywords = {ucn}, month = {03}, number = 4, pages = {37-40}, title = {Improving Web QoE Monitoring for Encrypted Network Traffic through Time Series Modeling}, volume = 48, year = 2021 }

%0 Journal Article %1 info3-article-2020-4 %A Wehner, Nikolas %A Seufert, Michael %A Schüler, Joshua %A Wassermann, Sarah %A Casas, Pedro %A Hoßfeld, Tobias %D 2021 %J ACM SIGMETRICS Performance Evaluation Review %N 4 %P 37-40 %T Improving Web QoE Monitoring for Encrypted Network Traffic through Time Series Modeling %V 48 %X This paper addresses the problem of Quality of Experience (QoE) monitoring for web browsing. In particular, the inference of common Web QoE metrics such as Speed Index (SI) is investigated. Based on a large dataset collected with open web-measurement platforms on different device-types, a unique feature set is designed and used to estimate the RUMSI -- an efficient approximation to SI, with machine-learning based regression and classification approaches. Results indicate that it is possible to estimate the RUMSI accurately, and that in particular, recurrent neural networks are highly suitable for the task, as they capture the network dynamics more precisely.
Statistical Methods and Models based on Quality of Experience Distributions. Seufert, Michael. In Quality and User Experience, 6(1). 2020.
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Due to biased assumptions on the underlying ordinal rating scale in subjective Quality of Experience (QoE) studies, Mean Opinion Score (MOS)-based evaluations provide results, which are hard to interpret and can be misleading. This paper proposes to consider the full QoE distribution for evaluating, reporting, and modeling QoE results instead of relying on MOS-based metrics derived from results based on ordinal rating scales. The QoE distribution can be represented in a concise way by using the parameters of a multinomial distribution without losing any information about the underlying QoE ratings, and even keeps backward compatibility with previous, biased MOS-based results. Considering QoE results as a realization of a multinomial distribution allows to rely on a well-established theoretical background, which enables meaningful evaluations also for ordinal rating scales. Moreover, QoE models based on QoE distributions keep detailed information from the results of a QoE study of a technical system, and thus, give an unprecedented richness of insights into the end users’ experience with the technical system. In this work, existing and novel statistical methods for QoE distributions are summarized and exemplary evaluations are outlined. Furthermore, using the novel concept of quality steps, simulative and analytical QoE models based on QoE distributions are presented and showcased. The goal is to demonstrate the fundamental advantages of considering QoE distributions over MOS-based evaluations if the underlying rating data is ordinal in nature.

@article{info3-article-2020-7, abstract = {Due to biased assumptions on the underlying ordinal rating scale in subjective Quality of Experience (QoE) studies, Mean Opinion Score (MOS)-based evaluations provide results, which are hard to interpret and can be misleading. This paper proposes to consider the full QoE distribution for evaluating, reporting, and modeling QoE results instead of relying on MOS-based metrics derived from results based on ordinal rating scales. The QoE distribution can be represented in a concise way by using the parameters of a multinomial distribution without losing any information about the underlying QoE ratings, and even keeps backward compatibility with previous, biased MOS-based results. Considering QoE results as a realization of a multinomial distribution allows to rely on a well-established theoretical background, which enables meaningful evaluations also for ordinal rating scales. Moreover, QoE models based on QoE distributions keep detailed information from the results of a QoE study of a technical system, and thus, give an unprecedented richness of insights into the end users’ experience with the technical system. In this work, existing and novel statistical methods for QoE distributions are summarized and exemplary evaluations are outlined. Furthermore, using the novel concept of quality steps, simulative and analytical QoE models based on QoE distributions are presented and showcased. The goal is to demonstrate the fundamental advantages of considering QoE distributions over MOS-based evaluations if the underlying rating data is ordinal in nature.}, author = {Seufert, Michael}, journal = {Quality and User Experience}, keywords = {ucn}, month = 12, number = 1, title = {Statistical Methods and Models based on Quality of Experience Distributions}, volume = 6, year = 2020 }

%0 Journal Article %1 info3-article-2020-7 %A Seufert, Michael %D 2020 %J Quality and User Experience %N 1 %T Statistical Methods and Models based on Quality of Experience Distributions %V 6 %X Due to biased assumptions on the underlying ordinal rating scale in subjective Quality of Experience (QoE) studies, Mean Opinion Score (MOS)-based evaluations provide results, which are hard to interpret and can be misleading. This paper proposes to consider the full QoE distribution for evaluating, reporting, and modeling QoE results instead of relying on MOS-based metrics derived from results based on ordinal rating scales. The QoE distribution can be represented in a concise way by using the parameters of a multinomial distribution without losing any information about the underlying QoE ratings, and even keeps backward compatibility with previous, biased MOS-based results. Considering QoE results as a realization of a multinomial distribution allows to rely on a well-established theoretical background, which enables meaningful evaluations also for ordinal rating scales. Moreover, QoE models based on QoE distributions keep detailed information from the results of a QoE study of a technical system, and thus, give an unprecedented richness of insights into the end users’ experience with the technical system. In this work, existing and novel statistical methods for QoE distributions are summarized and exemplary evaluations are outlined. Furthermore, using the novel concept of quality steps, simulative and analytical QoE models based on QoE distributions are presented and showcased. The goal is to demonstrate the fundamental advantages of considering QoE distributions over MOS-based evaluations if the underlying rating data is ordinal in nature.
ViCrypt to the Rescue: Real-time, Machine-Learning-driven Video-QoE Monitoring for Encrypted Streaming Traffic. Wassermann, Sarah; Seufert, Michael; Casas, Pedro; Li, Gang; Kuang, Li. In IEEE Transactions on Network and Service Management, 17(4), pp. 2007–2023. 2020.
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- [ BibTeX ]
- [ EndNote ]
Video streaming is the killer application of the Internet today. In this paper, we address the problem of real-time, passive Quality-of-Experience (QoE) monitoring of HTTP Adaptive Video Streaming (HAS), from the Internet-Service-Provider (ISP) perspective - i.e., relying exclusively on in-network traffic measurements. Given the wide adoption of end-to-end encryption, we resort to machine-learning (ML) models to estimate multiple key video-QoE indicators (KQIs) from the analysis of the encrypted traffic. We present ViCrypt, an ML-driven monitoring solution able to infer the most important KQIs for HTTP Adaptive Streaming (HAS), namely stalling, initial delay, video resolution, and average video bitrate. ViCrypt performs estimations in real-time, during the playback of an ongoing video-streaming session, with a fine-grained temporal resolution of just one second. For this, it relies on lightweight, stream-like features continuously extracted from the encrypted stream of packets. Empirical evaluations on a large and heterogeneous corpus of YouTube measurements show that ViCrypt can infer the targeted KQIs with high accuracy, enabling large-scale passive video-QoE monitoring and proactive QoE-aware traffic management. Different from the state of the art, and besides real-time operation, ViCrypt is not bound to coarse-grained KQI-classes, providing better and sharper insights than other solutions. Finally, ViCrypt does not require chunk-detection approaches for feature extraction, significantly reducing the complexity of the monitoring approach, and potentially improving on generalization to different HAS protocols used by other video-streaming services such as Netflix and Amazon.

@article{info3-article-2020-5, abstract = {Video streaming is the killer application of the Internet today. In this paper, we address the problem of real-time, passive Quality-of-Experience (QoE) monitoring of HTTP Adaptive Video Streaming (HAS), from the Internet-Service-Provider (ISP) perspective - i.e., relying exclusively on in-network traffic measurements. Given the wide adoption of end-to-end encryption, we resort to machine-learning (ML) models to estimate multiple key video-QoE indicators (KQIs) from the analysis of the encrypted traffic. We present ViCrypt, an ML-driven monitoring solution able to infer the most important KQIs for HTTP Adaptive Streaming (HAS), namely stalling, initial delay, video resolution, and average video bitrate. ViCrypt performs estimations in real-time, during the playback of an ongoing video-streaming session, with a fine-grained temporal resolution of just one second. For this, it relies on lightweight, stream-like features continuously extracted from the encrypted stream of packets. Empirical evaluations on a large and heterogeneous corpus of YouTube measurements show that ViCrypt can infer the targeted KQIs with high accuracy, enabling large-scale passive video-QoE monitoring and proactive QoE-aware traffic management. Different from the state of the art, and besides real-time operation, ViCrypt is not bound to coarse-grained KQI-classes, providing better and sharper insights than other solutions. Finally, ViCrypt does not require chunk-detection approaches for feature extraction, significantly reducing the complexity of the monitoring approach, and potentially improving on generalization to different HAS protocols used by other video-streaming services such as Netflix and Amazon.}, author = {Wassermann, Sarah and Seufert, Michael and Casas, Pedro and Li, Gang and Kuang, Li}, journal = {IEEE Transactions on Network and Service Management}, keywords = {ucn}, month = 12, number = 4, pages = {2007 - 2023}, title = {ViCrypt to the Rescue: Real-time, Machine-Learning-driven Video-QoE Monitoring for Encrypted Streaming Traffic}, volume = 17, year = 2020 }

%0 Journal Article %1 info3-article-2020-5 %A Wassermann, Sarah %A Seufert, Michael %A Casas, Pedro %A Li, Gang %A Kuang, Li %D 2020 %J IEEE Transactions on Network and Service Management %N 4 %P 2007 - 2023 %T ViCrypt to the Rescue: Real-time, Machine-Learning-driven Video-QoE Monitoring for Encrypted Streaming Traffic %V 17 %X Video streaming is the killer application of the Internet today. In this paper, we address the problem of real-time, passive Quality-of-Experience (QoE) monitoring of HTTP Adaptive Video Streaming (HAS), from the Internet-Service-Provider (ISP) perspective - i.e., relying exclusively on in-network traffic measurements. Given the wide adoption of end-to-end encryption, we resort to machine-learning (ML) models to estimate multiple key video-QoE indicators (KQIs) from the analysis of the encrypted traffic. We present ViCrypt, an ML-driven monitoring solution able to infer the most important KQIs for HTTP Adaptive Streaming (HAS), namely stalling, initial delay, video resolution, and average video bitrate. ViCrypt performs estimations in real-time, during the playback of an ongoing video-streaming session, with a fine-grained temporal resolution of just one second. For this, it relies on lightweight, stream-like features continuously extracted from the encrypted stream of packets. Empirical evaluations on a large and heterogeneous corpus of YouTube measurements show that ViCrypt can infer the targeted KQIs with high accuracy, enabling large-scale passive video-QoE monitoring and proactive QoE-aware traffic management. Different from the state of the art, and besides real-time operation, ViCrypt is not bound to coarse-grained KQI-classes, providing better and sharper insights than other solutions. Finally, ViCrypt does not require chunk-detection approaches for feature extraction, significantly reducing the complexity of the monitoring approach, and potentially improving on generalization to different HAS protocols used by other video-streaming services such as Netflix and Amazon.
Considering User Behavior in the Quality of Experience Cycle: Towards Proactive QoE-aware Traffic Management. Seufert, Michael; Wassermann, Sarah; Casas, Pedro. In IEEE Communications Letters, 23(7), pp. 1145–1148. 2019.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
The concept of Quality of Experience (QoE) of Internet services is widely recognized by service providers and network operators. They strive to deliver the best experience to their customers in order to increase revenues and avoid churn. Therefore, QoE is increasingly considered as an integral part of the reactive traffic management cycle of network operators. Additionally, QoE also constitutes a cycle of its own, which includes the user behavior and the service requirements. This work describes this QoE cycle, which is not widely taken into account yet, discusses the interactions of the two cycles, and derives implications towards an improved and proactive QoE-aware traffic management. A showcase on how network operators can obtain hints on the change of network requirements from detecting user behavior in encrypted video traffic is also presented in this paper.

@article{info3-article-2019-5, abstract = {The concept of Quality of Experience (QoE) of Internet services is widely recognized by service providers and network operators. They strive to deliver the best experience to their customers in order to increase revenues and avoid churn. Therefore, QoE is increasingly considered as an integral part of the reactive traffic management cycle of network operators. Additionally, QoE also constitutes a cycle of its own, which includes the user behavior and the service requirements. This work describes this QoE cycle, which is not widely taken into account yet, discusses the interactions of the two cycles, and derives implications towards an improved and proactive QoE-aware traffic management. A showcase on how network operators can obtain hints on the change of network requirements from detecting user behavior in encrypted video traffic is also presented in this paper.}, author = {Seufert, Michael and Wassermann, Sarah and Casas, Pedro}, journal = {IEEE Communications Letters}, keywords = {ua-net}, month = {07}, number = 7, pages = {1145-1148}, title = {Considering User Behavior in the Quality of Experience Cycle: Towards Proactive QoE-aware Traffic Management}, volume = 23, year = 2019 }

%0 Journal Article %1 info3-article-2019-5 %A Seufert, Michael %A Wassermann, Sarah %A Casas, Pedro %D 2019 %J IEEE Communications Letters %N 7 %P 1145-1148 %T Considering User Behavior in the Quality of Experience Cycle: Towards Proactive QoE-aware Traffic Management %V 23 %X The concept of Quality of Experience (QoE) of Internet services is widely recognized by service providers and network operators. They strive to deliver the best experience to their customers in order to increase revenues and avoid churn. Therefore, QoE is increasingly considered as an integral part of the reactive traffic management cycle of network operators. Additionally, QoE also constitutes a cycle of its own, which includes the user behavior and the service requirements. This work describes this QoE cycle, which is not widely taken into account yet, discusses the interactions of the two cycles, and derives implications towards an improved and proactive QoE-aware traffic management. A showcase on how network operators can obtain hints on the change of network requirements from detecting user behavior in encrypted video traffic is also presented in this paper.
A Fair Share for All: TCP-inspired Adaptation Logic for QoE Fairness among Heterogeneous HTTP Adaptive Video Streaming Clients. Seufert, Michael; Wehner, Nikolas; Casas, Pedro. In IEEE Transactions on Network and Service Management, 16(2), pp. 475–488. 2019.
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- [ EndNote ]
@article{info3-article-2019-4, author = {Seufert, Michael and Wehner, Nikolas and Casas, Pedro}, journal = {IEEE Transactions on Network and Service Management}, keywords = {sys:hidden:article}, month = {06}, number = 2, pages = {475-488}, title = {A Fair Share for All: TCP-inspired Adaptation Logic for QoE Fairness among Heterogeneous HTTP Adaptive Video Streaming Clients}, volume = 16, year = 2019 }

%0 Journal Article %1 info3-article-2019-4 %A Seufert, Michael %A Wehner, Nikolas %A Casas, Pedro %D 2019 %J IEEE Transactions on Network and Service Management %N 2 %P 475-488 %T A Fair Share for All: TCP-inspired Adaptation Logic for QoE Fairness among Heterogeneous HTTP Adaptive Video Streaming Clients %V 16
Analytical Model for SDN Signaling Traffic and Flow Table Occupancy and its Application for Various Types of Traffic. Metter, Christopher; Seufert, Michael; Wamser, Florian; Zinner, Thomas; Tran-Gia, Phuoc. In IEEE Transactions on Network and Service Management, 14(3), pp. 603–615. 2017.
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Software Defined Networking (SDN) has emerged as a promising networking paradigm overcoming various drawbacks of current communication networks. The control and data plane of switching devices is decoupled and control functions are centralized at the network controller. In SDN, each new flow introduces additional signaling traffic between the switch and the controller. Based on this traffic, rules are created in the flow table of the switch, which specify the forwarding behavior. To avoid table overflows, unused entries are removed after a predefined time-out period. Given a specific traffic mix, the choice of this time-out period affects the trade-off between signaling rate and table occupancy. As a result, network operators have to adjust this parameter to enable a smooth and efficient network operation. Due to the complexity of this problem caused by the various traffic flows in a network, a suitable abstraction is necessary in order to derive valid parameter values in time. The contribution of this work is threefold. Firstly, we formulate a simple analytical model that allows optimizing the network performance with respect to the table occupancy and the signaling rate. Secondly, we validate the model by means of simulation. Thirdly, we illustrate the impact of the time-out period on the signaling traffic and the flow table occupancy for different data-plane traffic mixes and characteristics. This includes scenarios with single application instances, as well as multiple application instances of different application types in an SDN-enabled network.

@article{info3-article-2017-5, abstract = {Software Defined Networking (SDN) has emerged as a promising networking paradigm overcoming various drawbacks of current communication networks. The control and data plane of switching devices is decoupled and control functions are centralized at the network controller. In SDN, each new flow introduces additional signaling traffic between the switch and the controller. Based on this traffic, rules are created in the flow table of the switch, which specify the forwarding behavior. To avoid table overflows, unused entries are removed after a predefined time-out period. Given a specific traffic mix, the choice of this time-out period affects the trade-off between signaling rate and table occupancy. As a result, network operators have to adjust this parameter to enable a smooth and efficient network operation. Due to the complexity of this problem caused by the various traffic flows in a network, a suitable abstraction is necessary in order to derive valid parameter values in time. The contribution of this work is threefold. Firstly, we formulate a simple analytical model that allows optimizing the network performance with respect to the table occupancy and the signaling rate. Secondly, we validate the model by means of simulation. Thirdly, we illustrate the impact of the time-out period on the signaling traffic and the flow table occupancy for different data-plane traffic mixes and characteristics. This includes scenarios with single application instances, as well as multiple application instances of different application types in an SDN-enabled network.}, author = {Metter, Christopher and Seufert, Michael and Wamser, Florian and Zinner, Thomas and Tran-Gia, Phuoc}, journal = {IEEE Transactions on Network and Service Management}, keywords = {can}, month = {09}, number = 3, pages = {603-615}, title = {Analytical Model for SDN Signaling Traffic and Flow Table Occupancy and its Application for Various Types of Traffic}, volume = 14, year = 2017 }

%0 Journal Article %1 info3-article-2017-5 %A Metter, Christopher %A Seufert, Michael %A Wamser, Florian %A Zinner, Thomas %A Tran-Gia, Phuoc %D 2017 %J IEEE Transactions on Network and Service Management %N 3 %P 603-615 %T Analytical Model for SDN Signaling Traffic and Flow Table Occupancy and its Application for Various Types of Traffic %V 14 %X Software Defined Networking (SDN) has emerged as a promising networking paradigm overcoming various drawbacks of current communication networks. The control and data plane of switching devices is decoupled and control functions are centralized at the network controller. In SDN, each new flow introduces additional signaling traffic between the switch and the controller. Based on this traffic, rules are created in the flow table of the switch, which specify the forwarding behavior. To avoid table overflows, unused entries are removed after a predefined time-out period. Given a specific traffic mix, the choice of this time-out period affects the trade-off between signaling rate and table occupancy. As a result, network operators have to adjust this parameter to enable a smooth and efficient network operation. Due to the complexity of this problem caused by the various traffic flows in a network, a suitable abstraction is necessary in order to derive valid parameter values in time. The contribution of this work is threefold. Firstly, we formulate a simple analytical model that allows optimizing the network performance with respect to the table occupancy and the signaling rate. Secondly, we validate the model by means of simulation. Thirdly, we illustrate the impact of the time-out period on the signaling traffic and the flow table occupancy for different data-plane traffic mixes and characteristics. This includes scenarios with single application instances, as well as multiple application instances of different application types in an SDN-enabled network.
A Discrete-Time Model for Optimizing the Processing Time of Virtualized Network Functions. Zinner, Thomas; Geissler, Stefan; Lange, Stanislav; Gebert, Steffen; Seufert, Michael; Tran-Gia, Phuoc. In Computer Networks, 125, pp. 4–14. 2017.
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The softwarization of networks promises cost savings and better scalability of network functions by moving functionality from specialized devices into commercial off-the-shelf hardware. Generalized computing hardware offers many degrees of adjustment and tuning, which can affect performance and resource utilization. One of these adjustments are interrupt moderation techniques implemented by modern network interface cards and operating systems. Using these, an administrator can optimize either for low latencies or low CPU overhead for processing of network traffic. In this work, an analytical model that allows the computation of relevant performance metrics like packet processing time and packet loss for generic virtualized network functions running on commodity hardware is presented. Based on this model, impact factors like average packet interarrival time, interarrival time distribution, and duration of the interrupt aggregation interval are studied. Furthermore, we significantly improve the computational tractability of this discrete-time model by proving and leveraging a property regarding its limit behavior. We also demonstrate that using this property does not affect the accuracy of the model in the context of realistic parameter combinations. Finally, the improved runtime for numerical evaluations allows administrators to dynamically adapt their interrupt mitigation settings to changing network conditions by recalculating optimal parameters.

@article{info3-article-2017-1, abstract = {The softwarization of networks promises cost savings and better scalability of network functions by moving functionality from specialized devices into commercial off-the-shelf hardware. Generalized computing hardware offers many degrees of adjustment and tuning, which can affect performance and resource utilization. One of these adjustments are interrupt moderation techniques implemented by modern network interface cards and operating systems. Using these, an administrator can optimize either for low latencies or low CPU overhead for processing of network traffic. In this work, an analytical model that allows the computation of relevant performance metrics like packet processing time and packet loss for generic virtualized network functions running on commodity hardware is presented. Based on this model, impact factors like average packet interarrival time, interarrival time distribution, and duration of the interrupt aggregation interval are studied. Furthermore, we significantly improve the computational tractability of this discrete-time model by proving and leveraging a property regarding its limit behavior. We also demonstrate that using this property does not affect the accuracy of the model in the context of realistic parameter combinations. Finally, the improved runtime for numerical evaluations allows administrators to dynamically adapt their interrupt mitigation settings to changing network conditions by recalculating optimal parameters.}, author = {Zinner, Thomas and Geissler, Stefan and Lange, Stanislav and Gebert, Steffen and Seufert, Michael and Tran-Gia, Phuoc}, journal = {Computer Networks}, keywords = {sys:hidden:article}, pages = {4-14}, title = {A Discrete-Time Model for Optimizing the Processing Time of Virtualized Network Functions}, volume = 125, year = 2017 }

%0 Journal Article %1 info3-article-2017-1 %A Zinner, Thomas %A Geissler, Stefan %A Lange, Stanislav %A Gebert, Steffen %A Seufert, Michael %A Tran-Gia, Phuoc %D 2017 %J Computer Networks %P 4-14 %T A Discrete-Time Model for Optimizing the Processing Time of Virtualized Network Functions %V 125 %X The softwarization of networks promises cost savings and better scalability of network functions by moving functionality from specialized devices into commercial off-the-shelf hardware. Generalized computing hardware offers many degrees of adjustment and tuning, which can affect performance and resource utilization. One of these adjustments are interrupt moderation techniques implemented by modern network interface cards and operating systems. Using these, an administrator can optimize either for low latencies or low CPU overhead for processing of network traffic. In this work, an analytical model that allows the computation of relevant performance metrics like packet processing time and packet loss for generic virtualized network functions running on commodity hardware is presented. Based on this model, impact factors like average packet interarrival time, interarrival time distribution, and duration of the interrupt aggregation interval are studied. Furthermore, we significantly improve the computational tractability of this discrete-time model by proving and leveraging a property regarding its limit behavior. We also demonstrate that using this property does not affect the accuracy of the model in the context of realistic parameter combinations. Finally, the improved runtime for numerical evaluations allows administrators to dynamically adapt their interrupt mitigation settings to changing network conditions by recalculating optimal parameters.
Assessment of Subjective Influence and Trust with an Online Social Network Game. Seufert, Michael; Burger, Valentin; Lorey, Karl; Seith, Alexander; Loh, Frank; Tran-Gia, Phuoc. In Computers in Human Behavior, 64, pp. 233–246. 2016.
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The deduction of influence and trust between two individuals only from objective data in online social networks (OSNs) is a rather vague approach. Subjective assessments via surveys produce better results, but are harder to conduct considering the vast amount of friendships of OSN users. This work presents a framework for personalized surveys on relationships in OSNs, which follows a gamification approach. A Facebook game was developed, which was used to subjectively assess social influence and interpersonal trust based on models from psychology. The results show that it is possible to obtain subjective opinions and (limited) objective data about relationships with an OSN game. Also an implicit assessment of influence and trust with subcategory questions is feasible in this case.

@article{info3-article-2016-7, abstract = {The deduction of influence and trust between two individuals only from objective data in online social networks (OSNs) is a rather vague approach. Subjective assessments via surveys produce better results, but are harder to conduct considering the vast amount of friendships of OSN users. This work presents a framework for personalized surveys on relationships in OSNs, which follows a gamification approach. A Facebook game was developed, which was used to subjectively assess social influence and interpersonal trust based on models from psychology. The results show that it is possible to obtain subjective opinions and (limited) objective data about relationships with an OSN game. Also an implicit assessment of influence and trust with subcategory questions is feasible in this case.}, author = {Seufert, Michael and Burger, Valentin and Lorey, Karl and Seith, Alexander and Loh, Frank and Tran-Gia, Phuoc}, journal = {Computers in Human Behavior}, keywords = {can}, month = 11, pages = {233-246}, title = {Assessment of Subjective Influence and Trust with an Online Social Network Game}, volume = 64, year = 2016 }

%0 Journal Article %1 info3-article-2016-7 %A Seufert, Michael %A Burger, Valentin %A Lorey, Karl %A Seith, Alexander %A Loh, Frank %A Tran-Gia, Phuoc %D 2016 %J Computers in Human Behavior %P 233-246 %T Assessment of Subjective Influence and Trust with an Online Social Network Game %V 64 %X The deduction of influence and trust between two individuals only from objective data in online social networks (OSNs) is a rather vague approach. Subjective assessments via surveys produce better results, but are harder to conduct considering the vast amount of friendships of OSN users. This work presents a framework for personalized surveys on relationships in OSNs, which follows a gamification approach. A Facebook game was developed, which was used to subjectively assess social influence and interpersonal trust based on models from psychology. The results show that it is possible to obtain subjective opinions and (limited) objective data about relationships with an OSN game. Also an implicit assessment of influence and trust with subcategory questions is feasible in this case.
Modeling the YouTube Stack: from Packets to Quality of Experience. Wamser, Florian; Casas, Pedro; Seufert, Michael; Moldovan, Christian; Tran-Gia, Phuoc; Hoßfeld, Tobias. In Computer Networks, 109(2), pp. 211–224. 2016.
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YouTube is one of the most popular and volume-dominant services in today’s Internet, and has changed the Web for ever. Consequently, network operators are forced to consider it in the design, deployment, and optimization of their networks. Taming YouTube requires a good understanding of the complete YouTube stack, from the network streaming service to the application itself. Understanding the interplays between individual YouTube functionalities and their implications for traffic and user Quality of Experience (QoE) becomes paramount nowadays. In this paper we characterize and model the YouTube stack at different layers, going from the generated network traffic to the QoE perceived by the users watching YouTube videos. Firstly, we present a network traffic model for the YouTube flow control mechanism, which permits to understand how YouTube provisions video traffic flows to users. Secondly, we investigate how traffic is consumed at the client side, deriving a simple model for the YouTube application. Thirdly, we analyze the implications for the end user, and present a model for the quality as perceived by them. This model is finally integrated into a system for real time QoE-based YouTube monitoring, highly useful to operators to assess the performance of their networks for provisioning YouTube videos. The central parameter for all the presented models is the buffer level at the YouTube application layer. This paper provides an extensive compendium of objective tools and models for network operators to better understand the YouTube traffic in their networks, to predict the playback behavior of the video player, and to assess how well they do it in the practice with the satisfaction of their customers watching YouTube.

@article{info3-article-2016-6, abstract = {YouTube is one of the most popular and volume-dominant services in today’s Internet, and has changed the Web for ever. Consequently, network operators are forced to consider it in the design, deployment, and optimization of their networks. Taming YouTube requires a good understanding of the complete YouTube stack, from the network streaming service to the application itself. Understanding the interplays between individual YouTube functionalities and their implications for traffic and user Quality of Experience (QoE) becomes paramount nowadays. In this paper we characterize and model the YouTube stack at different layers, going from the generated network traffic to the QoE perceived by the users watching YouTube videos. Firstly, we present a network traffic model for the YouTube flow control mechanism, which permits to understand how YouTube provisions video traffic flows to users. Secondly, we investigate how traffic is consumed at the client side, deriving a simple model for the YouTube application. Thirdly, we analyze the implications for the end user, and present a model for the quality as perceived by them. This model is finally integrated into a system for real time QoE-based YouTube monitoring, highly useful to operators to assess the performance of their networks for provisioning YouTube videos. The central parameter for all the presented models is the buffer level at the YouTube application layer. This paper provides an extensive compendium of objective tools and models for network operators to better understand the YouTube traffic in their networks, to predict the playback behavior of the video player, and to assess how well they do it in the practice with the satisfaction of their customers watching YouTube.}, author = {Wamser, Florian and Casas, Pedro and Seufert, Michael and Moldovan, Christian and Tran-Gia, Phuoc and Hoßfeld, Tobias}, journal = {Computer Networks}, keywords = {can}, month = 11, number = 2, pages = {211-224}, title = {Modeling the YouTube Stack: from Packets to Quality of Experience}, volume = 109, year = 2016 }

%0 Journal Article %1 info3-article-2016-6 %A Wamser, Florian %A Casas, Pedro %A Seufert, Michael %A Moldovan, Christian %A Tran-Gia, Phuoc %A Hoßfeld, Tobias %D 2016 %J Computer Networks %N 2 %P 211-224 %T Modeling the YouTube Stack: from Packets to Quality of Experience %V 109 %X YouTube is one of the most popular and volume-dominant services in today’s Internet, and has changed the Web for ever. Consequently, network operators are forced to consider it in the design, deployment, and optimization of their networks. Taming YouTube requires a good understanding of the complete YouTube stack, from the network streaming service to the application itself. Understanding the interplays between individual YouTube functionalities and their implications for traffic and user Quality of Experience (QoE) becomes paramount nowadays. In this paper we characterize and model the YouTube stack at different layers, going from the generated network traffic to the QoE perceived by the users watching YouTube videos. Firstly, we present a network traffic model for the YouTube flow control mechanism, which permits to understand how YouTube provisions video traffic flows to users. Secondly, we investigate how traffic is consumed at the client side, deriving a simple model for the YouTube application. Thirdly, we analyze the implications for the end user, and present a model for the quality as perceived by them. This model is finally integrated into a system for real time QoE-based YouTube monitoring, highly useful to operators to assess the performance of their networks for provisioning YouTube videos. The central parameter for all the presented models is the buffer level at the YouTube application layer. This paper provides an extensive compendium of objective tools and models for network operators to better understand the YouTube traffic in their networks, to predict the playback behavior of the video player, and to assess how well they do it in the practice with the satisfaction of their customers watching YouTube.
Perceptual Quality of HTTP Adaptive Streaming Strategies: Cross-Experimental Analysis of Multi-Laboratory and Crowdsourced Subjective Studies. Tavakoli, Samira; Egger, Sebastian; Seufert, Michael; Schatz, Raimund; Brunnström, Kjell; García, Narciso. In IEEE Journal on Selected Areas in Communications, 34(8), pp. 2141–2153. 2016.
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Today’s packet-switched networks are subject to bandwidth fluctuations that cause for degradation of user experience of multimedia services. In order to cope with this problem, HTTP Adaptive Streaming (HAS) has been proposed in recent years as a video delivery solution for the future Internet and being adopted by an increasing number of streaming services such as Netflix and Youtube. HAS enables service providers to improve users’ Quality of Experience (QoE) and network resource utilization by adapting the quality of the video stream to the current network conditions. However, the resulting timevarying video quality caused by adaptation introduces a new type of impairment and thus novel QoE research challenges. Despite of various recent attempts to investigate these challenges, many fundamental questions regarding HAS perceptual performance are still open. In this paper, the QoE impact of different technical adaptation parameters including chunk length, switching amplitude, switching frequency and temporal recency are investigated. In addition, the influence of content on perceptual quality of these parameters is analyzed. To this end, a large number of adaptation scenarios have been subjectively evaluated in four laboratory experiments and one crowdsourcing study. Statistical analysis of the combined dataset reveals results that partly contradict widely held assumptions and provide novel insights in perceptual quality of adapted video sequences, e.g. interaction effects between quality switching direction (up/down) and switching strategy (smooth/abrupt). The large variety of experimental configurations across different studies ensures the consistency and external validity of the presented results that can be utilized for enhancing the perceptual performance of adaptive streaming services.

@article{info3-article-2016-5, abstract = {Today’s packet-switched networks are subject to bandwidth fluctuations that cause for degradation of user experience of multimedia services. In order to cope with this problem, HTTP Adaptive Streaming (HAS) has been proposed in recent years as a video delivery solution for the future Internet and being adopted by an increasing number of streaming services such as Netflix and Youtube. HAS enables service providers to improve users’ Quality of Experience (QoE) and network resource utilization by adapting the quality of the video stream to the current network conditions. However, the resulting timevarying video quality caused by adaptation introduces a new type of impairment and thus novel QoE research challenges. Despite of various recent attempts to investigate these challenges, many fundamental questions regarding HAS perceptual performance are still open. In this paper, the QoE impact of different technical adaptation parameters including chunk length, switching amplitude, switching frequency and temporal recency are investigated. In addition, the influence of content on perceptual quality of these parameters is analyzed. To this end, a large number of adaptation scenarios have been subjectively evaluated in four laboratory experiments and one crowdsourcing study. Statistical analysis of the combined dataset reveals results that partly contradict widely held assumptions and provide novel insights in perceptual quality of adapted video sequences, e.g. interaction effects between quality switching direction (up/down) and switching strategy (smooth/abrupt). The large variety of experimental configurations across different studies ensures the consistency and external validity of the presented results that can be utilized for enhancing the perceptual performance of adaptive streaming services.}, author = {Tavakoli, Samira and Egger, Sebastian and Seufert, Michael and Schatz, Raimund and Brunnström, Kjell and García, Narciso}, journal = {IEEE Journal on Selected Areas in Communications}, keywords = {can}, month = {06}, number = 8, pages = {2141-2153}, title = {Perceptual Quality of HTTP Adaptive Streaming Strategies: Cross-Experimental Analysis of Multi-Laboratory and Crowdsourced Subjective Studies}, volume = 34, year = 2016 }

%0 Journal Article %1 info3-article-2016-5 %A Tavakoli, Samira %A Egger, Sebastian %A Seufert, Michael %A Schatz, Raimund %A Brunnström, Kjell %A García, Narciso %D 2016 %J IEEE Journal on Selected Areas in Communications %N 8 %P 2141-2153 %T Perceptual Quality of HTTP Adaptive Streaming Strategies: Cross-Experimental Analysis of Multi-Laboratory and Crowdsourced Subjective Studies %V 34 %X Today’s packet-switched networks are subject to bandwidth fluctuations that cause for degradation of user experience of multimedia services. In order to cope with this problem, HTTP Adaptive Streaming (HAS) has been proposed in recent years as a video delivery solution for the future Internet and being adopted by an increasing number of streaming services such as Netflix and Youtube. HAS enables service providers to improve users’ Quality of Experience (QoE) and network resource utilization by adapting the quality of the video stream to the current network conditions. However, the resulting timevarying video quality caused by adaptation introduces a new type of impairment and thus novel QoE research challenges. Despite of various recent attempts to investigate these challenges, many fundamental questions regarding HAS perceptual performance are still open. In this paper, the QoE impact of different technical adaptation parameters including chunk length, switching amplitude, switching frequency and temporal recency are investigated. In addition, the influence of content on perceptual quality of these parameters is analyzed. To this end, a large number of adaptation scenarios have been subjectively evaluated in four laboratory experiments and one crowdsourcing study. Statistical analysis of the combined dataset reveals results that partly contradict widely held assumptions and provide novel insights in perceptual quality of adapted video sequences, e.g. interaction effects between quality switching direction (up/down) and switching strategy (smooth/abrupt). The large variety of experimental configurations across different studies ensures the consistency and external validity of the presented results that can be utilized for enhancing the perceptual performance of adaptive streaming services.
Performance Evaluation of Backhaul Bandwidth Aggregation Using a Partial Sharing Scheme. Burger, Valentin; Seufert, Michael; Hoßfeld, Tobias; Tran-Gia, Phuoc. In Physical Communication, 19, pp. 135–144. 2016.
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To cope with the increasing demand of mobile devices and the limited capacity of cellular networks mobile connections are offloaded to WiFi. The access capacity is further increased, by aggregating bandwidth of WiFi access links. To analyse the performance of aggregated access links we model the most simple case of two cooperating systems interchanging capacities using an offloading scheme. The resulting analytic model is computed by means of a two-dimensional birth and death process. It can be used to seamlessly evaluate the performance of systems between partitioning and complete sharing. This allows to optimize the setting of thresholds dependent on the load of the cooperating system. Furthermore the benefit of aggregating bandwidth in different scenarios with homogeneous and heterogeneous workloads is quantified and the performance of more than two cooperating systems is evaluated by simulation.

@article{info3-article-2016-3, abstract = {To cope with the increasing demand of mobile devices and the limited capacity of cellular networks mobile connections are offloaded to WiFi. The access capacity is further increased, by aggregating bandwidth of WiFi access links. To analyse the performance of aggregated access links we model the most simple case of two cooperating systems interchanging capacities using an offloading scheme. The resulting analytic model is computed by means of a two-dimensional birth and death process. It can be used to seamlessly evaluate the performance of systems between partitioning and complete sharing. This allows to optimize the setting of thresholds dependent on the load of the cooperating system. Furthermore the benefit of aggregating bandwidth in different scenarios with homogeneous and heterogeneous workloads is quantified and the performance of more than two cooperating systems is evaluated by simulation.}, author = {Burger, Valentin and Seufert, Michael and Hoßfeld, Tobias and Tran-Gia, Phuoc}, journal = {Physical Communication}, keywords = {can}, month = {06}, pages = {135-144}, title = {Performance Evaluation of Backhaul Bandwidth Aggregation Using a Partial Sharing Scheme}, volume = 19, year = 2016 }

%0 Journal Article %1 info3-article-2016-3 %A Burger, Valentin %A Seufert, Michael %A Hoßfeld, Tobias %A Tran-Gia, Phuoc %D 2016 %J Physical Communication %P 135-144 %T Performance Evaluation of Backhaul Bandwidth Aggregation Using a Partial Sharing Scheme %V 19 %X To cope with the increasing demand of mobile devices and the limited capacity of cellular networks mobile connections are offloaded to WiFi. The access capacity is further increased, by aggregating bandwidth of WiFi access links. To analyse the performance of aggregated access links we model the most simple case of two cooperating systems interchanging capacities using an offloading scheme. The resulting analytic model is computed by means of a two-dimensional birth and death process. It can be used to seamlessly evaluate the performance of systems between partitioning and complete sharing. This allows to optimize the setting of thresholds dependent on the load of the cooperating system. Furthermore the benefit of aggregating bandwidth in different scenarios with homogeneous and heterogeneous workloads is quantified and the performance of more than two cooperating systems is evaluated by simulation.
Next to You: Monitoring Quality of Experience in Cellular Networks from the End-devices. Casas, Pedro; Seufert, Michael; Wamser, Florian; Gardlo, Bruno; Sackl, Andreas; Schatz, Raimund. In IEEE Transactions on Network and Service Management, 13(2), pp. 181–196. 2016.
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A quarter of the world population will be using smartphones to access the Internet in the near future. In this context, understanding the Quality of Experience (QoE) of popular apps in such devices becomes paramount to cellular network operators, who need to offer high quality levels to reduce the risks of customers churning for quality dissatisfaction. In this paper we address the problem of QoE provisioning in smartphones from a double perspective, combining the results obtained from subjective lab tests with end-device passive measurements and QoE crowd-sourced feedback obtained in operational cellular networks. The study addresses the impact of both access bandwidth and latency on the QoE of five different services and mobile apps: YouTube, Facebook, Web browsing through Chrome, Google Maps, and WhatsApp. We evaluate the influence of both constant and dynamically changing network access conditions, tackling in particular the case of fluctuating downlink bandwidth, which is typical in cellular networks. As a main contribution, we show that the results obtained in the lab are highly applicable in the live scenario, as mappings track the QoE provided by users in real networks. We additionally provide hints and bandwidth thresholds for good QoE levels on such apps, as well as discussion on end-device passive measurements and analysis. The results presented in this paper provide a sound basis to better understand the QoE requirements of popular mobile apps, as well as for monitoring the underlying provisioning network. To the best of our knowledge, this is the first paper providing such a comprehensive analysis of QoE in mobile devices, combining network measurements with users QoE feedback in lab tests and operational networks.

@article{info3-article-2016-4, abstract = {A quarter of the world population will be using smartphones to access the Internet in the near future. In this context, understanding the Quality of Experience (QoE) of popular apps in such devices becomes paramount to cellular network operators, who need to offer high quality levels to reduce the risks of customers churning for quality dissatisfaction. In this paper we address the problem of QoE provisioning in smartphones from a double perspective, combining the results obtained from subjective lab tests with end-device passive measurements and QoE crowd-sourced feedback obtained in operational cellular networks. The study addresses the impact of both access bandwidth and latency on the QoE of five different services and mobile apps: YouTube, Facebook, Web browsing through Chrome, Google Maps, and WhatsApp. We evaluate the influence of both constant and dynamically changing network access conditions, tackling in particular the case of fluctuating downlink bandwidth, which is typical in cellular networks. As a main contribution, we show that the results obtained in the lab are highly applicable in the live scenario, as mappings track the QoE provided by users in real networks. We additionally provide hints and bandwidth thresholds for good QoE levels on such apps, as well as discussion on end-device passive measurements and analysis. The results presented in this paper provide a sound basis to better understand the QoE requirements of popular mobile apps, as well as for monitoring the underlying provisioning network. To the best of our knowledge, this is the first paper providing such a comprehensive analysis of QoE in mobile devices, combining network measurements with users QoE feedback in lab tests and operational networks.}, author = {Casas, Pedro and Seufert, Michael and Wamser, Florian and Gardlo, Bruno and Sackl, Andreas and Schatz, Raimund}, journal = {IEEE Transactions on Network and Service Management}, keywords = {can}, month = {03}, number = 2, pages = {181-196}, title = {Next to You: Monitoring Quality of Experience in Cellular Networks from the End-devices}, volume = 13, year = 2016 }

%0 Journal Article %1 info3-article-2016-4 %A Casas, Pedro %A Seufert, Michael %A Wamser, Florian %A Gardlo, Bruno %A Sackl, Andreas %A Schatz, Raimund %D 2016 %J IEEE Transactions on Network and Service Management %N 2 %P 181-196 %T Next to You: Monitoring Quality of Experience in Cellular Networks from the End-devices %V 13 %X A quarter of the world population will be using smartphones to access the Internet in the near future. In this context, understanding the Quality of Experience (QoE) of popular apps in such devices becomes paramount to cellular network operators, who need to offer high quality levels to reduce the risks of customers churning for quality dissatisfaction. In this paper we address the problem of QoE provisioning in smartphones from a double perspective, combining the results obtained from subjective lab tests with end-device passive measurements and QoE crowd-sourced feedback obtained in operational cellular networks. The study addresses the impact of both access bandwidth and latency on the QoE of five different services and mobile apps: YouTube, Facebook, Web browsing through Chrome, Google Maps, and WhatsApp. We evaluate the influence of both constant and dynamically changing network access conditions, tackling in particular the case of fluctuating downlink bandwidth, which is typical in cellular networks. As a main contribution, we show that the results obtained in the lab are highly applicable in the live scenario, as mappings track the QoE provided by users in real networks. We additionally provide hints and bandwidth thresholds for good QoE levels on such apps, as well as discussion on end-device passive measurements and analysis. The results presented in this paper provide a sound basis to better understand the QoE requirements of popular mobile apps, as well as for monitoring the underlying provisioning network. To the best of our knowledge, this is the first paper providing such a comprehensive analysis of QoE in mobile devices, combining network measurements with users QoE feedback in lab tests and operational networks.
A Simple WiFi Hotspot Model for Cities. Seufert, Michael; Griepentrog, Tobias; Burger, Valentin; Hoßfeld, Tobias. In IEEE Communications Letters, 20(2), pp. 384–387. 2016.
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WiFi offloading has become increasingly popular. Many private and public institutions (e.g., libraries, cafes, restaurants) already provide an alternative free Internet link via WiFi, but also commercial services emerge to mitigate the load on mobile networks. Moreover, smart cities start to establish WiFi infrastructure for current and future civic services. In this work, the hotspot locations of ten diverse large cities are characterized, and a surprisingly simple model for the distribution of WiFi hotspots in an urban environment is derived.

@article{info3-article-2016-2, abstract = {WiFi offloading has become increasingly popular. Many private and public institutions (e.g., libraries, cafes, restaurants) already provide an alternative free Internet link via WiFi, but also commercial services emerge to mitigate the load on mobile networks. Moreover, smart cities start to establish WiFi infrastructure for current and future civic services. In this work, the hotspot locations of ten diverse large cities are characterized, and a surprisingly simple model for the distribution of WiFi hotspots in an urban environment is derived.}, author = {Seufert, Michael and Griepentrog, Tobias and Burger, Valentin and Hoßfeld, Tobias}, journal = {IEEE Communications Letters}, keywords = {can}, month = {02}, number = 2, pages = {384 - 387}, title = {A Simple WiFi Hotspot Model for Cities}, volume = 20, year = 2016 }

%0 Journal Article %1 info3-article-2016-2 %A Seufert, Michael %A Griepentrog, Tobias %A Burger, Valentin %A Hoßfeld, Tobias %D 2016 %J IEEE Communications Letters %N 2 %P 384 - 387 %T A Simple WiFi Hotspot Model for Cities %V 20 %X WiFi offloading has become increasingly popular. Many private and public institutions (e.g., libraries, cafes, restaurants) already provide an alternative free Internet link via WiFi, but also commercial services emerge to mitigate the load on mobile networks. Moreover, smart cities start to establish WiFi infrastructure for current and future civic services. In this work, the hotspot locations of ten diverse large cities are characterized, and a surprisingly simple model for the distribution of WiFi hotspots in an urban environment is derived.
More than Topology: Joint Topology and Attribute Sampling and Generation of Social Network Graphs. Seufert, Michael; Lange, Stanislav; Hoßfeld, Tobias. In Computer Communications, 73(Part B), pp. 176–187. 2016.
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Graph sampling refers to the process of deriving a small subset of nodes from a possibly huge graph in order to estimate properties of the whole graph from examining the sample. Whereas topological properties can already be obtained accurately by sampling, current approaches do not take possibly hidden dependencies between node topology and attributes into account. Especially in the context of online social networks, node attributes are of importance as they correspond to properties of the social network's users. Therefore, existing sampling algorithms can be extended to attribute sampling, but still lack the capturing of structural properties. Analyzing topology (e.g., node degree, clustering coefficient) and attribute properties (e.g., age, location) jointly can provide valuable insights into the social network and allows for a better understanding of social processes. As major contribution, this work proposes a novel sampling algorithm which provides unbiased and reliable estimates of joint topological and attribute based graph properties in a resource efficient fashion. Furthermore, the obtained samples allow for the generation of synthetic graphs, which show high similarity to the original graph with respect to topology and attributes. The proposed sampling and generation algorithms are evaluated on real world social network graphs, for which they demonstrate to be effective.

@article{info3-article-2016-1, abstract = {Graph sampling refers to the process of deriving a small subset of nodes from a possibly huge graph in order to estimate properties of the whole graph from examining the sample. Whereas topological properties can already be obtained accurately by sampling, current approaches do not take possibly hidden dependencies between node topology and attributes into account. Especially in the context of online social networks, node attributes are of importance as they correspond to properties of the social network's users. Therefore, existing sampling algorithms can be extended to attribute sampling, but still lack the capturing of structural properties. Analyzing topology (e.g., node degree, clustering coefficient) and attribute properties (e.g., age, location) jointly can provide valuable insights into the social network and allows for a better understanding of social processes. As major contribution, this work proposes a novel sampling algorithm which provides unbiased and reliable estimates of joint topological and attribute based graph properties in a resource efficient fashion. Furthermore, the obtained samples allow for the generation of synthetic graphs, which show high similarity to the original graph with respect to topology and attributes. The proposed sampling and generation algorithms are evaluated on real world social network graphs, for which they demonstrate to be effective.}, author = {Seufert, Michael and Lange, Stanislav and Hoßfeld, Tobias}, journal = {Computer Communications}, keywords = {can}, month = {01}, number = {Part B}, pages = {176-187}, title = {More than Topology: Joint Topology and Attribute Sampling and Generation of Social Network Graphs}, volume = 73, year = 2016 }

%0 Journal Article %1 info3-article-2016-1 %A Seufert, Michael %A Lange, Stanislav %A Hoßfeld, Tobias %D 2016 %J Computer Communications %N Part B %P 176-187 %T More than Topology: Joint Topology and Attribute Sampling and Generation of Social Network Graphs %V 73 %X Graph sampling refers to the process of deriving a small subset of nodes from a possibly huge graph in order to estimate properties of the whole graph from examining the sample. Whereas topological properties can already be obtained accurately by sampling, current approaches do not take possibly hidden dependencies between node topology and attributes into account. Especially in the context of online social networks, node attributes are of importance as they correspond to properties of the social network's users. Therefore, existing sampling algorithms can be extended to attribute sampling, but still lack the capturing of structural properties. Analyzing topology (e.g., node degree, clustering coefficient) and attribute properties (e.g., age, location) jointly can provide valuable insights into the social network and allows for a better understanding of social processes. As major contribution, this work proposes a novel sampling algorithm which provides unbiased and reliable estimates of joint topological and attribute based graph properties in a resource efficient fashion. Furthermore, the obtained samples allow for the generation of synthetic graphs, which show high similarity to the original graph with respect to topology and attributes. The proposed sampling and generation algorithms are evaluated on real world social network graphs, for which they demonstrate to be effective.
Modeling and Performance Analysis of Application-Aware Resource Management. Wamser, Florian; Blenk, Andreas; Seufert, Michael; Zinner, Thomas; Kellerer, Wolfgang; Tran-Gia, Phuoc. In International Journal of Network Management, 25, pp. 223–241. 2015.
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Application-aware resource management is the approach to tailor access networks to have characteristics beneficial for the running applications and services. This is achieved through the monitoring and integration of key performance indicators from the application layer within the network resource management. The aim is to increase user-perceived quality and network resource efficiency by traffic engineering with the help of these indicators. Using analytic and simulative approaches, this paper provides analysis methods for network operators to quantify the performance gains of alternative resource allocation algorithms that implement the application-aware concept. Network operators can use the proposed methods to evaluate possible performance gain trade-offs between investing in a pure capacity increase (over-provisioning) and the realization of an application-aware resource allocation. For this purpose, we model and analyze the application quality trade-offs of four algorithms for application-aware resource management at a single link in varying traffic situations. The algorithms are chosen with respect to different complexity and implementation level in order to cover the design space in a systematic way. The study of the algorithms focuses on the application-layer performance for the most used applications today, namely web browsing and video streaming with constant bit-rate as well as HTTP progressive streaming with variable bit-rate. Application quality trade-offs are analyzed in particular for a high resource utilization at a bottleneck link. The results confirm that application-aware resource management outperforms best-effort resource management in terms of QoE. Moreover, our study provides guidelines for the selection and configuration of the evaluated algorithms.

@article{info3-article-2015-134, abstract = {Application-aware resource management is the approach to tailor access networks to have characteristics beneficial for the running applications and services. This is achieved through the monitoring and integration of key performance indicators from the application layer within the network resource management. The aim is to increase user-perceived quality and network resource efficiency by traffic engineering with the help of these indicators. Using analytic and simulative approaches, this paper provides analysis methods for network operators to quantify the performance gains of alternative resource allocation algorithms that implement the application-aware concept. Network operators can use the proposed methods to evaluate possible performance gain trade-offs between investing in a pure capacity increase (over-provisioning) and the realization of an application-aware resource allocation. For this purpose, we model and analyze the application quality trade-offs of four algorithms for application-aware resource management at a single link in varying traffic situations. The algorithms are chosen with respect to different complexity and implementation level in order to cover the design space in a systematic way. The study of the algorithms focuses on the application-layer performance for the most used applications today, namely web browsing and video streaming with constant bit-rate as well as HTTP progressive streaming with variable bit-rate. Application quality trade-offs are analyzed in particular for a high resource utilization at a bottleneck link. The results confirm that application-aware resource management outperforms best-effort resource management in terms of QoE. Moreover, our study provides guidelines for the selection and configuration of the evaluated algorithms.}, author = {Wamser, Florian and Blenk, Andreas and Seufert, Michael and Zinner, Thomas and Kellerer, Wolfgang and Tran-Gia, Phuoc}, journal = {International Journal of Network Management}, keywords = {sys:hidden:article}, month = {07}, pages = {223-241}, title = {Modeling and Performance Analysis of Application-Aware Resource Management}, volume = 25, year = 2015 }

%0 Journal Article %1 info3-article-2015-134 %A Wamser, Florian %A Blenk, Andreas %A Seufert, Michael %A Zinner, Thomas %A Kellerer, Wolfgang %A Tran-Gia, Phuoc %D 2015 %J International Journal of Network Management %P 223-241 %T Modeling and Performance Analysis of Application-Aware Resource Management %V 25 %X Application-aware resource management is the approach to tailor access networks to have characteristics beneficial for the running applications and services. This is achieved through the monitoring and integration of key performance indicators from the application layer within the network resource management. The aim is to increase user-perceived quality and network resource efficiency by traffic engineering with the help of these indicators. Using analytic and simulative approaches, this paper provides analysis methods for network operators to quantify the performance gains of alternative resource allocation algorithms that implement the application-aware concept. Network operators can use the proposed methods to evaluate possible performance gain trade-offs between investing in a pure capacity increase (over-provisioning) and the realization of an application-aware resource allocation. For this purpose, we model and analyze the application quality trade-offs of four algorithms for application-aware resource management at a single link in varying traffic situations. The algorithms are chosen with respect to different complexity and implementation level in order to cover the design space in a systematic way. The study of the algorithms focuses on the application-layer performance for the most used applications today, namely web browsing and video streaming with constant bit-rate as well as HTTP progressive streaming with variable bit-rate. Application quality trade-offs are analyzed in particular for a high resource utilization at a bottleneck link. The results confirm that application-aware resource management outperforms best-effort resource management in terms of QoE. Moreover, our study provides guidelines for the selection and configuration of the evaluated algorithms.
Identifying QoE Optimal Adaptation of HTTP Adaptive Streaming Based on Subjective Studies. Hoßfeld, Tobias; Seufert, Michael; Sieber, Christian; Zinner, Thomas; Tran-Gia, Phuoc. In Computer Networks, 81, pp. 320–332. 2015.
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HTTP Adaptive Streaming (HAS) technologies, e.g., Apple HLS or MPEG-DASH, automatically adapt the delivered video quality to the available network. This reduces stalling of the video but additionally introduces quality switches, which also influence the user-perceived Quality of Experience (QoE). In this work, we conduct a subjective study to identify the impact of adaptation parameters on QoE. The results indicate that the video quality has to be maximized first, and that the number of quality switches is less important. Based on these results, a method to compute the optimal QoE-optimal adaptation strategy for HAS on a per user basis with mixed-integer linear programming is presented. This QoE-optimal adaptation enables the benchmarking of existing adaptation algorithms for any given network condition. Moreover, the investigated concept is extended to a multi-user IPTV scenario. The question is answered whether video quality, and thereby, the QoE can be shared in a fair manner among the involved users.

@article{info3-article-2015-132, abstract = {HTTP Adaptive Streaming (HAS) technologies, e.g., Apple HLS or MPEG-DASH, automatically adapt the delivered video quality to the available network. This reduces stalling of the video but additionally introduces quality switches, which also influence the user-perceived Quality of Experience (QoE). In this work, we conduct a subjective study to identify the impact of adaptation parameters on QoE. The results indicate that the video quality has to be maximized first, and that the number of quality switches is less important. Based on these results, a method to compute the optimal QoE-optimal adaptation strategy for HAS on a per user basis with mixed-integer linear programming is presented. This QoE-optimal adaptation enables the benchmarking of existing adaptation algorithms for any given network condition. Moreover, the investigated concept is extended to a multi-user IPTV scenario. The question is answered whether video quality, and thereby, the QoE can be shared in a fair manner among the involved users.}, author = {Hoßfeld, Tobias and Seufert, Michael and Sieber, Christian and Zinner, Thomas and Tran-Gia, Phuoc}, journal = {Computer Networks}, keywords = {sys:hidden:article}, month = {04}, pages = {320-332}, title = {Identifying QoE Optimal Adaptation of HTTP Adaptive Streaming Based on Subjective Studies}, volume = 81, year = 2015 }

%0 Journal Article %1 info3-article-2015-132 %A Hoßfeld, Tobias %A Seufert, Michael %A Sieber, Christian %A Zinner, Thomas %A Tran-Gia, Phuoc %D 2015 %J Computer Networks %P 320-332 %T Identifying QoE Optimal Adaptation of HTTP Adaptive Streaming Based on Subjective Studies %V 81 %X HTTP Adaptive Streaming (HAS) technologies, e.g., Apple HLS or MPEG-DASH, automatically adapt the delivered video quality to the available network. This reduces stalling of the video but additionally introduces quality switches, which also influence the user-perceived Quality of Experience (QoE). In this work, we conduct a subjective study to identify the impact of adaptation parameters on QoE. The results indicate that the video quality has to be maximized first, and that the number of quality switches is less important. Based on these results, a method to compute the optimal QoE-optimal adaptation strategy for HAS on a per user basis with mixed-integer linear programming is presented. This QoE-optimal adaptation enables the benchmarking of existing adaptation algorithms for any given network condition. Moreover, the investigated concept is extended to a multi-user IPTV scenario. The question is answered whether video quality, and thereby, the QoE can be shared in a fair manner among the involved users.
A Survey on Quality of Experience of HTTP Adaptive Streaming. Seufert, Michael; Egger, Sebastian; Slanina, Martin; Zinner, Thomas; Hoßfeld, Tobias; Tran-Gia, Phuoc. In IEEE Communications Surveys & Tutorials, 17, pp. 469–492. 2015.
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Changing network conditions pose severe problems to video streaming in the Internet. HTTP adaptive streaming (HAS) is a technology employed by numerous video services which relieves these issues by adapting the video to the current network conditions. It enables service providers to improve resource utilization and Quality of Experience (QoE) by incorporating information from different layers in order to deliver and adapt a video in its best possible quality. Thereby, it allows to take into account end user device capabilities, available video quality levels, current network conditions, and current server load. For end users, the major benefits of HAS compared to classical HTTP video streaming are reduced interruptions of the video playback and higher bandwidth utilization, which both generally result in a higher QoE. Adaptation is possible by changing the frame rate, resolution, or quantization of the video, which can be done with various adaptation strategies and related client- and server-side actions. The technical development of HAS, existing open standardized solutions, but also proprietary solutions are reviewed in this article as fundament to derive the QoE influence factors which emerge as a result of adaptation. The main contribution is a comprehensive survey of QoE related works from human computer interaction and networking domains which are structured according to the QoE impact of video adaptation. To be more precise, subjective studies which cover QoE aspects of adaptation dimensions and strategies are revisited. As a result, QoE influence factors of HAS and corresponding QoE models are identified, but also open issues and conflicting results are discussed. Furthermore, technical influence factors, which are often ignored in the context of HAS, affect perceptual QoE influence factors and are consequently analyzed. This survey gives the reader an overview of the current state of the art and recent developments. At the same time it targets networking researchers who develop new solutions for HTTP video streaming or assess video streaming from a user centric point of view. Therefore, the article is a major step towards truly improving HAS.

@article{info3-article-2015-126, abstract = {Changing network conditions pose severe problems to video streaming in the Internet. HTTP adaptive streaming (HAS) is a technology employed by numerous video services which relieves these issues by adapting the video to the current network conditions. It enables service providers to improve resource utilization and Quality of Experience (QoE) by incorporating information from different layers in order to deliver and adapt a video in its best possible quality. Thereby, it allows to take into account end user device capabilities, available video quality levels, current network conditions, and current server load. For end users, the major benefits of HAS compared to classical HTTP video streaming are reduced interruptions of the video playback and higher bandwidth utilization, which both generally result in a higher QoE. Adaptation is possible by changing the frame rate, resolution, or quantization of the video, which can be done with various adaptation strategies and related client- and server-side actions. The technical development of HAS, existing open standardized solutions, but also proprietary solutions are reviewed in this article as fundament to derive the QoE influence factors which emerge as a result of adaptation. The main contribution is a comprehensive survey of QoE related works from human computer interaction and networking domains which are structured according to the QoE impact of video adaptation. To be more precise, subjective studies which cover QoE aspects of adaptation dimensions and strategies are revisited. As a result, QoE influence factors of HAS and corresponding QoE models are identified, but also open issues and conflicting results are discussed. Furthermore, technical influence factors, which are often ignored in the context of HAS, affect perceptual QoE influence factors and are consequently analyzed. This survey gives the reader an overview of the current state of the art and recent developments. At the same time it targets networking researchers who develop new solutions for HTTP video streaming or assess video streaming from a user centric point of view. Therefore, the article is a major step towards truly improving HAS.}, author = {Seufert, Michael and Egger, Sebastian and Slanina, Martin and Zinner, Thomas and Hoßfeld, Tobias and Tran-Gia, Phuoc}, journal = {IEEE Communications Surveys & Tutorials}, keywords = {sys:hidden:article}, month = {03}, pages = {469-492}, title = {A Survey on Quality of Experience of HTTP Adaptive Streaming}, volume = 17, year = 2015 }

%0 Journal Article %1 info3-article-2015-126 %A Seufert, Michael %A Egger, Sebastian %A Slanina, Martin %A Zinner, Thomas %A Hoßfeld, Tobias %A Tran-Gia, Phuoc %D 2015 %J IEEE Communications Surveys & Tutorials %P 469-492 %T A Survey on Quality of Experience of HTTP Adaptive Streaming %V 17 %X Changing network conditions pose severe problems to video streaming in the Internet. HTTP adaptive streaming (HAS) is a technology employed by numerous video services which relieves these issues by adapting the video to the current network conditions. It enables service providers to improve resource utilization and Quality of Experience (QoE) by incorporating information from different layers in order to deliver and adapt a video in its best possible quality. Thereby, it allows to take into account end user device capabilities, available video quality levels, current network conditions, and current server load. For end users, the major benefits of HAS compared to classical HTTP video streaming are reduced interruptions of the video playback and higher bandwidth utilization, which both generally result in a higher QoE. Adaptation is possible by changing the frame rate, resolution, or quantization of the video, which can be done with various adaptation strategies and related client- and server-side actions. The technical development of HAS, existing open standardized solutions, but also proprietary solutions are reviewed in this article as fundament to derive the QoE influence factors which emerge as a result of adaptation. The main contribution is a comprehensive survey of QoE related works from human computer interaction and networking domains which are structured according to the QoE impact of video adaptation. To be more precise, subjective studies which cover QoE aspects of adaptation dimensions and strategies are revisited. As a result, QoE influence factors of HAS and corresponding QoE models are identified, but also open issues and conflicting results are discussed. Furthermore, technical influence factors, which are often ignored in the context of HAS, affect perceptual QoE influence factors and are consequently analyzed. This survey gives the reader an overview of the current state of the art and recent developments. At the same time it targets networking researchers who develop new solutions for HTTP video streaming or assess video streaming from a user centric point of view. Therefore, the article is a major step towards truly improving HAS.
Close to Optimum? User-centric Evaluation of Adaptation Logics for HTTP Adaptive Streaming. Hoßfeld, Tobias; Seufert, Michael; Sieber, Christian; Zinner, Thomas; Tran-Gia, Phuoc. In PIK - Praxis der Informationsverarbeitung und Kommunikation, 37, pp. 275–285. 2014.
- [ Abstract ]
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HTTP Adaptive Streaming (HAS) is the de-facto standard for over-the-top (OTT) video streaming services. It allows to react to fluctuating network conditions on short time scales by adapting the video bit rate in order to avoid stalling of the video playback. With HAS the video content is split into small segments of a few seconds playtime each, which are available in different bit rates, i.e., quality level representations. Depending on the current conditions, the adaptation algorithm on the client side chooses the appropriate quality level and downloads the respective segment. This allows to avoid stalling, which is seen as the worst possible disturbance of HTTP video streaming, to the most possible extend. Nevertheless, the user perceived Quality of Experience (QoE) may be affected, namely by playing back lower qualities and by switching between different qualities. Therefore, adaptation algorithms are desired which maximize the user’sQoEfor the currently available network resources. Many downloading strategies have been proposed in literature, but a solid user-centric comparison of these mechanisms among each other and with the global optimum is missing. The major contributions of this work are as follows. A proper analysis of the influence of quality switches and played out representations on QoE is conducted by means of subjective user studies. The results suggest that, in order to optimize QoE, first, the quality level of the video stream has to be maximized and second, the number of quality switches should be minimized. Based on our findings, a QoEoptimization problem is formulated and the performance of our proposed algorithm is compared to other algorithms and to the QoE-optimal adaptation.

@article{info3-article-2014-127, abstract = {HTTP Adaptive Streaming (HAS) is the de-facto standard for over-the-top (OTT) video streaming services. It allows to react to fluctuating network conditions on short time scales by adapting the video bit rate in order to avoid stalling of the video playback. With HAS the video content is split into small segments of a few seconds playtime each, which are available in different bit rates, i.e., quality level representations. Depending on the current conditions, the adaptation algorithm on the client side chooses the appropriate quality level and downloads the respective segment. This allows to avoid stalling, which is seen as the worst possible disturbance of HTTP video streaming, to the most possible extend. Nevertheless, the user perceived Quality of Experience (QoE) may be affected, namely by playing back lower qualities and by switching between different qualities. Therefore, adaptation algorithms are desired which maximize the user’sQoEfor the currently available network resources. Many downloading strategies have been proposed in literature, but a solid user-centric comparison of these mechanisms among each other and with the global optimum is missing. The major contributions of this work are as follows. A proper analysis of the influence of quality switches and played out representations on QoE is conducted by means of subjective user studies. The results suggest that, in order to optimize QoE, first, the quality level of the video stream has to be maximized and second, the number of quality switches should be minimized. Based on our findings, a QoEoptimization problem is formulated and the performance of our proposed algorithm is compared to other algorithms and to the QoE-optimal adaptation.}, author = {Hoßfeld, Tobias and Seufert, Michael and Sieber, Christian and Zinner, Thomas and Tran-Gia, Phuoc}, journal = {PIK - Praxis der Informationsverarbeitung und Kommunikation}, keywords = {sys:hidden:article}, month = 10, pages = {275-285}, title = {Close to Optimum? User-centric Evaluation of Adaptation Logics for HTTP Adaptive Streaming}, volume = 37, year = 2014 }

%0 Journal Article %1 info3-article-2014-127 %A Hoßfeld, Tobias %A Seufert, Michael %A Sieber, Christian %A Zinner, Thomas %A Tran-Gia, Phuoc %D 2014 %J PIK - Praxis der Informationsverarbeitung und Kommunikation %P 275-285 %T Close to Optimum? User-centric Evaluation of Adaptation Logics for HTTP Adaptive Streaming %V 37 %X HTTP Adaptive Streaming (HAS) is the de-facto standard for over-the-top (OTT) video streaming services. It allows to react to fluctuating network conditions on short time scales by adapting the video bit rate in order to avoid stalling of the video playback. With HAS the video content is split into small segments of a few seconds playtime each, which are available in different bit rates, i.e., quality level representations. Depending on the current conditions, the adaptation algorithm on the client side chooses the appropriate quality level and downloads the respective segment. This allows to avoid stalling, which is seen as the worst possible disturbance of HTTP video streaming, to the most possible extend. Nevertheless, the user perceived Quality of Experience (QoE) may be affected, namely by playing back lower qualities and by switching between different qualities. Therefore, adaptation algorithms are desired which maximize the user’sQoEfor the currently available network resources. Many downloading strategies have been proposed in literature, but a solid user-centric comparison of these mechanisms among each other and with the global optimum is missing. The major contributions of this work are as follows. A proper analysis of the influence of quality switches and played out representations on QoE is conducted by means of subjective user studies. The results suggest that, in order to optimize QoE, first, the quality level of the video stream has to be maximized and second, the number of quality switches should be minimized. Based on our findings, a QoEoptimization problem is formulated and the performance of our proposed algorithm is compared to other algorithms and to the QoE-optimal adaptation.
YOUQMON: A System for On-line Monitoring of YouTube QoE in Operational 3G Networks. Casas, Pedro; Seufert, Michael; Schatz, Raimund. In ACM SIGMETRICS Performance Evaluation Review, 41, pp. 44–46. 2013.
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YouTube is changing the way operators manage network performance monitoring. In this paper we introduce YOUQMON, a novel on-line monitoring system for assessing the Quality of Experience (QoE) undergone by HSPA/3G customers watching YouTube videos, using network-layer measurements only. YOUQMON combines passive traffic analysis techniques to detect stalling events in YouTube video streams, with a QoE model to map stallings into a Mean Opinion Score reflecting the end-user experience. We evaluate the stalling detection performance of YOUQMON with hundreds of YouTube video streams, and present results showing the feasibility of performing real-time YouTube QoE monitoring in an operational mobile broadband network.

@article{info3-article-2013-114, abstract = {YouTube is changing the way operators manage network performance monitoring. In this paper we introduce YOUQMON, a novel on-line monitoring system for assessing the Quality of Experience (QoE) undergone by HSPA/3G customers watching YouTube videos, using network-layer measurements only. YOUQMON combines passive traffic analysis techniques to detect stalling events in YouTube video streams, with a QoE model to map stallings into a Mean Opinion Score reflecting the end-user experience. We evaluate the stalling detection performance of YOUQMON with hundreds of YouTube video streams, and present results showing the feasibility of performing real-time YouTube QoE monitoring in an operational mobile broadband network.}, author = {Casas, Pedro and Seufert, Michael and Schatz, Raimund}, journal = {ACM SIGMETRICS Performance Evaluation Review}, keywords = {sys:hidden:article}, month = {09}, pages = {44-46}, title = {YOUQMON: A System for On-line Monitoring of YouTube QoE in Operational 3G Networks}, volume = 41, year = 2013 }

%0 Journal Article %1 info3-article-2013-114 %A Casas, Pedro %A Seufert, Michael %A Schatz, Raimund %D 2013 %J ACM SIGMETRICS Performance Evaluation Review %P 44-46 %T YOUQMON: A System for On-line Monitoring of YouTube QoE in Operational 3G Networks %V 41 %X YouTube is changing the way operators manage network performance monitoring. In this paper we introduce YOUQMON, a novel on-line monitoring system for assessing the Quality of Experience (QoE) undergone by HSPA/3G customers watching YouTube videos, using network-layer measurements only. YOUQMON combines passive traffic analysis techniques to detect stalling events in YouTube video streams, with a QoE model to map stallings into a Mean Opinion Score reflecting the end-user experience. We evaluate the stalling detection performance of YOUQMON with hundreds of YouTube video streams, and present results showing the feasibility of performing real-time YouTube QoE monitoring in an operational mobile broadband network.
Using Buffered Playtime for QoE-Oriented Resource Management of YouTube Video Streaming. Wamser, Florian; Hock, David; Seufert, Michael; Staehle, Barbara; Pries, Rastin; Tran-Gia, Phuoc. In Transactions on Emerging Telecommunications Technologies, 24, pp. 288–302. 2013.
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YouTube is the most important online platform for streaming video clips. The popularity and the continuously increasing number of users pose new challenges for Internet Service Providers (ISPs). In particular, in access networks where the transmission resources are limited and the providers are interested in reducing their operational expenditure, it is worth to efficiently optimize the network for popular services such as YouTube. In this paper, we propose different resource management mechanisms to improve the Quality of Experience (QoE) of YouTube users. In particular, we investigate the benefit of cross-layer resource management actions at the client and in the access network for YouTube video streaming. The proposed algorithms are evaluated in a wireless mesh testbed. The results show how to improve the YouTube QoE for the users with the help of client-based or network-based control actions.

@article{info3-article-2013-109, abstract = {YouTube is the most important online platform for streaming video clips. The popularity and the continuously increasing number of users pose new challenges for Internet Service Providers (ISPs). In particular, in access networks where the transmission resources are limited and the providers are interested in reducing their operational expenditure, it is worth to efficiently optimize the network for popular services such as YouTube. In this paper, we propose different resource management mechanisms to improve the Quality of Experience (QoE) of YouTube users. In particular, we investigate the benefit of cross-layer resource management actions at the client and in the access network for YouTube video streaming. The proposed algorithms are evaluated in a wireless mesh testbed. The results show how to improve the YouTube QoE for the users with the help of client-based or network-based control actions.}, author = {Wamser, Florian and Hock, David and Seufert, Michael and Staehle, Barbara and Pries, Rastin and Tran-Gia, Phuoc}, journal = {Transactions on Emerging Telecommunications Technologies}, keywords = {sys:hidden:article}, month = {04}, pages = {288–302}, title = {Using Buffered Playtime for QoE-Oriented Resource Management of YouTube Video Streaming}, volume = 24, year = 2013 }

%0 Journal Article %1 info3-article-2013-109 %A Wamser, Florian %A Hock, David %A Seufert, Michael %A Staehle, Barbara %A Pries, Rastin %A Tran-Gia, Phuoc %D 2013 %J Transactions on Emerging Telecommunications Technologies %P 288–302 %T Using Buffered Playtime for QoE-Oriented Resource Management of YouTube Video Streaming %V 24 %X YouTube is the most important online platform for streaming video clips. The popularity and the continuously increasing number of users pose new challenges for Internet Service Providers (ISPs). In particular, in access networks where the transmission resources are limited and the providers are interested in reducing their operational expenditure, it is worth to efficiently optimize the network for popular services such as YouTube. In this paper, we propose different resource management mechanisms to improve the Quality of Experience (QoE) of YouTube users. In particular, we investigate the benefit of cross-layer resource management actions at the client and in the access network for YouTube video streaming. The proposed algorithms are evaluated in a wireless mesh testbed. The results show how to improve the YouTube QoE for the users with the help of client-based or network-based control actions.
OC²E²AN: Optimized Control Center for Experience Enhancements in Access Networks. Hock, David; Wamser, Florian; Seufert, Michael; Pries, Rastin; Tran-Gia, Phuoc. In PIK - Praxis der Informationsverarbeitung und Kommunikation, 36, p. 40. 2013.
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@article{info3-article-2013-112, author = {Hock, David and Wamser, Florian and Seufert, Michael and Pries, Rastin and Tran-Gia, Phuoc}, journal = {PIK - Praxis der Informationsverarbeitung und Kommunikation}, keywords = {sys:hidden:article}, month = {02}, pages = 40, title = {OC²E²AN: Optimized Control Center for Experience Enhancements in Access Networks}, volume = 36, year = 2013 }

%0 Journal Article %1 info3-article-2013-112 %A Hock, David %A Wamser, Florian %A Seufert, Michael %A Pries, Rastin %A Tran-Gia, Phuoc %D 2013 %J PIK - Praxis der Informationsverarbeitung und Kommunikation %P 40 %T OC²E²AN: Optimized Control Center for Experience Enhancements in Access Networks %V 36

Conference Articles

Fitting the Puzzle: Towards Source Traffic Modeling For Mobile Instant Messaging. Poignée, Fabian; Seufert, Anika; Loh, Frank; Seufert, Michael; Hoßfeld, Tobias. In 2024 15th International Conference on Network of the Future (NoF). Castelldefels (Barcelona), Spain, 2024.
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@inproceedings{info3-inproceedings-2024-11, address = {Castelldefels (Barcelona), Spain}, author = {Poignée, Fabian and Seufert, Anika and Loh, Frank and Seufert, Michael and Hoßfeld, Tobias}, booktitle = {2024 15th International Conference on Network of the Future (NoF)}, keywords = {ucn}, month = 10, title = {Fitting the Puzzle: Towards Source Traffic Modeling For Mobile Instant Messaging}, year = 2024 }

%0 Conference Paper %1 info3-inproceedings-2024-11 %A Poignée, Fabian %A Seufert, Anika %A Loh, Frank %A Seufert, Michael %A Hoßfeld, Tobias %B 2024 15th International Conference on Network of the Future (NoF) %C Castelldefels (Barcelona), Spain %D 2024 %T Fitting the Puzzle: Towards Source Traffic Modeling For Mobile Instant Messaging
Agree to Disagree: Exploring Consensus of XAI Methods for ML-based NIDS. Dietz, Katharina; Hajizadeh, Mehrdad; Schleicher, Johannes; Wehner, Nikolas; Geißler, Stefan; Casas, Pedro; Seufert, Michael; Hoßfeld, Tobias. In 1st Workshop on Network Security Operations (NeSecOr) as part of CNSM’24. Prague, Czech Republic, 2024.
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@inproceedings{info3-inproceedings-2024-8, address = {Prague, Czech Republic}, author = {Dietz, Katharina and Hajizadeh, Mehrdad and Schleicher, Johannes and Wehner, Nikolas and Geißler, Stefan and Casas, Pedro and Seufert, Michael and Hoßfeld, Tobias}, booktitle = {1st Workshop on Network Security Operations (NeSecOr) as part of CNSM'24}, keywords = {vipnano}, month = 10, title = {Agree to Disagree: Exploring Consensus of XAI Methods for ML-based NIDS}, year = 2024 }

%0 Conference Paper %1 info3-inproceedings-2024-8 %A Dietz, Katharina %A Hajizadeh, Mehrdad %A Schleicher, Johannes %A Wehner, Nikolas %A Geißler, Stefan %A Casas, Pedro %A Seufert, Michael %A Hoßfeld, Tobias %B 1st Workshop on Network Security Operations (NeSecOr) as part of CNSM'24 %C Prague, Czech Republic %D 2024 %T Agree to Disagree: Exploring Consensus of XAI Methods for ML-based NIDS
Certainly Uncertain: Demystifying ML Uncertainty for Active Learning in Network Monitoring Tasks. Dietz, Katharina; Hajizadeh, Mehrdad; Wehner, Nikolas; Geißler, Stefan; Casas, Pedro; Seufert, Michael; Hoßfeld, Tobias. In 20th International Conference on Network and Service Management (CNSM). Prague, Czech Republic, 2024.
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@inproceedings{info3-inproceedings-2024-7, address = {Prague, Czech Republic}, author = {Dietz, Katharina and Hajizadeh, Mehrdad and Wehner, Nikolas and Geißler, Stefan and Casas, Pedro and Seufert, Michael and Hoßfeld, Tobias}, booktitle = {20th International Conference on Network and Service Management (CNSM)}, keywords = {vipnano}, month = 10, title = {Certainly Uncertain: Demystifying ML Uncertainty for Active Learning in Network Monitoring Tasks}, year = 2024 }

%0 Conference Paper %1 info3-inproceedings-2024-7 %A Dietz, Katharina %A Hajizadeh, Mehrdad %A Wehner, Nikolas %A Geißler, Stefan %A Casas, Pedro %A Seufert, Michael %A Hoßfeld, Tobias %B 20th International Conference on Network and Service Management (CNSM) %C Prague, Czech Republic %D 2024 %T Certainly Uncertain: Demystifying ML Uncertainty for Active Learning in Network Monitoring Tasks
(Not) The Sum of Its Parts: Relating Individual Video and Browsing Stimuli to Web Session QoE. Schleicher, Johannes; Wehner, Nikolas; Hoßfeld, Tobias; Seufert, Michael. In 16th International Conference on Quality of Multimedia Experience (QoMEX). Karlshamn, Sweden, 2024.
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@inproceedings{info3-inproceedings-2024-3, address = {Karlshamn, Sweden}, author = {Schleicher, Johannes and Wehner, Nikolas and Hoßfeld, Tobias and Seufert, Michael}, booktitle = {16th International Conference on Quality of Multimedia Experience (QoMEX)}, keywords = {sys:hidden:inproceedings}, month = {06}, title = {(Not) The Sum of Its Parts: Relating Individual Video and Browsing Stimuli to Web Session QoE}, year = 2024 }

%0 Conference Paper %1 info3-inproceedings-2024-3 %A Schleicher, Johannes %A Wehner, Nikolas %A Hoßfeld, Tobias %A Seufert, Michael %B 16th International Conference on Quality of Multimedia Experience (QoMEX) %C Karlshamn, Sweden %D 2024 %T (Not) The Sum of Its Parts: Relating Individual Video and Browsing Stimuli to Web Session QoE
Sitting, Chatting, Waiting: Influence of Loading Times on Mobile Instant Messaging QoE. Seufert, Anika; Baur, Carina; Poignée, Fabian; Seufert, Michael; Hoßfeld, Tobias. In 16th International Conference on Quality of Multimedia Experience (QoMEX). Karlshamn, Sweden, 2024.
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This paper explores the relationship between loading times and Quality of Experience (QoE) in Mobile Instant Messaging (MIM) applications. Using a web application that mimics MIM interfaces, we conducted a QoE study in which participants engaged with a virtual chat partner. We controlled image loading times during chatting and evaluated their impact on QoE, annoyance, and acceptance ratings. Although the results show no difference in the QoE ratings, they clearly show that longer delays lead to greater annoyance and lower user acceptance. These findings underscore the importance for MIM app providers to minimize loading times in order to increase user satisfaction and retention.

@inproceedings{info3-inproceedings-2024-5, abstract = {This paper explores the relationship between loading times and Quality of Experience (QoE) in Mobile Instant Messaging (MIM) applications. Using a web application that mimics MIM interfaces, we conducted a QoE study in which participants engaged with a virtual chat partner. We controlled image loading times during chatting and evaluated their impact on QoE, annoyance, and acceptance ratings. Although the results show no difference in the QoE ratings, they clearly show that longer delays lead to greater annoyance and lower user acceptance. These findings underscore the importance for MIM app providers to minimize loading times in order to increase user satisfaction and retention.}, address = {Karlshamn, Sweden}, author = {Seufert, Anika and Baur, Carina and Poignée, Fabian and Seufert, Michael and Hoßfeld, Tobias}, booktitle = {16th International Conference on Quality of Multimedia Experience (QoMEX)}, keywords = {can}, month = {06}, title = {Sitting, Chatting, Waiting: Influence of Loading Times on Mobile Instant Messaging QoE}, year = 2024 }

%0 Conference Paper %1 info3-inproceedings-2024-5 %A Seufert, Anika %A Baur, Carina %A Poignée, Fabian %A Seufert, Michael %A Hoßfeld, Tobias %B 16th International Conference on Quality of Multimedia Experience (QoMEX) %C Karlshamn, Sweden %D 2024 %T Sitting, Chatting, Waiting: Influence of Loading Times on Mobile Instant Messaging QoE %X This paper explores the relationship between loading times and Quality of Experience (QoE) in Mobile Instant Messaging (MIM) applications. Using a web application that mimics MIM interfaces, we conducted a QoE study in which participants engaged with a virtual chat partner. We controlled image loading times during chatting and evaluated their impact on QoE, annoyance, and acceptance ratings. Although the results show no difference in the QoE ratings, they clearly show that longer delays lead to greater annoyance and lower user acceptance. These findings underscore the importance for MIM app providers to minimize loading times in order to increase user satisfaction and retention.
QoEXplainer: Mediating Explainable Quality of Experience Models with Large Language Models. Wehner, Nikolas; Feldhus, Nils; Seufert, Michael; Möller, Sebastian; Hoßfeld, Tobias. In 16th International Conference on Quality of Multimedia Experience (QoMEX). Karlshamn, Sweden, 2024.
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@inproceedings{info3-inproceedings-2024-4, address = {Karlshamn, Sweden}, author = {Wehner, Nikolas and Feldhus, Nils and Seufert, Michael and Möller, Sebastian and Hoßfeld, Tobias}, booktitle = {16th International Conference on Quality of Multimedia Experience (QoMEX)}, keywords = {sys:hidden:inproceedings}, month = {06}, title = {QoEXplainer: Mediating Explainable Quality of Experience Models with Large Language Models}, year = 2024 }

%0 Conference Paper %1 info3-inproceedings-2024-4 %A Wehner, Nikolas %A Feldhus, Nils %A Seufert, Michael %A Möller, Sebastian %A Hoßfeld, Tobias %B 16th International Conference on Quality of Multimedia Experience (QoMEX) %C Karlshamn, Sweden %D 2024 %T QoEXplainer: Mediating Explainable Quality of Experience Models with Large Language Models
HALIDS: a hardware-assisted machine learning IDS for in-network monitoring. Brandino, Belén; Grampin, Eduardo; Dietz, Katharina; Wehner, Nikolas; Seufert, Michael; Hoßfeld, Tobias; Casas, Pedro. In 2024 8th Network Traffic Measurement and Analysis Conference (TMA), Dresden, Germany. 2024.
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@inproceedings{info3-poster-2024-1, author = {Brandino, Belén and Grampin, Eduardo and Dietz, Katharina and Wehner, Nikolas and Seufert, Michael and Hoßfeld, Tobias and Casas, Pedro}, booktitle = {2024 8th Network Traffic Measurement and Analysis Conference (TMA), Dresden, Germany}, keywords = {sys:hidden:inproceedings}, month = {05}, title = {HALIDS: a hardware-assisted machine learning IDS for in-network monitoring}, year = 2024 }

%0 Conference Paper %1 info3-poster-2024-1 %A Brandino, Belén %A Grampin, Eduardo %A Dietz, Katharina %A Wehner, Nikolas %A Seufert, Michael %A Hoßfeld, Tobias %A Casas, Pedro %B 2024 8th Network Traffic Measurement and Analysis Conference (TMA), Dresden, Germany %D 2024 %T HALIDS: a hardware-assisted machine learning IDS for in-network monitoring
Demystifying User-based Active Learning for Network Monitoring Tasks. Dietz, Katharina; Wehner, Nikolas; Casas, Pedro; Hoßfeld, Tobias; Seufert, Michael. In 2nd Workshop on Machine Learning & Networking (MaLeNe) as part of NetSys’23. Potsdam, Germany, 2023.
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@inproceedings{info3-inproceedings-2023-9, address = {Potsdam, Germany}, author = {Dietz, Katharina and Wehner, Nikolas and Casas, Pedro and Hoßfeld, Tobias and Seufert, Michael}, booktitle = {2nd Workshop on Machine Learning & Networking (MaLeNe) as part of NetSys'23}, keywords = {ucn}, month = {09}, title = {Demystifying User-based Active Learning for Network Monitoring Tasks}, year = 2023 }

%0 Conference Paper %1 info3-inproceedings-2023-9 %A Dietz, Katharina %A Wehner, Nikolas %A Casas, Pedro %A Hoßfeld, Tobias %A Seufert, Michael %B 2nd Workshop on Machine Learning & Networking (MaLeNe) as part of NetSys'23 %C Potsdam, Germany %D 2023 %T Demystifying User-based Active Learning for Network Monitoring Tasks
Explainable Data-Driven QoE Modelling using XAI. Wehner, Nikolas; Seufert, Anika; Hoßfeld, Tobias; Seufert, Michael. In 15th International Conference on Quality of Multimedia Experience (QoMEX). Ghent, Belgium, 2023.
- [ Abstract ]
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Data-driven QoE modelling using Machine Learning (ML) allows to reduce the modelling bias and to continuously integrate new QoE results into the QoE model, which can improve its generalizability. The downside is that the majority of ML models are black-box models, which prevent to obtain insights about QoE influence factors and their fundamental relationships that are highly relevant for researchers and providers of services and networks. However, recent advances in the field of eXplainable Artificial Intelligence (XAI) resolve these issues. Thus, XAI allows to benefit from data-driven QoE modelling to obtain generalizable QoE models, and at the same time to understand what QoE factors are relevant and how they affect the QoE score. In this work, we showcase the feasibility of explainable data-driven QoE modelling for video streaming, since video streaming QoE has been well researched, and thus, allows us to validate our results. Finally, we discuss opportunities and challenges of deploying XAI for QoE modelling.

@inproceedings{info3-inproceedings-2023-4, abstract = {Data-driven QoE modelling using Machine Learning (ML) allows to reduce the modelling bias and to continuously integrate new QoE results into the QoE model, which can improve its generalizability. The downside is that the majority of ML models are black-box models, which prevent to obtain insights about QoE influence factors and their fundamental relationships that are highly relevant for researchers and providers of services and networks. However, recent advances in the field of eXplainable Artificial Intelligence (XAI) resolve these issues. Thus, XAI allows to benefit from data-driven QoE modelling to obtain generalizable QoE models, and at the same time to understand what QoE factors are relevant and how they affect the QoE score. In this work, we showcase the feasibility of explainable data-driven QoE modelling for video streaming, since video streaming QoE has been well researched, and thus, allows us to validate our results. Finally, we discuss opportunities and challenges of deploying XAI for QoE modelling.}, address = {Ghent, Belgium}, author = {Wehner, Nikolas and Seufert, Anika and Hoßfeld, Tobias and Seufert, Michael}, booktitle = {15th International Conference on Quality of Multimedia Experience (QoMEX)}, keywords = {ucn}, month = {06}, title = {Explainable Data-Driven QoE Modelling using XAI}, year = 2023 }

%0 Conference Paper %1 info3-inproceedings-2023-4 %A Wehner, Nikolas %A Seufert, Anika %A Hoßfeld, Tobias %A Seufert, Michael %B 15th International Conference on Quality of Multimedia Experience (QoMEX) %C Ghent, Belgium %D 2023 %T Explainable Data-Driven QoE Modelling using XAI %X Data-driven QoE modelling using Machine Learning (ML) allows to reduce the modelling bias and to continuously integrate new QoE results into the QoE model, which can improve its generalizability. The downside is that the majority of ML models are black-box models, which prevent to obtain insights about QoE influence factors and their fundamental relationships that are highly relevant for researchers and providers of services and networks. However, recent advances in the field of eXplainable Artificial Intelligence (XAI) resolve these issues. Thus, XAI allows to benefit from data-driven QoE modelling to obtain generalizable QoE models, and at the same time to understand what QoE factors are relevant and how they affect the QoE score. In this work, we showcase the feasibility of explainable data-driven QoE modelling for video streaming, since video streaming QoE has been well researched, and thus, allows us to validate our results. Finally, we discuss opportunities and challenges of deploying XAI for QoE modelling.
Moving Down the Stack: Performance Evaluation of Packet Processing Technologies for Stateful Firewalls. Dietz, Katharina; Gray, Nicholas; Wolz, Manuel; Lorenz, Claas; Hoßfeld, Tobias; Seufert, Michael. In 34th IEEE/IFIP Network Operations and Management Symposium (NOMS). Miami, Florida, 2023.
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@inproceedings{info3-inproceedings-2023-2, address = {Miami, Florida}, author = {Dietz, Katharina and Gray, Nicholas and Wolz, Manuel and Lorenz, Claas and Hoßfeld, Tobias and Seufert, Michael}, booktitle = {34th IEEE/IFIP Network Operations and Management Symposium (NOMS)}, keywords = {ucn}, month = {05}, title = {Moving Down the Stack: Performance Evaluation of Packet Processing Technologies for Stateful Firewalls}, year = 2023 }

%0 Conference Paper %1 info3-inproceedings-2023-2 %A Dietz, Katharina %A Gray, Nicholas %A Wolz, Manuel %A Lorenz, Claas %A Hoßfeld, Tobias %A Seufert, Michael %B 34th IEEE/IFIP Network Operations and Management Symposium (NOMS) %C Miami, Florida %D 2023 %T Moving Down the Stack: Performance Evaluation of Packet Processing Technologies for Stateful Firewalls
Fingerprinting Webpages and Smartphone Apps from Encrypted Network Traffic with WebScanner. Casas, Pedro; Wehner, Nikolas; Wassermann, Sarah; Seufert, Michael. In Global Internet (GI) Symposium. Paris, France, 2022.
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The wide adoption of end-to-end encryption drastically limits the visibility Internet Service Providers (ISPs) have on the services consumed by their customers. This is particularly challenging for monitoring and analysis of web and apps traffic, which is highly complex and heterogeneous. Loading a web page or app today requires tens of flows to download the various resources located in distributed cloud servers from different content providers. We introduce WebScanner, a webpage and app fingerprinting approach capable to identify all the traffic flows corresponding to individual webpage and app loading sessions within concurrent web pages traffic, enabling highly detailed, per webpage analysis in practical deployments. Different from the state of the art in web and app traffic fingerprinting, and as our most relevant contribution, WebScanner automatically performs the parsing of all the traffic generated by a web visit and its isolation from concurrent traffic, instead of assuming that an external oracle system does so. WebScanner also implements a deep fingerprinting approach to detect user action-dependent traffic from apps, relying on simple machine learning models and strong input features as fingerprints. Extensive evaluation across a large measurement dataset of popular webpages and mobile apps confirms the outstanding performance of WebScanner, identifying the top-500 Alexa websites with precision and recall (P/R) above 95%, isolating their full contents with P/R above 80% for up to 15 concurrent webpages, and detecting specific action-dependent apps traffic with average P/R above 92%.

@inproceedings{info3-inproceedings-2022-18, abstract = {The wide adoption of end-to-end encryption drastically limits the visibility Internet Service Providers (ISPs) have on the services consumed by their customers. This is particularly challenging for monitoring and analysis of web and apps traffic, which is highly complex and heterogeneous. Loading a web page or app today requires tens of flows to download the various resources located in distributed cloud servers from different content providers. We introduce WebScanner, a webpage and app fingerprinting approach capable to identify all the traffic flows corresponding to individual webpage and app loading sessions within concurrent web pages traffic, enabling highly detailed, per webpage analysis in practical deployments. Different from the state of the art in web and app traffic fingerprinting, and as our most relevant contribution, WebScanner automatically performs the parsing of all the traffic generated by a web visit and its isolation from concurrent traffic, instead of assuming that an external oracle system does so. WebScanner also implements a deep fingerprinting approach to detect user action-dependent traffic from apps, relying on simple machine learning models and strong input features as fingerprints. Extensive evaluation across a large measurement dataset of popular webpages and mobile apps confirms the outstanding performance of WebScanner, identifying the top-500 Alexa websites with precision and recall (P/R) above 95%, isolating their full contents with P/R above 80% for up to 15 concurrent webpages, and detecting specific action-dependent apps traffic with average P/R above 92%.}, address = {Paris, France}, author = {Casas, Pedro and Wehner, Nikolas and Wassermann, Sarah and Seufert, Michael}, booktitle = {Global Internet (GI) Symposium}, keywords = {ucn}, month = 11, title = {Fingerprinting Webpages and Smartphone Apps from Encrypted Network Traffic with WebScanner}, year = 2022 }

%0 Conference Paper %1 info3-inproceedings-2022-18 %A Casas, Pedro %A Wehner, Nikolas %A Wassermann, Sarah %A Seufert, Michael %B Global Internet (GI) Symposium %C Paris, France %D 2022 %T Fingerprinting Webpages and Smartphone Apps from Encrypted Network Traffic with WebScanner %X The wide adoption of end-to-end encryption drastically limits the visibility Internet Service Providers (ISPs) have on the services consumed by their customers. This is particularly challenging for monitoring and analysis of web and apps traffic, which is highly complex and heterogeneous. Loading a web page or app today requires tens of flows to download the various resources located in distributed cloud servers from different content providers. We introduce WebScanner, a webpage and app fingerprinting approach capable to identify all the traffic flows corresponding to individual webpage and app loading sessions within concurrent web pages traffic, enabling highly detailed, per webpage analysis in practical deployments. Different from the state of the art in web and app traffic fingerprinting, and as our most relevant contribution, WebScanner automatically performs the parsing of all the traffic generated by a web visit and its isolation from concurrent traffic, instead of assuming that an external oracle system does so. WebScanner also implements a deep fingerprinting approach to detect user action-dependent traffic from apps, relying on simple machine learning models and strong input features as fingerprints. Extensive evaluation across a large measurement dataset of popular webpages and mobile apps confirms the outstanding performance of WebScanner, identifying the top-500 Alexa websites with precision and recall (P/R) above 95%, isolating their full contents with P/R above 80% for up to 15 concurrent webpages, and detecting specific action-dependent apps traffic with average P/R above 92%.
Comparing Traditional and GAN-based Approaches for the Synthesis of Wide Area Network Topologies. Dietz, Katharina; Seufert, Michael; Hoßfeld, Tobias. In 18th International Conference on Network and Service Management (CNSM). Thessaloniki, Greece, 2022.
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@inproceedings{info3-inproceedings-2022-16, address = {Thessaloniki, Greece}, author = {Dietz, Katharina and Seufert, Michael and Hoßfeld, Tobias}, booktitle = {18th International Conference on Network and Service Management (CNSM)}, keywords = {ucn}, month = 10, title = {Comparing Traditional and GAN-based Approaches for the Synthesis of Wide Area Network Topologies}, year = 2022 }

%0 Conference Paper %1 info3-inproceedings-2022-16 %A Dietz, Katharina %A Seufert, Michael %A Hoßfeld, Tobias %B 18th International Conference on Network and Service Management (CNSM) %C Thessaloniki, Greece %D 2022 %T Comparing Traditional and GAN-based Approaches for the Synthesis of Wide Area Network Topologies
Waiting along the Path: How Browsing Delays Impact the QoE of Music Streaming Applications. Seufert, Anika; Schweifler, Ralf; Poignée, Fabian; Seufert, Michael; Hoßfeld, Tobias. In 14th International Conference on Quality of Multimedia Experience (QoMEX). 2022.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
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Streaming has become the dominant source of media consumption, which not only applies to the widely researched field of video streaming, but also to music streaming. Here, previous studies so far have only researched the impact of streaming aspects, such as stalling events or initial loading times, on the QoE of music streaming. However, when using a music streaming application, users are already facing waiting times along the click path before they can start the actual streaming. These waiting times are caused by browsing delays, e.g., during searching for songs or scrolling through playlists, and can potentially deteriorate the QoE of the music streaming application. In this work, we conduct an online QoE study to quantify the impact of these browsing delays with the support of an emulated mobile music streaming web app. We found that browsing delays have no impact on the music streaming QoE, which shows that users are able to clearly distinguish between the two main functionalities of such apps, namely, browsing and streaming. However, browsing delays significantly reduce the QoE of the entire music streaming application, to a similar extent as if QoE degradations happen during the actual streaming. This shows that both browsing and streaming are equally important and have to be considered when designing music streaming applications.

@inproceedings{info3-inproceedings-2022-13, abstract = {Streaming has become the dominant source of media consumption, which not only applies to the widely researched field of video streaming, but also to music streaming. Here, previous studies so far have only researched the impact of streaming aspects, such as stalling events or initial loading times, on the QoE of music streaming. However, when using a music streaming application, users are already facing waiting times along the click path before they can start the actual streaming. These waiting times are caused by browsing delays, e.g., during searching for songs or scrolling through playlists, and can potentially deteriorate the QoE of the music streaming application. In this work, we conduct an online QoE study to quantify the impact of these browsing delays with the support of an emulated mobile music streaming web app. We found that browsing delays have no impact on the music streaming QoE, which shows that users are able to clearly distinguish between the two main functionalities of such apps, namely, browsing and streaming. However, browsing delays significantly reduce the QoE of the entire music streaming application, to a similar extent as if QoE degradations happen during the actual streaming. This shows that both browsing and streaming are equally important and have to be considered when designing music streaming applications.}, author = {Seufert, Anika and Schweifler, Ralf and Poignée, Fabian and Seufert, Michael and Hoßfeld, Tobias}, booktitle = {14th International Conference on Quality of Multimedia Experience (QoMEX)}, keywords = {sys:hidden:inproceedings}, month = {09}, title = {Waiting along the Path: How Browsing Delays Impact the QoE of Music Streaming Applications}, year = 2022 }

%0 Conference Paper %1 info3-inproceedings-2022-13 %A Seufert, Anika %A Schweifler, Ralf %A Poignée, Fabian %A Seufert, Michael %A Hoßfeld, Tobias %B 14th International Conference on Quality of Multimedia Experience (QoMEX) %D 2022 %T Waiting along the Path: How Browsing Delays Impact the QoE of Music Streaming Applications %X Streaming has become the dominant source of media consumption, which not only applies to the widely researched field of video streaming, but also to music streaming. Here, previous studies so far have only researched the impact of streaming aspects, such as stalling events or initial loading times, on the QoE of music streaming. However, when using a music streaming application, users are already facing waiting times along the click path before they can start the actual streaming. These waiting times are caused by browsing delays, e.g., during searching for songs or scrolling through playlists, and can potentially deteriorate the QoE of the music streaming application. In this work, we conduct an online QoE study to quantify the impact of these browsing delays with the support of an emulated mobile music streaming web app. We found that browsing delays have no impact on the music streaming QoE, which shows that users are able to clearly distinguish between the two main functionalities of such apps, namely, browsing and streaming. However, browsing delays significantly reduce the QoE of the entire music streaming application, to a similar extent as if QoE degradations happen during the actual streaming. This shows that both browsing and streaming are equally important and have to be considered when designing music streaming applications.
A Vital Improvement? Relating Google’s Core Web Vitals to Actual Web QoE. Wehner, Nikolas; Amir, Monisha; Seufert, Michael; Schatz, Raimund; Hoßfeld, Tobias. In 14th International Conference on Quality of Multimedia Experience (QoMEX), Best Paper Award. Lippstadt, Germany, 2022.
- [ Abstract ]
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Providing sophisticated Web Quality of Experience (QoE) has become paramount for web service providers and network operators alike. Due to advances in Web technologies (HTML5, responsive design, etc.), traditional Web QoE models focusing mainly on loading times have to be refined and improved. In this work, we relate Google's Core Web Vitals, a set of metrics for improving user experience, to the loading time aspects of Web QoE. To this end, we first perform objective measurements in the Web using Google's Lighthouse. To close the gap between metrics and experience, we complement these objective measurements with subjective assessment by performing multiple crowdsourcing QoE studies. In these studies, we use CWeQS, a customized framework to emulate the entire web page loading process, and ask users for their experience while controlling the Core Web Vitals. Our results suggest that the Core Web Vitals have less predictive value for Web QoE than expected and that page loading times remain the main influence factor in this context.

@inproceedings{info3-inproceedings-2022-12, abstract = {Providing sophisticated Web Quality of Experience (QoE) has become paramount for web service providers and network operators alike. Due to advances in Web technologies (HTML5, responsive design, etc.), traditional Web QoE models focusing mainly on loading times have to be refined and improved. In this work, we relate Google's Core Web Vitals, a set of metrics for improving user experience, to the loading time aspects of Web QoE. To this end, we first perform objective measurements in the Web using Google's Lighthouse. To close the gap between metrics and experience, we complement these objective measurements with subjective assessment by performing multiple crowdsourcing QoE studies. In these studies, we use CWeQS, a customized framework to emulate the entire web page loading process, and ask users for their experience while controlling the Core Web Vitals. Our results suggest that the Core Web Vitals have less predictive value for Web QoE than expected and that page loading times remain the main influence factor in this context.}, address = {Lippstadt, Germany}, author = {Wehner, Nikolas and Amir, Monisha and Seufert, Michael and Schatz, Raimund and Hoßfeld, Tobias}, booktitle = {14th International Conference on Quality of Multimedia Experience (QoMEX), Best Paper Award}, keywords = {ucn}, month = {09}, title = {A Vital Improvement? Relating Google's Core Web Vitals to Actual Web QoE}, year = 2022 }

%0 Conference Paper %1 info3-inproceedings-2022-12 %A Wehner, Nikolas %A Amir, Monisha %A Seufert, Michael %A Schatz, Raimund %A Hoßfeld, Tobias %B 14th International Conference on Quality of Multimedia Experience (QoMEX), Best Paper Award %C Lippstadt, Germany %D 2022 %T A Vital Improvement? Relating Google's Core Web Vitals to Actual Web QoE %X Providing sophisticated Web Quality of Experience (QoE) has become paramount for web service providers and network operators alike. Due to advances in Web technologies (HTML5, responsive design, etc.), traditional Web QoE models focusing mainly on loading times have to be refined and improved. In this work, we relate Google's Core Web Vitals, a set of metrics for improving user experience, to the loading time aspects of Web QoE. To this end, we first perform objective measurements in the Web using Google's Lighthouse. To close the gap between metrics and experience, we complement these objective measurements with subjective assessment by performing multiple crowdsourcing QoE studies. In these studies, we use CWeQS, a customized framework to emulate the entire web page loading process, and ask users for their experience while controlling the Core Web Vitals. Our results suggest that the Core Web Vitals have less predictive value for Web QoE than expected and that page loading times remain the main influence factor in this context.
Not all Web Pages are Born the Same. Content Tailored Learning for Web QoE Inference. Casas, Pedro; Wassermann, Sarah; Wehner, Nikolas; Seufert, Michael; Hoßfeld, Tobias. In IEEE International Symposium on Measurements & Networking (M&N 2022). 2022.
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- [ BibTeX ]
- [ EndNote ]
Web Quality of Experience (QoE) monitoring is a critical task for Internet Service Providers (ISPs), especially due to the key role played by customer experience in churn management. Previously, we have tackled the problem of Web QoE inference from the ISP perspective, relying on passive measurement of encrypted network traffic and machine learning models. In this paper, we exploit the broad heterogeneity of contents embedded in web pages to improve the state of the art performance in Web QoE inference, relying on web-content learning model tailoring. By analyzing the top-500 most popular web pages of the Internet through unsupervised learning, we discover different web page content classes which realize significantly different Web QoE inference performance. We train supervised learning inference models separately for each of these classes, using the well-known Speed Index (SI) metric as proxy to Web QoE. Empirical evaluations on a large corpus of Web QoE measurements for top popular websites demonstrate that our combined content-tailored approach improves the inference performance of the SI by almost 30% with respect to previous single-model approaches, reducing the QoE inference error in terms of mean opinion scores by more than 40%.

@inproceedings{info3-inproceedings-2022-10, abstract = {Web Quality of Experience (QoE) monitoring is a critical task for Internet Service Providers (ISPs), especially due to the key role played by customer experience in churn management. Previously, we have tackled the problem of Web QoE inference from the ISP perspective, relying on passive measurement of encrypted network traffic and machine learning models. In this paper, we exploit the broad heterogeneity of contents embedded in web pages to improve the state of the art performance in Web QoE inference, relying on web-content learning model tailoring. By analyzing the top-500 most popular web pages of the Internet through unsupervised learning, we discover different web page content classes which realize significantly different Web QoE inference performance. We train supervised learning inference models separately for each of these classes, using the well-known Speed Index (SI) metric as proxy to Web QoE. Empirical evaluations on a large corpus of Web QoE measurements for top popular websites demonstrate that our combined content-tailored approach improves the inference performance of the SI by almost 30% with respect to previous single-model approaches, reducing the QoE inference error in terms of mean opinion scores by more than 40%.}, author = {Casas, Pedro and Wassermann, Sarah and Wehner, Nikolas and Seufert, Michael and Hoßfeld, Tobias}, booktitle = {IEEE International Symposium on Measurements & Networking (M&N 2022)}, keywords = {sys:hidden:inproceedings}, month = {07}, title = {Not all Web Pages are Born the Same. Content Tailored Learning for Web QoE Inference}, year = 2022 }

%0 Conference Paper %1 info3-inproceedings-2022-10 %A Casas, Pedro %A Wassermann, Sarah %A Wehner, Nikolas %A Seufert, Michael %A Hoßfeld, Tobias %B IEEE International Symposium on Measurements & Networking (M&N 2022) %D 2022 %T Not all Web Pages are Born the Same. Content Tailored Learning for Web QoE Inference %X Web Quality of Experience (QoE) monitoring is a critical task for Internet Service Providers (ISPs), especially due to the key role played by customer experience in churn management. Previously, we have tackled the problem of Web QoE inference from the ISP perspective, relying on passive measurement of encrypted network traffic and machine learning models. In this paper, we exploit the broad heterogeneity of contents embedded in web pages to improve the state of the art performance in Web QoE inference, relying on web-content learning model tailoring. By analyzing the top-500 most popular web pages of the Internet through unsupervised learning, we discover different web page content classes which realize significantly different Web QoE inference performance. We train supervised learning inference models separately for each of these classes, using the well-known Speed Index (SI) metric as proxy to Web QoE. Empirical evaluations on a large corpus of Web QoE measurements for top popular websites demonstrate that our combined content-tailored approach improves the inference performance of the SI by almost 30% with respect to previous single-model approaches, reducing the QoE inference error in terms of mean opinion scores by more than 40%.
X-Ray Goggles for the ISP: Improving in-Network Web and App QoE Monitoring with Deep Learning. Casas, Pedro; Wassermann, Sarah; Seufert, Michael; Wehner, Nikolas; Dinica, Olivia; Hoßfeld, Tobias. In Network Traffic Measurement and Analysis Conference (TMA). 2022.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
The wide adoption of end-to-end encryption is drastically limiting the visibility Internet Service Providers (ISPs) have on the performance of the services consumed by their customers. In times of strong competition, where customer experience plays a key role in churn management, ISPs require novel solutions enabling network-wide Quality of Experience (QoE) monitoring. To this end, we present DeepQoE, a deep-learning based approach to infer the QoE of web services and mobile applications from the ISP perspective, relying exclusively on the analysis of encrypted network traffic. Using raw features derived from the encrypted stream of bytes as input to deep Convolutional Neural Networks (CNNs), DeepQoE infers the Speed Index of web browsing sessions and general mobile apps with unprecedented accuracy, improving the state of the art by more than 25%, and reducing the QoE inference error in terms of mean opinion scores by nearly 40%. DeepQoE implements a web fingerprinting solution to identify individual web browsing sessions within concurrent web pages traffic, enabling highly detailed, per web page QoE inference in practical deployments. Extensive evaluations over a large and heterogeneous dataset composed of web and app measurements, using different device types and for top-popular websites and apps, confirm the out-performance of DeepQoE over previously used shallow-learning models, as well as the deep-model generalization to different devices, web pages, apps, and network setups. DeepQoE is the first deployable system providing such a deep, highly-detailed QoE for individual web browsing and mobile apps over encrypted traffic, using deep learning models on heterogeneous measurements.

@inproceedings{info3-inproceedings-2022-11, abstract = {The wide adoption of end-to-end encryption is drastically limiting the visibility Internet Service Providers (ISPs) have on the performance of the services consumed by their customers. In times of strong competition, where customer experience plays a key role in churn management, ISPs require novel solutions enabling network-wide Quality of Experience (QoE) monitoring. To this end, we present DeepQoE, a deep-learning based approach to infer the QoE of web services and mobile applications from the ISP perspective, relying exclusively on the analysis of encrypted network traffic. Using raw features derived from the encrypted stream of bytes as input to deep Convolutional Neural Networks (CNNs), DeepQoE infers the Speed Index of web browsing sessions and general mobile apps with unprecedented accuracy, improving the state of the art by more than 25%, and reducing the QoE inference error in terms of mean opinion scores by nearly 40%. DeepQoE implements a web fingerprinting solution to identify individual web browsing sessions within concurrent web pages traffic, enabling highly detailed, per web page QoE inference in practical deployments. Extensive evaluations over a large and heterogeneous dataset composed of web and app measurements, using different device types and for top-popular websites and apps, confirm the out-performance of DeepQoE over previously used shallow-learning models, as well as the deep-model generalization to different devices, web pages, apps, and network setups. DeepQoE is the first deployable system providing such a deep, highly-detailed QoE for individual web browsing and mobile apps over encrypted traffic, using deep learning models on heterogeneous measurements.}, author = {Casas, Pedro and Wassermann, Sarah and Seufert, Michael and Wehner, Nikolas and Dinica, Olivia and Hoßfeld, Tobias}, booktitle = {Network Traffic Measurement and Analysis Conference (TMA)}, keywords = {sys:hidden:inproceedings}, month = {06}, title = {X-Ray Goggles for the ISP: Improving in-Network Web and App QoE Monitoring with Deep Learning}, year = 2022 }

%0 Conference Paper %1 info3-inproceedings-2022-11 %A Casas, Pedro %A Wassermann, Sarah %A Seufert, Michael %A Wehner, Nikolas %A Dinica, Olivia %A Hoßfeld, Tobias %B Network Traffic Measurement and Analysis Conference (TMA) %D 2022 %T X-Ray Goggles for the ISP: Improving in-Network Web and App QoE Monitoring with Deep Learning %X The wide adoption of end-to-end encryption is drastically limiting the visibility Internet Service Providers (ISPs) have on the performance of the services consumed by their customers. In times of strong competition, where customer experience plays a key role in churn management, ISPs require novel solutions enabling network-wide Quality of Experience (QoE) monitoring. To this end, we present DeepQoE, a deep-learning based approach to infer the QoE of web services and mobile applications from the ISP perspective, relying exclusively on the analysis of encrypted network traffic. Using raw features derived from the encrypted stream of bytes as input to deep Convolutional Neural Networks (CNNs), DeepQoE infers the Speed Index of web browsing sessions and general mobile apps with unprecedented accuracy, improving the state of the art by more than 25%, and reducing the QoE inference error in terms of mean opinion scores by nearly 40%. DeepQoE implements a web fingerprinting solution to identify individual web browsing sessions within concurrent web pages traffic, enabling highly detailed, per web page QoE inference in practical deployments. Extensive evaluations over a large and heterogeneous dataset composed of web and app measurements, using different device types and for top-popular websites and apps, confirm the out-performance of DeepQoE over previously used shallow-learning models, as well as the deep-model generalization to different devices, web pages, apps, and network setups. DeepQoE is the first deployable system providing such a deep, highly-detailed QoE for individual web browsing and mobile apps over encrypted traffic, using deep learning models on heterogeneous measurements.
DeepCrypt - Deep Learning for QoE Monitoring and Fingerprinting of User Actions in Adaptive Video Streaming. Casas, Pedro; Seufert, Michael; Wassermann, Sarah; Gardlo, Bruno; Wehner, Nikolas; Schatz, Raimund. In IEEE Conference on Network Softwarization (IEEE NetSoft 2022). 2022.
- [ Abstract ]
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We introduce DeepCrypt, a deep-learning based approach to analyze YouTube video streaming Quality of Experience (QoE) from the Internet Service Provider (ISP) perspective, relying exclusively on the analysis of encrypted network traffic. Using raw features derived on-line from the encrypted stream of bytes, DeepCrypt can infer six different video QoE indicators capturing the user-perceived performance of the service, including the initial playback delay, the number and frequency of rebuffering events, the video playback quality, the video encoding bitrate, and the number of quality changes. DeepCrypt offers deep visibility into the behavior of the end-user, enabling the fingerprinting and detection of different user actions on the video player, such as video pauses and playback scrubbing (forward, backward, out-of-buffer), offering a complete visibility on the video streaming process from in-network traffic measurements. Extensive evaluations over a large and heterogeneous dataset composed of mobile and fixed-line measurements, using the YouTube HTML5 player, the native YouTube mobile app, as well as a generic HTML5 video player built on top of open source libraries, and considering measurements collected at different ISPs, confirm the out-performance of DeepCrypt over previously used shallow-learning models, as well as the deep-model generalization to different video players and network setups. To the best of our knowledge, this is the first paper tackling such a combined QoE and user-actions approach for video streaming applications, using deep learning models over heterogeneous measurements.

@inproceedings{info3-inproceedings-2022-9, abstract = {We introduce DeepCrypt, a deep-learning based approach to analyze YouTube video streaming Quality of Experience (QoE) from the Internet Service Provider (ISP) perspective, relying exclusively on the analysis of encrypted network traffic. Using raw features derived on-line from the encrypted stream of bytes, DeepCrypt can infer six different video QoE indicators capturing the user-perceived performance of the service, including the initial playback delay, the number and frequency of rebuffering events, the video playback quality, the video encoding bitrate, and the number of quality changes. DeepCrypt offers deep visibility into the behavior of the end-user, enabling the fingerprinting and detection of different user actions on the video player, such as video pauses and playback scrubbing (forward, backward, out-of-buffer), offering a complete visibility on the video streaming process from in-network traffic measurements. Extensive evaluations over a large and heterogeneous dataset composed of mobile and fixed-line measurements, using the YouTube HTML5 player, the native YouTube mobile app, as well as a generic HTML5 video player built on top of open source libraries, and considering measurements collected at different ISPs, confirm the out-performance of DeepCrypt over previously used shallow-learning models, as well as the deep-model generalization to different video players and network setups. To the best of our knowledge, this is the first paper tackling such a combined QoE and user-actions approach for video streaming applications, using deep learning models over heterogeneous measurements.}, author = {Casas, Pedro and Seufert, Michael and Wassermann, Sarah and Gardlo, Bruno and Wehner, Nikolas and Schatz, Raimund}, booktitle = {IEEE Conference on Network Softwarization (IEEE NetSoft 2022)}, keywords = {sys:hidden:inproceedings}, month = {06}, title = {DeepCrypt - Deep Learning for QoE Monitoring and Fingerprinting of User Actions in Adaptive Video Streaming}, year = 2022 }

%0 Conference Paper %1 info3-inproceedings-2022-9 %A Casas, Pedro %A Seufert, Michael %A Wassermann, Sarah %A Gardlo, Bruno %A Wehner, Nikolas %A Schatz, Raimund %B IEEE Conference on Network Softwarization (IEEE NetSoft 2022) %D 2022 %T DeepCrypt - Deep Learning for QoE Monitoring and Fingerprinting of User Actions in Adaptive Video Streaming %X We introduce DeepCrypt, a deep-learning based approach to analyze YouTube video streaming Quality of Experience (QoE) from the Internet Service Provider (ISP) perspective, relying exclusively on the analysis of encrypted network traffic. Using raw features derived on-line from the encrypted stream of bytes, DeepCrypt can infer six different video QoE indicators capturing the user-perceived performance of the service, including the initial playback delay, the number and frequency of rebuffering events, the video playback quality, the video encoding bitrate, and the number of quality changes. DeepCrypt offers deep visibility into the behavior of the end-user, enabling the fingerprinting and detection of different user actions on the video player, such as video pauses and playback scrubbing (forward, backward, out-of-buffer), offering a complete visibility on the video streaming process from in-network traffic measurements. Extensive evaluations over a large and heterogeneous dataset composed of mobile and fixed-line measurements, using the YouTube HTML5 player, the native YouTube mobile app, as well as a generic HTML5 video player built on top of open source libraries, and considering measurements collected at different ISPs, confirm the out-performance of DeepCrypt over previously used shallow-learning models, as well as the deep-model generalization to different video players and network setups. To the best of our knowledge, this is the first paper tackling such a combined QoE and user-actions approach for video streaming applications, using deep learning models over heterogeneous measurements.
On Learning Hierarchical Embeddings from Encrypted Network Traffic. Wehner, Nikolas; Ring, Markus; Schüler, Joshua; Hotho, Andreas; Hoßfeld, Tobias; Seufert, Michael. In 33th IEEE/IFIP Network Operations and Management Symposium (NOMS). Budapest, Hungary, 2022.
- [ Abstract ]
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This work presents a novel concept for learning embeddings from encrypted network traffic. In contrast to existing approaches, we evaluate the feasibility of hierarchical embeddings by iteratively aggregating packet embeddings to flow embeddings, and flow embeddings to trace embeddings. The hierarchical embedding concept was designed to especially consider complex dependencies of Internet traffic on different time scales. We describe this novel embedding concept for the domain of network traffic in full detail, and evaluate its performance for the downstream task of website fingerprinting, i.e., identifying websites from encrypted traffic, which is relevant for network management, e.g., as a prerequisite for QoE monitoring or for intrusion detection. Our evaluation reveals that embeddings are a promising solution for website fingerprinting as our model correctly labels up to 99.8\% of traces from 500 target websites.

@inproceedings{info3-inproceedings-2022-1, abstract = {This work presents a novel concept for learning embeddings from encrypted network traffic. In contrast to existing approaches, we evaluate the feasibility of hierarchical embeddings by iteratively aggregating packet embeddings to flow embeddings, and flow embeddings to trace embeddings. The hierarchical embedding concept was designed to especially consider complex dependencies of Internet traffic on different time scales. We describe this novel embedding concept for the domain of network traffic in full detail, and evaluate its performance for the downstream task of website fingerprinting, i.e., identifying websites from encrypted traffic, which is relevant for network management, e.g., as a prerequisite for QoE monitoring or for intrusion detection. Our evaluation reveals that embeddings are a promising solution for website fingerprinting as our model correctly labels up to 99.8\% of traces from 500 target websites.}, address = {Budapest, Hungary}, author = {Wehner, Nikolas and Ring, Markus and Schüler, Joshua and Hotho, Andreas and Hoßfeld, Tobias and Seufert, Michael}, booktitle = {33th IEEE/IFIP Network Operations and Management Symposium (NOMS)}, keywords = {sys:hidden:inproceedings}, month = {04}, title = {On Learning Hierarchical Embeddings from Encrypted Network Traffic}, year = 2022 }

%0 Conference Paper %1 info3-inproceedings-2022-1 %A Wehner, Nikolas %A Ring, Markus %A Schüler, Joshua %A Hotho, Andreas %A Hoßfeld, Tobias %A Seufert, Michael %B 33th IEEE/IFIP Network Operations and Management Symposium (NOMS) %C Budapest, Hungary %D 2022 %T On Learning Hierarchical Embeddings from Encrypted Network Traffic %X This work presents a novel concept for learning embeddings from encrypted network traffic. In contrast to existing approaches, we evaluate the feasibility of hierarchical embeddings by iteratively aggregating packet embeddings to flow embeddings, and flow embeddings to trace embeddings. The hierarchical embedding concept was designed to especially consider complex dependencies of Internet traffic on different time scales. We describe this novel embedding concept for the domain of network traffic in full detail, and evaluate its performance for the downstream task of website fingerprinting, i.e., identifying websites from encrypted traffic, which is relevant for network management, e.g., as a prerequisite for QoE monitoring or for intrusion detection. Our evaluation reveals that embeddings are a promising solution for website fingerprinting as our model correctly labels up to 99.8\% of traces from 500 target websites.
ML-based Performance Prediction of SDN using Simulated Data from Real and Synthetic Networks. Dietz, Katharina; Gray, Nicholas; Seufert, Michael; Hoßfeld, Tobias. In 33th IEEE/IFIP Network Operations and Management Symposium (NOMS). Budapest, Hungary, 2022.
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@inproceedings{info3-inproceedings-2022-2, address = {Budapest, Hungary}, author = {Dietz, Katharina and Gray, Nicholas and Seufert, Michael and Hoßfeld, Tobias}, booktitle = {33th IEEE/IFIP Network Operations and Management Symposium (NOMS)}, keywords = {ucn}, month = {04}, title = {ML-based Performance Prediction of SDN using Simulated Data from Real and Synthetic Networks}, year = 2022 }

%0 Conference Paper %1 info3-inproceedings-2022-2 %A Dietz, Katharina %A Gray, Nicholas %A Seufert, Michael %A Hoßfeld, Tobias %B 33th IEEE/IFIP Network Operations and Management Symposium (NOMS) %C Budapest, Hungary %D 2022 %T ML-based Performance Prediction of SDN using Simulated Data from Real and Synthetic Networks
How are your Apps Doing? QoE Inference and Analysis in Mobile Devices. Wehner, Nikolas; Seufert, Michael; Schüler, Joshua; Casas, Pedro; Hoßfeld, Tobias. In 17th International Conference on Network and Service Management (CNSM). Izmir, Turkey (Virtual Conference), 2021.
- [ Abstract ]
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- [ EndNote ]
Web browsing has become the most important application of the Internet for the end user. When it comes to mobile devices, web services are mainly accessed through apps. This paper tackles the problem of Web Quality of Experience (QoE) in mobile devices, with a specific focus on apps QoE monitoring and analysis, using in-network (encrypted) traffic measurements. Measuring apps QoE is complex, not only from an instrumentation point of view, but also from the heterogeneity of user interactions which might realize substantially different user experience. To this end, we conduct a feasibility study on four specific and popular Android apps and their corresponding web services. Our test automation framework emulates and measures different user interactions commonly executed during an app session, including the app startup, clicking, scrolling, and searching. The resulting traffic is characterized on different dimensions, and machine learning models are trained to identify web services, apps, and user interactions, and to infer their QoE. The proposed models can correctly identify the specific web service and app in 86% of the cases and accurately estimate the associated QoE with small errors. Our preliminary study represents a first step towards an in-network, web QoE monitoring solution for mobile-device apps.

@inproceedings{info3-inproceedings-2021-15, abstract = {Web browsing has become the most important application of the Internet for the end user. When it comes to mobile devices, web services are mainly accessed through apps. This paper tackles the problem of Web Quality of Experience (QoE) in mobile devices, with a specific focus on apps QoE monitoring and analysis, using in-network (encrypted) traffic measurements. Measuring apps QoE is complex, not only from an instrumentation point of view, but also from the heterogeneity of user interactions which might realize substantially different user experience. To this end, we conduct a feasibility study on four specific and popular Android apps and their corresponding web services. Our test automation framework emulates and measures different user interactions commonly executed during an app session, including the app startup, clicking, scrolling, and searching. The resulting traffic is characterized on different dimensions, and machine learning models are trained to identify web services, apps, and user interactions, and to infer their QoE. The proposed models can correctly identify the specific web service and app in 86% of the cases and accurately estimate the associated QoE with small errors. Our preliminary study represents a first step towards an in-network, web QoE monitoring solution for mobile-device apps.}, address = {Izmir, Turkey (Virtual Conference)}, author = {Wehner, Nikolas and Seufert, Michael and Schüler, Joshua and Casas, Pedro and Hoßfeld, Tobias}, booktitle = {17th International Conference on Network and Service Management (CNSM)}, keywords = {ucn}, month = 10, title = {How are your Apps Doing? QoE Inference and Analysis in Mobile Devices}, year = 2021 }

%0 Conference Paper %1 info3-inproceedings-2021-15 %A Wehner, Nikolas %A Seufert, Michael %A Schüler, Joshua %A Casas, Pedro %A Hoßfeld, Tobias %B 17th International Conference on Network and Service Management (CNSM) %C Izmir, Turkey (Virtual Conference) %D 2021 %T How are your Apps Doing? QoE Inference and Analysis in Mobile Devices %X Web browsing has become the most important application of the Internet for the end user. When it comes to mobile devices, web services are mainly accessed through apps. This paper tackles the problem of Web Quality of Experience (QoE) in mobile devices, with a specific focus on apps QoE monitoring and analysis, using in-network (encrypted) traffic measurements. Measuring apps QoE is complex, not only from an instrumentation point of view, but also from the heterogeneity of user interactions which might realize substantially different user experience. To this end, we conduct a feasibility study on four specific and popular Android apps and their corresponding web services. Our test automation framework emulates and measures different user interactions commonly executed during an app session, including the app startup, clicking, scrolling, and searching. The resulting traffic is characterized on different dimensions, and machine learning models are trained to identify web services, apps, and user interactions, and to infer their QoE. The proposed models can correctly identify the specific web service and app in 86% of the cases and accurately estimate the associated QoE with small errors. Our preliminary study represents a first step towards an in-network, web QoE monitoring solution for mobile-device apps.
Machine-Learning Based Prediction of Next HTTP Request Arrival Time in Adaptive Video Streaming. Pimpinella, Andrea; Redondi, Alessandro E.C.; Loh, Frank; Seufert, Michael. In 3rd International Workshop on High-Precision, Predictable, and Low-Latency Networking (HiPNet). Izmir, Turkey (Virtual Conference), 2021.
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@inproceedings{info3-inproceedings-2021-18, address = {Izmir, Turkey (Virtual Conference)}, author = {Pimpinella, Andrea and Redondi, Alessandro E.C. and Loh, Frank and Seufert, Michael}, booktitle = {3rd International Workshop on High-Precision, Predictable, and Low-Latency Networking (HiPNet)}, keywords = {ucn}, month = 10, title = {Machine-Learning Based Prediction of Next HTTP Request Arrival Time in Adaptive Video Streaming}, year = 2021 }

%0 Conference Paper %1 info3-inproceedings-2021-18 %A Pimpinella, Andrea %A Redondi, Alessandro E.C. %A Loh, Frank %A Seufert, Michael %B 3rd International Workshop on High-Precision, Predictable, and Low-Latency Networking (HiPNet) %C Izmir, Turkey (Virtual Conference) %D 2021 %T Machine-Learning Based Prediction of Next HTTP Request Arrival Time in Adaptive Video Streaming
Mobile Web and App QoE Monitoring for ISPs - from Encrypted Traffic to Speed Index through Machine Learning. Casas, Pedro; Wassermann, Sarah; Wehner, Nikolas; Seufert, Michael; Schüler, Joshua; Hoßfeld, Tobias. In 13th Wireless and Mobile Networking Conference (WMNC), Best Paper Award. Montreal, Canada (Virtual Conference), 2021.
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@inproceedings{info3-inproceedings-2021-17, address = {Montreal, Canada (Virtual Conference)}, author = {Casas, Pedro and Wassermann, Sarah and Wehner, Nikolas and Seufert, Michael and Schüler, Joshua and Hoßfeld, Tobias}, booktitle = {13th Wireless and Mobile Networking Conference (WMNC), Best Paper Award}, keywords = {ucn}, month = 10, title = {Mobile Web and App QoE Monitoring for ISPs - from Encrypted Traffic to Speed Index through Machine Learning}, year = 2021 }

%0 Conference Paper %1 info3-inproceedings-2021-17 %A Casas, Pedro %A Wassermann, Sarah %A Wehner, Nikolas %A Seufert, Michael %A Schüler, Joshua %A Hoßfeld, Tobias %B 13th Wireless and Mobile Networking Conference (WMNC), Best Paper Award %C Montreal, Canada (Virtual Conference) %D 2021 %T Mobile Web and App QoE Monitoring for ISPs - from Encrypted Traffic to Speed Index through Machine Learning
Browser Fingerprinting: How to Protect Machine Learning Models and Data with Differential Privacy?. Dietz, Katharina; Mühlhauser, Michael; Seufert, Michael; Gray, Nicholas; Hoßfeld, Tobias; Herrmann, Dominik. In 1st International Workshop on Machine Learning in Networking (MaLeNe) as part of NetSys’21. Lübeck, Germany (Virtual Conference), 2021.
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@inproceedings{info3-inproceedings-2021-16, address = {Lübeck, Germany (Virtual Conference)}, author = {Dietz, Katharina and Mühlhauser, Michael and Seufert, Michael and Gray, Nicholas and Hoßfeld, Tobias and Herrmann, Dominik}, booktitle = {1st International Workshop on Machine Learning in Networking (MaLeNe) as part of NetSys'21}, keywords = {ucn}, month = {09}, title = {Browser Fingerprinting: How to Protect Machine Learning Models and Data with Differential Privacy?}, year = 2021 }

%0 Conference Paper %1 info3-inproceedings-2021-16 %A Dietz, Katharina %A Mühlhauser, Michael %A Seufert, Michael %A Gray, Nicholas %A Hoßfeld, Tobias %A Herrmann, Dominik %B 1st International Workshop on Machine Learning in Networking (MaLeNe) as part of NetSys'21 %C Lübeck, Germany (Virtual Conference) %D 2021 %T Browser Fingerprinting: How to Protect Machine Learning Models and Data with Differential Privacy?
On Machine Learning based Video QoE Estimation Across Different Networks. Orsolic, Irena; Seufert, Michael. In 16th International Conference on Telecommunications (ConTEL), Best Paper Award. Zagreb, Croatia (Virtual Conference), 2021.
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@inproceedings{info3-inproceedings-2021-10, address = {Zagreb, Croatia (Virtual Conference)}, author = {Orsolic, Irena and Seufert, Michael}, booktitle = {16th International Conference on Telecommunications (ConTEL), Best Paper Award}, keywords = {ucn}, month = {07}, title = {On Machine Learning based Video QoE Estimation Across Different Networks}, year = 2021 }

%0 Conference Paper %1 info3-inproceedings-2021-10 %A Orsolic, Irena %A Seufert, Michael %B 16th International Conference on Telecommunications (ConTEL), Best Paper Award %C Zagreb, Croatia (Virtual Conference) %D 2021 %T On Machine Learning based Video QoE Estimation Across Different Networks
On Inter-Rater Reliability for Crowdsourced QoE. Hoßfeld, Tobias; Seufert, Michael; Naderi, Babak. In 13th International Conference on Quality of Multimedia Experience (QoMEX). Montreal, Canada (Virtual Conference), 2021.
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@inproceedings{info3-inproceedings-2021-9, address = {Montreal, Canada (Virtual Conference)}, author = {Hoßfeld, Tobias and Seufert, Michael and Naderi, Babak}, booktitle = {13th International Conference on Quality of Multimedia Experience (QoMEX)}, keywords = {ucn}, month = {06}, title = {On Inter-Rater Reliability for Crowdsourced QoE}, year = 2021 }

%0 Conference Paper %1 info3-inproceedings-2021-9 %A Hoßfeld, Tobias %A Seufert, Michael %A Naderi, Babak %B 13th International Conference on Quality of Multimedia Experience (QoMEX) %C Montreal, Canada (Virtual Conference) %D 2021 %T On Inter-Rater Reliability for Crowdsourced QoE
High Performance Network Metadata Extraction Using P4 for ML-Based Intrusion Detection Systems. Gray, Nicholas; Dietz, Katharina; Seufert, Michael; Hoßfeld, Tobias. In 22nd International Conference on High Performance Switching and Routing (HPSR). Paris, France (Virtual Conference), 2021.
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@inproceedings{info3-inproceedings-2021-8, address = {Paris, France (Virtual Conference)}, author = {Gray, Nicholas and Dietz, Katharina and Seufert, Michael and Hoßfeld, Tobias}, booktitle = {22nd International Conference on High Performance Switching and Routing (HPSR)}, keywords = {ucn}, month = {06}, title = {High Performance Network Metadata Extraction Using P4 for ML-Based Intrusion Detection Systems}, year = 2021 }

%0 Conference Paper %1 info3-inproceedings-2021-8 %A Gray, Nicholas %A Dietz, Katharina %A Seufert, Michael %A Hoßfeld, Tobias %B 22nd International Conference on High Performance Switching and Routing (HPSR) %C Paris, France (Virtual Conference) %D 2021 %T High Performance Network Metadata Extraction Using P4 for ML-Based Intrusion Detection Systems
ML-Assisted Latency Assignments in Time-Sensitive Networking. Grigorjew, Alexej; Seufert, Michael; Wehner, Nikolas; Hofmann, Jan; Hoßfeld, Tobias. In IFIP/IEEE International Symposium on Integrated Network Management (IM 2021). Bordeaux, France (Virtual Conference), 2021.
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- [ EndNote ]
Recent developments in industrial automation and invehicle communication have raised the requirements of real-time networking. Bus systems that were traditionally deployed in these fields cannot provide sufficient bandwidth and are now shifting towards Ethernet for their real-time communication needs. In this field, standardization efforts from the IEEE and the IETF have developed new data plane mechanisms such as shapers and schedulers, as well as control plane mechanisms such as reservation protocols to support their new requirements. However, their implementation and their optimal configuration remain an important factor for their efficiency. This work presents a machine learning framework that takes on the configuration task. Four different models are trained for the configuration of per-hop latency guarantees in a distributed resource reservation process and compared with respect to their real-time traffic capacity. The evaluation shows that all models provide good configurations for the provided scenarios, but more importantly, they represent a first step for a semi-automated configuration of parameters in Time-Sensitive Networking.

@inproceedings{info3-inproceedings-2021-2, abstract = {Recent developments in industrial automation and invehicle communication have raised the requirements of real-time networking. Bus systems that were traditionally deployed in these fields cannot provide sufficient bandwidth and are now shifting towards Ethernet for their real-time communication needs. In this field, standardization efforts from the IEEE and the IETF have developed new data plane mechanisms such as shapers and schedulers, as well as control plane mechanisms such as reservation protocols to support their new requirements. However, their implementation and their optimal configuration remain an important factor for their efficiency. This work presents a machine learning framework that takes on the configuration task. Four different models are trained for the configuration of per-hop latency guarantees in a distributed resource reservation process and compared with respect to their real-time traffic capacity. The evaluation shows that all models provide good configurations for the provided scenarios, but more importantly, they represent a first step for a semi-automated configuration of parameters in Time-Sensitive Networking.}, address = {Bordeaux, France (Virtual Conference)}, author = {Grigorjew, Alexej and Seufert, Michael and Wehner, Nikolas and Hofmann, Jan and Hoßfeld, Tobias}, booktitle = {IFIP/IEEE International Symposium on Integrated Network Management (IM 2021)}, keywords = {kikdin}, month = {05}, title = {ML-Assisted Latency Assignments in Time-Sensitive Networking}, year = 2021 }

%0 Conference Paper %1 info3-inproceedings-2021-2 %A Grigorjew, Alexej %A Seufert, Michael %A Wehner, Nikolas %A Hofmann, Jan %A Hoßfeld, Tobias %B IFIP/IEEE International Symposium on Integrated Network Management (IM 2021) %C Bordeaux, France (Virtual Conference) %D 2021 %T ML-Assisted Latency Assignments in Time-Sensitive Networking %X Recent developments in industrial automation and invehicle communication have raised the requirements of real-time networking. Bus systems that were traditionally deployed in these fields cannot provide sufficient bandwidth and are now shifting towards Ethernet for their real-time communication needs. In this field, standardization efforts from the IEEE and the IETF have developed new data plane mechanisms such as shapers and schedulers, as well as control plane mechanisms such as reservation protocols to support their new requirements. However, their implementation and their optimal configuration remain an important factor for their efficiency. This work presents a machine learning framework that takes on the configuration task. Four different models are trained for the configuration of per-hop latency guarantees in a distributed resource reservation process and compared with respect to their real-time traffic capacity. The evaluation shows that all models provide good configurations for the provided scenarios, but more importantly, they represent a first step for a semi-automated configuration of parameters in Time-Sensitive Networking.
Quality that Matters: QoE Monitoring in Education Service Provider (ESP) Networks. Wehner, Nikolas; Seufert, Michael; Wieser, Viktoria; Casas, Pedro; Capdehourat, Germán. In IFIP/IEEE International Symposium on Integrated Network Management (IM 2021). Bordeaux, France (Virtual Conference), 2021.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
Education Service Providers (ESPs) play a crucial role in the digitization of education as they equip students and teachers with reliable devices and provide high quality Internet access at schools. This paper investigates four months worth of continuous measurements conducted by an ESP using a largescale, passive, in-device Quality of Experience (QoE) monitoring system deployed into a nationwide network of education-purpose devices. These measurements cover more than 800 education centers and about 4000 devices, used both in schools and at home. Using this rich dataset, we present an exhaustive characterization of the browsing behavior, and a quantification of the web and video QoE in this educational context. Web QoE results showed a better performance for school Wi-Fi networks compared to home connections, suggesting that several issues may arise for ESPs due to the increasing relevance of home-schooling caused by the COVID-19 pandemic.

@inproceedings{info3-inproceedings-2021-3, abstract = {Education Service Providers (ESPs) play a crucial role in the digitization of education as they equip students and teachers with reliable devices and provide high quality Internet access at schools. This paper investigates four months worth of continuous measurements conducted by an ESP using a largescale, passive, in-device Quality of Experience (QoE) monitoring system deployed into a nationwide network of education-purpose devices. These measurements cover more than 800 education centers and about 4000 devices, used both in schools and at home. Using this rich dataset, we present an exhaustive characterization of the browsing behavior, and a quantification of the web and video QoE in this educational context. Web QoE results showed a better performance for school Wi-Fi networks compared to home connections, suggesting that several issues may arise for ESPs due to the increasing relevance of home-schooling caused by the COVID-19 pandemic.}, address = {Bordeaux, France (Virtual Conference)}, author = {Wehner, Nikolas and Seufert, Michael and Wieser, Viktoria and Casas, Pedro and Capdehourat, Germán}, booktitle = {IFIP/IEEE International Symposium on Integrated Network Management (IM 2021)}, keywords = {ucn}, month = {05}, title = {Quality that Matters: QoE Monitoring in Education Service Provider (ESP) Networks}, year = 2021 }

%0 Conference Paper %1 info3-inproceedings-2021-3 %A Wehner, Nikolas %A Seufert, Michael %A Wieser, Viktoria %A Casas, Pedro %A Capdehourat, Germán %B IFIP/IEEE International Symposium on Integrated Network Management (IM 2021) %C Bordeaux, France (Virtual Conference) %D 2021 %T Quality that Matters: QoE Monitoring in Education Service Provider (ESP) Networks %X Education Service Providers (ESPs) play a crucial role in the digitization of education as they equip students and teachers with reliable devices and provide high quality Internet access at schools. This paper investigates four months worth of continuous measurements conducted by an ESP using a largescale, passive, in-device Quality of Experience (QoE) monitoring system deployed into a nationwide network of education-purpose devices. These measurements cover more than 800 education centers and about 4000 devices, used both in schools and at home. Using this rich dataset, we present an exhaustive characterization of the browsing behavior, and a quantification of the web and video QoE in this educational context. Web QoE results showed a better performance for school Wi-Fi networks compared to home connections, suggesting that several issues may arise for ESPs due to the increasing relevance of home-schooling caused by the COVID-19 pandemic.
Improving Web QoE Monitoring for Encrypted Network Traffic through Time Series Modeling. Wehner, Nikolas; Seufert, Michael; Schüler, Joshua; Wassermann, Sarah; Casas, Pedro; Hoßfeld, Tobias. In 2nd Workshop on AI in Networks and Distributed Systems (WAIN). Milan, Italy, 2020.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
This paper addresses the problem of Quality of Experience (QoE) monitoring for web browsing. In particular, the inference of common Web QoE metrics such as Speed Index (SI) is investigated. Based on a large dataset collected with open web-measurement platforms on different device-types, a unique feature set is designed and used to estimate the RUMSI -- an efficient approximation to SI, with machine-learning based regression and classification approaches. Results indicate that it is possible to estimate the RUMSI accurately, and that in particular, recurrent neural networks are highly suitable for the task, as they capture the network dynamics more precisely.

@inproceedings{info3-inproceedings-2020-12, abstract = {This paper addresses the problem of Quality of Experience (QoE) monitoring for web browsing. In particular, the inference of common Web QoE metrics such as Speed Index (SI) is investigated. Based on a large dataset collected with open web-measurement platforms on different device-types, a unique feature set is designed and used to estimate the RUMSI – an efficient approximation to SI, with machine-learning based regression and classification approaches. Results indicate that it is possible to estimate the RUMSI accurately, and that in particular, recurrent neural networks are highly suitable for the task, as they capture the network dynamics more precisely.}, address = {Milan, Italy}, author = {Wehner, Nikolas and Seufert, Michael and Schüler, Joshua and Wassermann, Sarah and Casas, Pedro and Hoßfeld, Tobias}, booktitle = {2nd Workshop on AI in Networks and Distributed Systems (WAIN)}, keywords = {ucn}, month = 11, title = {Improving Web QoE Monitoring for Encrypted Network Traffic through Time Series Modeling}, year = 2020 }

%0 Conference Paper %1 info3-inproceedings-2020-12 %A Wehner, Nikolas %A Seufert, Michael %A Schüler, Joshua %A Wassermann, Sarah %A Casas, Pedro %A Hoßfeld, Tobias %B 2nd Workshop on AI in Networks and Distributed Systems (WAIN) %C Milan, Italy %D 2020 %T Improving Web QoE Monitoring for Encrypted Network Traffic through Time Series Modeling %X This paper addresses the problem of Quality of Experience (QoE) monitoring for web browsing. In particular, the inference of common Web QoE metrics such as Speed Index (SI) is investigated. Based on a large dataset collected with open web-measurement platforms on different device-types, a unique feature set is designed and used to estimate the RUMSI -- an efficient approximation to SI, with machine-learning based regression and classification approaches. Results indicate that it is possible to estimate the RUMSI accurately, and that in particular, recurrent neural networks are highly suitable for the task, as they capture the network dynamics more precisely.
Mind the (QoE) Gap: On the Incompatibility of Web and Video QoE Models in the Wild. Seufert, Michael; Wehner, Nikolas; Wieser, Viktoria; Casas, Pedro; Capdehourat, Germán. In 16th International Conference on Network and Service Management (CNSM). Izmir, Turkey, 2020.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
Education Service Providers (ESPs) have a paramount role in the digitization of education, providing reliable devices for students and teachers and high quality Internet access at schools. In this paper, a large-scale, passive, in-device Quality of Experience (QoE) monitoring system is presented, which was deployed into a nationwide network of education-purpose devices. Four months' worth of continuous measurements were conducted by an ESP, covering more than 800 education centers and about 4000 devices, used both in schools and at home. When analyzing the QoE of web sessions in school networks, we identify a fundamental issue with the compatibility of web browsing and video QoE models, which inhibits the successful application of QoE-aware network management for multiple services.

@inproceedings{info3-inproceedings-2020-11, abstract = {Education Service Providers (ESPs) have a paramount role in the digitization of education, providing reliable devices for students and teachers and high quality Internet access at schools. In this paper, a large-scale, passive, in-device Quality of Experience (QoE) monitoring system is presented, which was deployed into a nationwide network of education-purpose devices. Four months' worth of continuous measurements were conducted by an ESP, covering more than 800 education centers and about 4000 devices, used both in schools and at home. When analyzing the QoE of web sessions in school networks, we identify a fundamental issue with the compatibility of web browsing and video QoE models, which inhibits the successful application of QoE-aware network management for multiple services.}, address = {Izmir, Turkey}, author = {Seufert, Michael and Wehner, Nikolas and Wieser, Viktoria and Casas, Pedro and Capdehourat, Germán}, booktitle = {16th International Conference on Network and Service Management (CNSM)}, keywords = {ucn}, month = 11, title = {Mind the (QoE) Gap: On the Incompatibility of Web and Video QoE Models in the Wild}, year = 2020 }

%0 Conference Paper %1 info3-inproceedings-2020-11 %A Seufert, Michael %A Wehner, Nikolas %A Wieser, Viktoria %A Casas, Pedro %A Capdehourat, Germán %B 16th International Conference on Network and Service Management (CNSM) %C Izmir, Turkey %D 2020 %T Mind the (QoE) Gap: On the Incompatibility of Web and Video QoE Models in the Wild %X Education Service Providers (ESPs) have a paramount role in the digitization of education, providing reliable devices for students and teachers and high quality Internet access at schools. In this paper, a large-scale, passive, in-device Quality of Experience (QoE) monitoring system is presented, which was deployed into a nationwide network of education-purpose devices. Four months' worth of continuous measurements were conducted by an ESP, covering more than 800 education centers and about 4000 devices, used both in schools and at home. When analyzing the QoE of web sessions in school networks, we identify a fundamental issue with the compatibility of web browsing and video QoE models, which inhibits the successful application of QoE-aware network management for multiple services.
Are you on Mobile or Desktop? On the Impact of End-User Device on Web QoE Inference from Encrypted Traffic. Wassermann, Sarah; Casas, Pedro; Ben Houidi, Zied; Huet, Alexis; Seufert, Michael; Wehner, Nikolas; Schüler, Joshua; Cai, Sheng-Ming; Shi, Hao; Xu, Jinchun; Hoßfeld, Tobias; Rossi, Dario. In 16th International Conference on Network and Service Management (CNSM). Izmir, Turkey, 2020.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
Web browsing is one of the key applications of the Internet, if not the most important one. We address the problem of Web Quality of Experience (QoE) monitoring from the ISP perspective, relying on in-network, passive measurements. As a proxy to Web QoE, we focus on the analysis of the well-known SpeedIndex (SI) metric. Given the lack of app-level data visibility introduced by the wide adoption of end-to-end encryption, we resort to machine-learning models to infer the SI and the QoE level of individual web page loading sessions, using as input only packet- and flow-level data. Our study targets the impact of different end-user device types (e.g., smartphone, desktop, tablet) on the performance of such models. Empirical evaluations on a large, multi-device, heterogeneous corpus of Web QoE measurements for top popular websites demonstrate that the proposed solution can infer the SI as well as estimate QoE ranges with high accuracy, using either packet-level or flow-level measurements. In addition, we show that the device type adds a strong bias in the feasibility of these Web QoE models, putting into question the applicability of previously conceived approaches on single-device measurements. To improve the state of affairs, we conceive cross-device generalizable models operating at both packet and flow levels, offering a feasible solution for Web QoE monitoring in operational, multi-device networks. To the best of our knowledge, this is the first study tackling the analysis of Web QoE from encrypted network traffic in multi-device scenarios.

@inproceedings{info3-inproceedings-2020-10, abstract = {Web browsing is one of the key applications of the Internet, if not the most important one. We address the problem of Web Quality of Experience (QoE) monitoring from the ISP perspective, relying on in-network, passive measurements. As a proxy to Web QoE, we focus on the analysis of the well-known SpeedIndex (SI) metric. Given the lack of app-level data visibility introduced by the wide adoption of end-to-end encryption, we resort to machine-learning models to infer the SI and the QoE level of individual web page loading sessions, using as input only packet- and flow-level data. Our study targets the impact of different end-user device types (e.g., smartphone, desktop, tablet) on the performance of such models. Empirical evaluations on a large, multi-device, heterogeneous corpus of Web QoE measurements for top popular websites demonstrate that the proposed solution can infer the SI as well as estimate QoE ranges with high accuracy, using either packet-level or flow-level measurements. In addition, we show that the device type adds a strong bias in the feasibility of these Web QoE models, putting into question the applicability of previously conceived approaches on single-device measurements. To improve the state of affairs, we conceive cross-device generalizable models operating at both packet and flow levels, offering a feasible solution for Web QoE monitoring in operational, multi-device networks. To the best of our knowledge, this is the first study tackling the analysis of Web QoE from encrypted network traffic in multi-device scenarios.}, address = {Izmir, Turkey}, author = {Wassermann, Sarah and Casas, Pedro and Ben Houidi, Zied and Huet, Alexis and Seufert, Michael and Wehner, Nikolas and Schüler, Joshua and Cai, Sheng-Ming and Shi, Hao and Xu, Jinchun and Hoßfeld, Tobias and Rossi, Dario}, booktitle = {16th International Conference on Network and Service Management (CNSM)}, keywords = {ucn}, month = 11, title = {Are you on Mobile or Desktop? On the Impact of End-User Device on Web QoE Inference from Encrypted Traffic}, year = 2020 }

%0 Conference Paper %1 info3-inproceedings-2020-10 %A Wassermann, Sarah %A Casas, Pedro %A Ben Houidi, Zied %A Huet, Alexis %A Seufert, Michael %A Wehner, Nikolas %A Schüler, Joshua %A Cai, Sheng-Ming %A Shi, Hao %A Xu, Jinchun %A Hoßfeld, Tobias %A Rossi, Dario %B 16th International Conference on Network and Service Management (CNSM) %C Izmir, Turkey %D 2020 %T Are you on Mobile or Desktop? On the Impact of End-User Device on Web QoE Inference from Encrypted Traffic %X Web browsing is one of the key applications of the Internet, if not the most important one. We address the problem of Web Quality of Experience (QoE) monitoring from the ISP perspective, relying on in-network, passive measurements. As a proxy to Web QoE, we focus on the analysis of the well-known SpeedIndex (SI) metric. Given the lack of app-level data visibility introduced by the wide adoption of end-to-end encryption, we resort to machine-learning models to infer the SI and the QoE level of individual web page loading sessions, using as input only packet- and flow-level data. Our study targets the impact of different end-user device types (e.g., smartphone, desktop, tablet) on the performance of such models. Empirical evaluations on a large, multi-device, heterogeneous corpus of Web QoE measurements for top popular websites demonstrate that the proposed solution can infer the SI as well as estimate QoE ranges with high accuracy, using either packet-level or flow-level measurements. In addition, we show that the device type adds a strong bias in the feasibility of these Web QoE models, putting into question the applicability of previously conceived approaches on single-device measurements. To improve the state of affairs, we conceive cross-device generalizable models operating at both packet and flow levels, offering a feasible solution for Web QoE monitoring in operational, multi-device networks. To the best of our knowledge, this is the first study tackling the analysis of Web QoE from encrypted network traffic in multi-device scenarios.
Scoring High: Analysis and Prediction of Viewer Behavior and Engagement in the Context of 2018 FIFA WC Live Streaming. Wehner, Nikolas; Seufert, Michael; Egger-Lampl, Sebastian; Gardlo, Bruno; Casas, Pedro; Schatz, Raimund. In Proceedings of the 28th ACM International Conference on Multimedia (MM). Seattle, WA, USA, 2020.
- [ BibTeX ]
- [ EndNote ]
@inproceedings{info3-inproceedings-2020-9, address = {Seattle, WA, USA}, author = {Wehner, Nikolas and Seufert, Michael and Egger-Lampl, Sebastian and Gardlo, Bruno and Casas, Pedro and Schatz, Raimund}, booktitle = {Proceedings of the 28th ACM International Conference on Multimedia (MM)}, keywords = {ucn}, month = 10, title = {Scoring High: Analysis and Prediction of Viewer Behavior and Engagement in the Context of 2018 FIFA WC Live Streaming}, year = 2020 }

%0 Conference Paper %1 info3-inproceedings-2020-9 %A Wehner, Nikolas %A Seufert, Michael %A Egger-Lampl, Sebastian %A Gardlo, Bruno %A Casas, Pedro %A Schatz, Raimund %B Proceedings of the 28th ACM International Conference on Multimedia (MM) %C Seattle, WA, USA %D 2020 %T Scoring High: Analysis and Prediction of Viewer Behavior and Engagement in the Context of 2018 FIFA WC Live Streaming
Different Points of View: Impact of 3D Point Cloud Reduction on QoE of Rendered Images. Seufert, Michael; Kargl, Julian; Schauer, Johannes; Nüchter, Andreas; Hoßfeld, Tobias. In 12th International Conference on Quality of Multimedia Experience (QoMEX). Athlone, Ireland, 2020.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
Modern photogrammetric methods as well as laser measurement systems make it easy to collect large 3D point clouds that sample objects or environments. As the recorded point clouds can be used to render computer-generated images and models, they are of particular interest in the domains of geographical and architectural engineering, as well for computer graphics (e.g., games or virtual reality). However, point clouds have a huge storage demand, thus, point clouds shall be reduced by removing some of the points. This will inevitably also reduce the Quality of Experience (QoE) of media, which is rendered from the reduced point clouds. In this work, the impact of two different reduction methods on the QoE of rendered images is investigated from two point of views, i.e., based on ratings from both naive crowdworkers as well as point cloud experts.

@inproceedings{info3-inproceedings-2020-4, abstract = {Modern photogrammetric methods as well as laser measurement systems make it easy to collect large 3D point clouds that sample objects or environments. As the recorded point clouds can be used to render computer-generated images and models, they are of particular interest in the domains of geographical and architectural engineering, as well for computer graphics (e.g., games or virtual reality). However, point clouds have a huge storage demand, thus, point clouds shall be reduced by removing some of the points. This will inevitably also reduce the Quality of Experience (QoE) of media, which is rendered from the reduced point clouds. In this work, the impact of two different reduction methods on the QoE of rendered images is investigated from two point of views, i.e., based on ratings from both naive crowdworkers as well as point cloud experts.}, address = {Athlone, Ireland}, author = {Seufert, Michael and Kargl, Julian and Schauer, Johannes and Nüchter, Andreas and Hoßfeld, Tobias}, booktitle = {12th International Conference on Quality of Multimedia Experience (QoMEX)}, keywords = {ua-net}, month = {05}, title = {Different Points of View: Impact of 3D Point Cloud Reduction on QoE of Rendered Images}, year = 2020 }

%0 Conference Paper %1 info3-inproceedings-2020-4 %A Seufert, Michael %A Kargl, Julian %A Schauer, Johannes %A Nüchter, Andreas %A Hoßfeld, Tobias %B 12th International Conference on Quality of Multimedia Experience (QoMEX) %C Athlone, Ireland %D 2020 %T Different Points of View: Impact of 3D Point Cloud Reduction on QoE of Rendered Images %X Modern photogrammetric methods as well as laser measurement systems make it easy to collect large 3D point clouds that sample objects or environments. As the recorded point clouds can be used to render computer-generated images and models, they are of particular interest in the domains of geographical and architectural engineering, as well for computer graphics (e.g., games or virtual reality). However, point clouds have a huge storage demand, thus, point clouds shall be reduced by removing some of the points. This will inevitably also reduce the Quality of Experience (QoE) of media, which is rendered from the reduced point clouds. In this work, the impact of two different reduction methods on the QoE of rendered images is investigated from two point of views, i.e., based on ratings from both naive crowdworkers as well as point cloud experts.
QoE Assessment of Enterprise Applications based on Self-motivated Ratings. Borchert, Kathrin; Seufert, Michael; Hildebrand, Kathrin; Hoßfeld, Tobias. In 12th International Conference on Quality of Multimedia Experience (QoMEX). Athlone, Ireland, 2020.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
In most companies, enterprise applications, such as office products or databases, are heavily used by employees during work hours. Impairments and performance issues not only slow down business processes, but might also increase the frustration of the workforce. While Quality of Experience (QoE) has been widely studied for personal multimedia applications, such as video streaming, its application to the business usage domain is still in its infancy. Due to several reasons, e.g., the high complexity of IT infrastructure, classical QoE studies can hardly be transferred to business applications. These studies are often independent from the context of usage and actively poll ratings from their participants. This work contrasts the commonly used "pull" method for collecting user ratings with a self-motivated "push" approach. This approach is inspired by complaint systems, in which users can directly report problems with a technical system as soon as they notice them. Therefore, performance assessments of a business application from employees of a cooperating company are collected with both rating systems during a time span of 1.5 years. Besides the analysis of the interaction of users with the "push" system, differences between the two methods are discussed. Further, QoE models for the monitored business application are derived based on the self-motivated "push" ratings.

@inproceedings{info3-inproceedings-2020-3, abstract = {In most companies, enterprise applications, such as office products or databases, are heavily used by employees during work hours. Impairments and performance issues not only slow down business processes, but might also increase the frustration of the workforce. While Quality of Experience (QoE) has been widely studied for personal multimedia applications, such as video streaming, its application to the business usage domain is still in its infancy. Due to several reasons, e.g., the high complexity of IT infrastructure, classical QoE studies can hardly be transferred to business applications. These studies are often independent from the context of usage and actively poll ratings from their participants. This work contrasts the commonly used "pull" method for collecting user ratings with a self-motivated "push" approach. This approach is inspired by complaint systems, in which users can directly report problems with a technical system as soon as they notice them. Therefore, performance assessments of a business application from employees of a cooperating company are collected with both rating systems during a time span of 1.5 years. Besides the analysis of the interaction of users with the "push" system, differences between the two methods are discussed. Further, QoE models for the monitored business application are derived based on the self-motivated "push" ratings.}, address = {Athlone, Ireland}, author = {Borchert, Kathrin and Seufert, Michael and Hildebrand, Kathrin and Hoßfeld, Tobias}, booktitle = {12th International Conference on Quality of Multimedia Experience (QoMEX)}, keywords = {kubus}, month = {05}, title = {QoE Assessment of Enterprise Applications based on Self-motivated Ratings}, year = 2020 }

%0 Conference Paper %1 info3-inproceedings-2020-3 %A Borchert, Kathrin %A Seufert, Michael %A Hildebrand, Kathrin %A Hoßfeld, Tobias %B 12th International Conference on Quality of Multimedia Experience (QoMEX) %C Athlone, Ireland %D 2020 %T QoE Assessment of Enterprise Applications based on Self-motivated Ratings %X In most companies, enterprise applications, such as office products or databases, are heavily used by employees during work hours. Impairments and performance issues not only slow down business processes, but might also increase the frustration of the workforce. While Quality of Experience (QoE) has been widely studied for personal multimedia applications, such as video streaming, its application to the business usage domain is still in its infancy. Due to several reasons, e.g., the high complexity of IT infrastructure, classical QoE studies can hardly be transferred to business applications. These studies are often independent from the context of usage and actively poll ratings from their participants. This work contrasts the commonly used "pull" method for collecting user ratings with a self-motivated "push" approach. This approach is inspired by complaint systems, in which users can directly report problems with a technical system as soon as they notice them. Therefore, performance assessments of a business application from employees of a cooperating company are collected with both rating systems during a time span of 1.5 years. Besides the analysis of the interaction of users with the "push" system, differences between the two methods are discussed. Further, QoE models for the monitored business application are derived based on the self-motivated "push" ratings.
Studying the Impact of the Content Selection Method on the Video QoE on Mobile Devices. Wehner, Nikolas; Mertinat, Nils; Seufert, Michael; Hoßfeld, Tobias. In 12th International Conference on Quality of Multimedia Experience (QoMEX). Athlone, Ireland, 2020.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
When conducting video QoE studies, participants are usually asked to rate the QoE of prepared test videos. However, participants are given no choice to select content, which they like or in which they are interested. This may cause annoyance or frustration when conducting the QoE study, which eventually might affect the QoE results of the study. The consequent question is whether the content liking has a direct impact on the submitted ratings by the participants and whether the freedom of choosing the video content in QoE studies results in better ratings. To investigate this research question, MCA, an existing framework for crowdsourced video testing, is extended and used in a pilot field study. MCA runs on mobile devices and allows users to watch the tested conditions of a QoE study within video content of their interest. The results of a QoE study with individual and dynamic content selection are compared to a QoE study with pre-selected contents. Moreover, this work includes a comparison to a previous QoE study for validation. As the previous study was conducted on desktop PCs, the MCA study further allows to identify differences in the stalling perception between studies on desktop PCs and mobile devices.

@inproceedings{info3-inproceedings-2020-8, abstract = {When conducting video QoE studies, participants are usually asked to rate the QoE of prepared test videos. However, participants are given no choice to select content, which they like or in which they are interested. This may cause annoyance or frustration when conducting the QoE study, which eventually might affect the QoE results of the study. The consequent question is whether the content liking has a direct impact on the submitted ratings by the participants and whether the freedom of choosing the video content in QoE studies results in better ratings. To investigate this research question, MCA, an existing framework for crowdsourced video testing, is extended and used in a pilot field study. MCA runs on mobile devices and allows users to watch the tested conditions of a QoE study within video content of their interest. The results of a QoE study with individual and dynamic content selection are compared to a QoE study with pre-selected contents. Moreover, this work includes a comparison to a previous QoE study for validation. As the previous study was conducted on desktop PCs, the MCA study further allows to identify differences in the stalling perception between studies on desktop PCs and mobile devices.}, address = {Athlone, Ireland}, author = {Wehner, Nikolas and Mertinat, Nils and Seufert, Michael and Hoßfeld, Tobias}, booktitle = {12th International Conference on Quality of Multimedia Experience (QoMEX)}, keywords = {ucn}, month = {05}, title = {Studying the Impact of the Content Selection Method on the Video QoE on Mobile Devices}, year = 2020 }

%0 Conference Paper %1 info3-inproceedings-2020-8 %A Wehner, Nikolas %A Mertinat, Nils %A Seufert, Michael %A Hoßfeld, Tobias %B 12th International Conference on Quality of Multimedia Experience (QoMEX) %C Athlone, Ireland %D 2020 %T Studying the Impact of the Content Selection Method on the Video QoE on Mobile Devices %X When conducting video QoE studies, participants are usually asked to rate the QoE of prepared test videos. However, participants are given no choice to select content, which they like or in which they are interested. This may cause annoyance or frustration when conducting the QoE study, which eventually might affect the QoE results of the study. The consequent question is whether the content liking has a direct impact on the submitted ratings by the participants and whether the freedom of choosing the video content in QoE studies results in better ratings. To investigate this research question, MCA, an existing framework for crowdsourced video testing, is extended and used in a pilot field study. MCA runs on mobile devices and allows users to watch the tested conditions of a QoE study within video content of their interest. The results of a QoE study with individual and dynamic content selection are compared to a QoE study with pre-selected contents. Moreover, this work includes a comparison to a previous QoE study for validation. As the previous study was conducted on desktop PCs, the MCA study further allows to identify differences in the stalling perception between studies on desktop PCs and mobile devices.
Optimizing HAS for 360-Degree Videos. Moldovan, Christian; Loh, Frank; Seufert, Michael; Hoßfeld, Tobias. In 5th IEEE/IFIP International Workshop on Analytics for Network and Service Management (AnNet). Budapest, Hungary, 2020.
- [ BibTeX ]
- [ EndNote ]
@inproceedings{info3-inproceedings-2020-1, address = {Budapest, Hungary}, author = {Moldovan, Christian and Loh, Frank and Seufert, Michael and Hoßfeld, Tobias}, booktitle = {5th IEEE/IFIP International Workshop on Analytics for Network and Service Management (AnNet)}, keywords = {net-man}, month = {04}, title = {Optimizing HAS for 360-Degree Videos}, year = 2020 }

%0 Conference Paper %1 info3-inproceedings-2020-1 %A Moldovan, Christian %A Loh, Frank %A Seufert, Michael %A Hoßfeld, Tobias %B 5th IEEE/IFIP International Workshop on Analytics for Network and Service Management (AnNet) %C Budapest, Hungary %D 2020 %T Optimizing HAS for 360-Degree Videos
I See What you See: Real Time Prediction of Video Quality from Encrypted Streaming Traffic. Wassermann, Sarah; Seufert, Michael; Casas, Pedro; Li, Gang; Kuang, Li. In 4th Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE). Los Cabos, Mexico, 2019.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
We address the problem of real-time QoE monitoring of HAS, from the ISP perspective, focusing in particular on videoresolution analysis. Given the wide adoption of end-to-end encryption, we resort to machine-learning models to predict different video resolution levels in a fine-grained scale, ranging from 144p to 1080p resolution, using as input only packet-level data. The proposed measurement system performs predictions in real time, during the course of an ongoing video-streaming session, with a time granularity as small as one second. We consider the particular case of YouTube video streaming. Empirical evaluations on a large and heterogeneous corpus of YouTube measurements demonstrate that the proposed system can predict video resolution with very high accuracy, and in real time. Different from state of the art, the prediction task is not bound to coarse-grained video quality classes and does not require chunk-detection approaches for feature extraction.

@inproceedings{info3-inproceedings-2019-28, abstract = {We address the problem of real-time QoE monitoring of HAS, from the ISP perspective, focusing in particular on videoresolution analysis. Given the wide adoption of end-to-end encryption, we resort to machine-learning models to predict different video resolution levels in a fine-grained scale, ranging from 144p to 1080p resolution, using as input only packet-level data. The proposed measurement system performs predictions in real time, during the course of an ongoing video-streaming session, with a time granularity as small as one second. We consider the particular case of YouTube video streaming. Empirical evaluations on a large and heterogeneous corpus of YouTube measurements demonstrate that the proposed system can predict video resolution with very high accuracy, and in real time. Different from state of the art, the prediction task is not bound to coarse-grained video quality classes and does not require chunk-detection approaches for feature extraction.}, address = {Los Cabos, Mexico}, author = {Wassermann, Sarah and Seufert, Michael and Casas, Pedro and Li, Gang and Kuang, Li}, booktitle = {4th Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE)}, keywords = {ua-net}, month = 10, title = {I See What you See: Real Time Prediction of Video Quality from Encrypted Streaming Traffic}, year = 2019 }

%0 Conference Paper %1 info3-inproceedings-2019-28 %A Wassermann, Sarah %A Seufert, Michael %A Casas, Pedro %A Li, Gang %A Kuang, Li %B 4th Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE) %C Los Cabos, Mexico %D 2019 %T I See What you See: Real Time Prediction of Video Quality from Encrypted Streaming Traffic %X We address the problem of real-time QoE monitoring of HAS, from the ISP perspective, focusing in particular on videoresolution analysis. Given the wide adoption of end-to-end encryption, we resort to machine-learning models to predict different video resolution levels in a fine-grained scale, ranging from 144p to 1080p resolution, using as input only packet-level data. The proposed measurement system performs predictions in real time, during the course of an ongoing video-streaming session, with a time granularity as small as one second. We consider the particular case of YouTube video streaming. Empirical evaluations on a large and heterogeneous corpus of YouTube measurements demonstrate that the proposed system can predict video resolution with very high accuracy, and in real time. Different from state of the art, the prediction task is not bound to coarse-grained video quality classes and does not require chunk-detection approaches for feature extraction.
On the Analysis of YouTube QoE in Cellular Networks through in-Smartphone Measurements. Wassermann, Sarah; Casas, Pedro; Seufert, Michael; Wamser, Florian. In 12th IFIP Wireless and Mobile Networking Conference (WMNC). Paris, France, 2019.
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@inproceedings{info3-inproceedings-2019-18, address = {Paris, France}, author = {Wassermann, Sarah and Casas, Pedro and Seufert, Michael and Wamser, Florian}, booktitle = {12th IFIP Wireless and Mobile Networking Conference (WMNC)}, keywords = {ua-net}, month = {09}, title = {On the Analysis of YouTube QoE in Cellular Networks through in-Smartphone Measurements}, year = 2019 }

%0 Conference Paper %1 info3-inproceedings-2019-18 %A Wassermann, Sarah %A Casas, Pedro %A Seufert, Michael %A Wamser, Florian %B 12th IFIP Wireless and Mobile Networking Conference (WMNC) %C Paris, France %D 2019 %T On the Analysis of YouTube QoE in Cellular Networks through in-Smartphone Measurements
Fundamental Advantages of Considering Quality of Experience Distributions over Mean Opinion Scores. Seufert, Michael. In 11th International Conference on Quality of Multimedia Experience (QoMEX). Berlin, Germany, 2019.
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@inproceedings{info3-inproceedings-2019-14, address = {Berlin, Germany}, author = {Seufert, Michael}, booktitle = {11th International Conference on Quality of Multimedia Experience (QoMEX)}, keywords = {ua-net}, month = {06}, title = {Fundamental Advantages of Considering Quality of Experience Distributions over Mean Opinion Scores}, year = 2019 }

%0 Conference Paper %1 info3-inproceedings-2019-14 %A Seufert, Michael %B 11th International Conference on Quality of Multimedia Experience (QoMEX) %C Berlin, Germany %D 2019 %T Fundamental Advantages of Considering Quality of Experience Distributions over Mean Opinion Scores
Is QUIC becoming the New TCP? On the Potential Impact of a New Protocol on Networked Multimedia QoE. Seufert, Michael; Schatz, Raimund; Wehner, Nikolas; Gardlo, Bruno; Casas, Pedro. In 11th International Conference on Quality of Multimedia Experience (QoMEX). Berlin, Germany, 2019.
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@inproceedings{info3-inproceedings-2019-13, address = {Berlin, Germany}, author = {Seufert, Michael and Schatz, Raimund and Wehner, Nikolas and Gardlo, Bruno and Casas, Pedro}, booktitle = {11th International Conference on Quality of Multimedia Experience (QoMEX)}, keywords = {ua-net}, month = {06}, title = {Is QUIC becoming the New TCP? On the Potential Impact of a New Protocol on Networked Multimedia QoE}, year = 2019 }

%0 Conference Paper %1 info3-inproceedings-2019-13 %A Seufert, Michael %A Schatz, Raimund %A Wehner, Nikolas %A Gardlo, Bruno %A Casas, Pedro %B 11th International Conference on Quality of Multimedia Experience (QoMEX) %C Berlin, Germany %D 2019 %T Is QUIC becoming the New TCP? On the Potential Impact of a New Protocol on Networked Multimedia QoE
Online Detection of Stalling and Scrubbing in Adaptive Video Streaming. Maggi, Lorenzo; Leguay, Jeremy; Seufert, Michael; Casas, Pedro. In 17th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt). Avignon, France, 2019.
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@inproceedings{info3-inproceedings-2019-12, address = {Avignon, France}, author = {Maggi, Lorenzo and Leguay, Jeremy and Seufert, Michael and Casas, Pedro}, booktitle = {17th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)}, keywords = {net-man}, month = {06}, title = {Online Detection of Stalling and Scrubbing in Adaptive Video Streaming}, year = 2019 }

%0 Conference Paper %1 info3-inproceedings-2019-12 %A Maggi, Lorenzo %A Leguay, Jeremy %A Seufert, Michael %A Casas, Pedro %B 17th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt) %C Avignon, France %D 2019 %T Online Detection of Stalling and Scrubbing in Adaptive Video Streaming
Features that Matter: Feature Selection for On-line Stalling Prediction in Encrypted Video Streaming. Seufert, Michael; Casas, Pedro; Wehner, Nikolas; Li, Gang; Kuang, Li. In 2nd International Workshop on Network Intelligence (NI). Paris, France, 2019.
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@inproceedings{info3-inproceedings-2019-11, address = {Paris, France}, author = {Seufert, Michael and Casas, Pedro and Wehner, Nikolas and Li, Gang and Kuang, Li}, booktitle = {2nd International Workshop on Network Intelligence (NI)}, keywords = {net-man}, month = {04}, title = {Features that Matter: Feature Selection for On-line Stalling Prediction in Encrypted Video Streaming}, year = 2019 }

%0 Conference Paper %1 info3-inproceedings-2019-11 %A Seufert, Michael %A Casas, Pedro %A Wehner, Nikolas %A Li, Gang %A Kuang, Li %B 2nd International Workshop on Network Intelligence (NI) %C Paris, France %D 2019 %T Features that Matter: Feature Selection for On-line Stalling Prediction in Encrypted Video Streaming
QUICker or not? - an Empirical Analysis of QUIC vs TCP for Video Streaming QoE Provisioning. Seufert, Michael; Schatz, Raimund; Wehner, Nikolas; Casas, Pedro. In 3rd International Workshop on Quality of Experience Management (QoE-Management). Paris, France, 2019.
- [ Abstract ]
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- [ EndNote ]
The introduction of the QUIC (Quick UDP Internet Connections) transport protocol by Google aimed to improve the Quality of Experience (QoE) with web services compared to the prevailing Transport Control Protocol (TCP). Nowadays, QUIC has become the default protocol to communicate between the Google Chrome browser and Google servers and accounts for an increasing share of the Internet traffic. This work investigates whether the promised QoE benefits of QUIC are indeed noticeable for end users or not. A measurement study was conducted for YouTube video streaming in two mobile and two fixed access networks, in which a defined set of videos was streamed back-to-back with QUIC and TCP in randomized order. QoE factors of video streaming (such as initial delay, the visual quality of the video, and stalling) were compared statistically to find significant differences between the streaming over QUIC and the streaming over TCP. Surprisingly, no evidence for any QoE improvement of QUIC over TCP in the context of YouTube streaming could be found.

@inproceedings{info3-inproceedings-2019-7, abstract = {The introduction of the QUIC (Quick UDP Internet Connections) transport protocol by Google aimed to improve the Quality of Experience (QoE) with web services compared to the prevailing Transport Control Protocol (TCP). Nowadays, QUIC has become the default protocol to communicate between the Google Chrome browser and Google servers and accounts for an increasing share of the Internet traffic. This work investigates whether the promised QoE benefits of QUIC are indeed noticeable for end users or not. A measurement study was conducted for YouTube video streaming in two mobile and two fixed access networks, in which a defined set of videos was streamed back-to-back with QUIC and TCP in randomized order. QoE factors of video streaming (such as initial delay, the visual quality of the video, and stalling) were compared statistically to find significant differences between the streaming over QUIC and the streaming over TCP. Surprisingly, no evidence for any QoE improvement of QUIC over TCP in the context of YouTube streaming could be found.}, address = {Paris, France}, author = {Seufert, Michael and Schatz, Raimund and Wehner, Nikolas and Casas, Pedro}, booktitle = {3rd International Workshop on Quality of Experience Management (QoE-Management)}, keywords = {ua-net}, month = {02}, title = {QUICker or not? - an Empirical Analysis of QUIC vs TCP for Video Streaming QoE Provisioning}, year = 2019 }

%0 Conference Paper %1 info3-inproceedings-2019-7 %A Seufert, Michael %A Schatz, Raimund %A Wehner, Nikolas %A Casas, Pedro %B 3rd International Workshop on Quality of Experience Management (QoE-Management) %C Paris, France %D 2019 %T QUICker or not? - an Empirical Analysis of QUIC vs TCP for Video Streaming QoE Provisioning %X The introduction of the QUIC (Quick UDP Internet Connections) transport protocol by Google aimed to improve the Quality of Experience (QoE) with web services compared to the prevailing Transport Control Protocol (TCP). Nowadays, QUIC has become the default protocol to communicate between the Google Chrome browser and Google servers and accounts for an increasing share of the Internet traffic. This work investigates whether the promised QoE benefits of QUIC are indeed noticeable for end users or not. A measurement study was conducted for YouTube video streaming in two mobile and two fixed access networks, in which a defined set of videos was streamed back-to-back with QUIC and TCP in randomized order. QoE factors of video streaming (such as initial delay, the visual quality of the video, and stalling) were compared statistically to find significant differences between the streaming over QUIC and the streaming over TCP. Surprisingly, no evidence for any QoE improvement of QUIC over TCP in the context of YouTube streaming could be found.
Stream-based Machine Learning for Real-time QoE Analysis of Encrypted Video Streaming Traffic. Seufert, Michael; Casas, Pedro; Wehner, Nikolas; Li, Gang; Kuang, Li. In 3rd International Workshop on Quality of Experience Management (QoE-Management). Paris, France, 2019.
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- [ EndNote ]
As stalling is the worst Quality of Experience (QoE) degradation of HTTP adaptive video streaming (HAS), this work presents a stream-based machine learning approach, ViCrypt, which analyzes stalling of YouTube streaming sessions in real-time from encrypted network traffic. The video streaming session is subdivided into a stream of short time slots of 1 s length, while considering two additional macro windows each for the current streaming trend and the whole ongoing streaming session. Constant memory features are extracted from the encrypted network traffic in these three windows in a stream-based fashion, and fed into a random forest model, which predicts whether the current time slot contains stalling or not. The presented system can predict stalling with a very high accuracy and the finest granularity to date (1 s), and thus, can be used in networks for real-time QoE analysis from encrypted YouTube video streaming traffic. The independent predictions for each consecutive slot of a streaming session can further be aggregated to obtain stalling estimations for the whole session. Thereby, the proposed method allows to quantify the initial delay, as well as the overall number of stalling events and the stalling ratio, i.e., the ratio of total stalling time and total playback time.

@inproceedings{info3-inproceedings-2019-8, abstract = {As stalling is the worst Quality of Experience (QoE) degradation of HTTP adaptive video streaming (HAS), this work presents a stream-based machine learning approach, ViCrypt, which analyzes stalling of YouTube streaming sessions in real-time from encrypted network traffic. The video streaming session is subdivided into a stream of short time slots of 1 s length, while considering two additional macro windows each for the current streaming trend and the whole ongoing streaming session. Constant memory features are extracted from the encrypted network traffic in these three windows in a stream-based fashion, and fed into a random forest model, which predicts whether the current time slot contains stalling or not. The presented system can predict stalling with a very high accuracy and the finest granularity to date (1 s), and thus, can be used in networks for real-time QoE analysis from encrypted YouTube video streaming traffic. The independent predictions for each consecutive slot of a streaming session can further be aggregated to obtain stalling estimations for the whole session. Thereby, the proposed method allows to quantify the initial delay, as well as the overall number of stalling events and the stalling ratio, i.e., the ratio of total stalling time and total playback time.}, address = {Paris, France}, author = {Seufert, Michael and Casas, Pedro and Wehner, Nikolas and Li, Gang and Kuang, Li}, booktitle = {3rd International Workshop on Quality of Experience Management (QoE-Management)}, keywords = {net-man}, month = {02}, title = {Stream-based Machine Learning for Real-time QoE Analysis of Encrypted Video Streaming Traffic}, year = 2019 }

%0 Conference Paper %1 info3-inproceedings-2019-8 %A Seufert, Michael %A Casas, Pedro %A Wehner, Nikolas %A Li, Gang %A Kuang, Li %B 3rd International Workshop on Quality of Experience Management (QoE-Management) %C Paris, France %D 2019 %T Stream-based Machine Learning for Real-time QoE Analysis of Encrypted Video Streaming Traffic %X As stalling is the worst Quality of Experience (QoE) degradation of HTTP adaptive video streaming (HAS), this work presents a stream-based machine learning approach, ViCrypt, which analyzes stalling of YouTube streaming sessions in real-time from encrypted network traffic. The video streaming session is subdivided into a stream of short time slots of 1 s length, while considering two additional macro windows each for the current streaming trend and the whole ongoing streaming session. Constant memory features are extracted from the encrypted network traffic in these three windows in a stream-based fashion, and fed into a random forest model, which predicts whether the current time slot contains stalling or not. The presented system can predict stalling with a very high accuracy and the finest granularity to date (1 s), and thus, can be used in networks for real-time QoE analysis from encrypted YouTube video streaming traffic. The independent predictions for each consecutive slot of a streaming session can further be aggregated to obtain stalling estimations for the whole session. Thereby, the proposed method allows to quantify the initial delay, as well as the overall number of stalling events and the stalling ratio, i.e., the ratio of total stalling time and total playback time.
A Fair Share for All: Novel Adaptation Logic for QoE Fairness of HTTP Adaptive Video Streaming. Seufert, Michael; Wehner, Nikolas; Casas, Pedro; Wamser, Florian. In 14th International Conference on Network and Service Management (CNSM), Best Paper Award. Rome, Italy, 2018.
- [ Abstract ]
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This paper presents a novel adaptation logic for HTTP adaptive streaming (HAS), which achieves not only a high Quality of Experience (QoE) but also high QoE fairness among independent and heterogeneous clients. The algorithm forces video clients to adapt the requested quality level based on the current network conditions and their individual bit rate requirements, such that the overall quality levels selected by all currently active streaming clients are fairly distributed, i.e., they do not diverge too much. The design of the algorithm is inspired by the well-known Transmission Control Protocol (TCP) congestion control, and drives heterogeneous clients to independently converge on similar quality levels without the need for communicating with each other and/or with a centralized controller in the network. By defining quality levels with equal visual quality, and preparing video representations accordingly, the quality level fairness is extended to QoE fairness. In this work, the design of the algorithm is described and a simulative performance evaluation is conducted to compare the QoE and QoE fairness of the proposed algorithm with other HAS adaptation logics.

@inproceedings{info3-inproceedings-2018-38, abstract = {This paper presents a novel adaptation logic for HTTP adaptive streaming (HAS), which achieves not only a high Quality of Experience (QoE) but also high QoE fairness among independent and heterogeneous clients. The algorithm forces video clients to adapt the requested quality level based on the current network conditions and their individual bit rate requirements, such that the overall quality levels selected by all currently active streaming clients are fairly distributed, i.e., they do not diverge too much. The design of the algorithm is inspired by the well-known Transmission Control Protocol (TCP) congestion control, and drives heterogeneous clients to independently converge on similar quality levels without the need for communicating with each other and/or with a centralized controller in the network. By defining quality levels with equal visual quality, and preparing video representations accordingly, the quality level fairness is extended to QoE fairness. In this work, the design of the algorithm is described and a simulative performance evaluation is conducted to compare the QoE and QoE fairness of the proposed algorithm with other HAS adaptation logics.}, address = {Rome, Italy}, author = {Seufert, Michael and Wehner, Nikolas and Casas, Pedro and Wamser, Florian}, booktitle = {14th International Conference on Network and Service Management (CNSM), Best Paper Award}, keywords = {can}, month = 11, title = {A Fair Share for All: Novel Adaptation Logic for QoE Fairness of HTTP Adaptive Video Streaming}, year = 2018 }

%0 Conference Paper %1 info3-inproceedings-2018-38 %A Seufert, Michael %A Wehner, Nikolas %A Casas, Pedro %A Wamser, Florian %B 14th International Conference on Network and Service Management (CNSM), Best Paper Award %C Rome, Italy %D 2018 %T A Fair Share for All: Novel Adaptation Logic for QoE Fairness of HTTP Adaptive Video Streaming %X This paper presents a novel adaptation logic for HTTP adaptive streaming (HAS), which achieves not only a high Quality of Experience (QoE) but also high QoE fairness among independent and heterogeneous clients. The algorithm forces video clients to adapt the requested quality level based on the current network conditions and their individual bit rate requirements, such that the overall quality levels selected by all currently active streaming clients are fairly distributed, i.e., they do not diverge too much. The design of the algorithm is inspired by the well-known Transmission Control Protocol (TCP) congestion control, and drives heterogeneous clients to independently converge on similar quality levels without the need for communicating with each other and/or with a centralized controller in the network. By defining quality levels with equal visual quality, and preparing video representations accordingly, the quality level fairness is extended to QoE fairness. In this work, the design of the algorithm is described and a simulative performance evaluation is conducted to compare the QoE and QoE fairness of the proposed algorithm with other HAS adaptation logics.
Potential Traffic Savings by Leveraging Proximity of Communication Groups in Mobile Messaging. Seufert, Michael; Schwind, Anika; Waigand, Marco; Hoßfeld, Tobias. In 14th International Conference on Network and Service Management (CNSM). Rome, Italy, 2018.
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Communication groups in mobile messaging applications (MMAs) multiply the data transmissions, because every message has to be delivered to all members of the communication group. Thereby, they put a high load on mobile networks. As the number of recipients is still comparably small, the dataintensive user-generated content cannot be handled efficiently in large content delivery networks. However, small communication groups, such as groups of friends or teams, might often be in close proximity, which can be leveraged to locally deliver messages by applying edge caching or device-to-device (D2D) communication. In this work, a simulation study is conducted to investigate these potential traffic savings in the mobile network. It is based on a realistic communication model of the MMA WhatsApp and utilizes different models for human mobility. The user mobility and MMA communication are simulated for a single day in a small city to obtain the ratio of messages, which could be potentially transmitted locally when utilizing edge caching and D2D communication.

@inproceedings{info3-inproceedings-2018-40, abstract = {Communication groups in mobile messaging applications (MMAs) multiply the data transmissions, because every message has to be delivered to all members of the communication group. Thereby, they put a high load on mobile networks. As the number of recipients is still comparably small, the dataintensive user-generated content cannot be handled efficiently in large content delivery networks. However, small communication groups, such as groups of friends or teams, might often be in close proximity, which can be leveraged to locally deliver messages by applying edge caching or device-to-device (D2D) communication. In this work, a simulation study is conducted to investigate these potential traffic savings in the mobile network. It is based on a realistic communication model of the MMA WhatsApp and utilizes different models for human mobility. The user mobility and MMA communication are simulated for a single day in a small city to obtain the ratio of messages, which could be potentially transmitted locally when utilizing edge caching and D2D communication.}, address = {Rome, Italy}, author = {Seufert, Michael and Schwind, Anika and Waigand, Marco and Hoßfeld, Tobias}, booktitle = {14th International Conference on Network and Service Management (CNSM)}, keywords = {can}, month = 11, title = {Potential Traffic Savings by Leveraging Proximity of Communication Groups in Mobile Messaging}, year = 2018 }

%0 Conference Paper %1 info3-inproceedings-2018-40 %A Seufert, Michael %A Schwind, Anika %A Waigand, Marco %A Hoßfeld, Tobias %B 14th International Conference on Network and Service Management (CNSM) %C Rome, Italy %D 2018 %T Potential Traffic Savings by Leveraging Proximity of Communication Groups in Mobile Messaging %X Communication groups in mobile messaging applications (MMAs) multiply the data transmissions, because every message has to be delivered to all members of the communication group. Thereby, they put a high load on mobile networks. As the number of recipients is still comparably small, the dataintensive user-generated content cannot be handled efficiently in large content delivery networks. However, small communication groups, such as groups of friends or teams, might often be in close proximity, which can be leveraged to locally deliver messages by applying edge caching or device-to-device (D2D) communication. In this work, a simulation study is conducted to investigate these potential traffic savings in the mobile network. It is based on a realistic communication model of the MMA WhatsApp and utilizes different models for human mobility. The user mobility and MMA communication are simulated for a single day in a small city to obtain the ratio of messages, which could be potentially transmitted locally when utilizing edge caching and D2D communication.
Beauty is in the Eye of the Smartphone Holder - A Data Driven Analysis of YouTube Mobile QoE. Wehner, Nikolas; Wassermann, Sarah; Casas, Pedro; Seufert, Michael; Wamser, Florian. In 14th International Conference on Network and Service Management (CNSM). Rome, Italy, 2018.
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Measuring the Quality of Experience (QoE) undergone by cellular network users has become paramount for cellular ISPs. Given its overwhelming dominance and ever-growing popularity, this paper focuses on the analysis of QoE for YouTube in mobile networks. Using a large-scale dataset of crowdsourced YouTube QoE measurements collected in smartphones with YoMoApp, we analyze the evolution of multiple relevant QoE-related metrics over time for YouTube mobile users. The dataset includes measurements from more than 360 users worldwide, spanning over the last five years. Our data-driven analysis shows a systematic performance and QoE improvement of YouTube in mobile devices over time, accompanied by an improvement of cellular network performance and by an optimization of the YouTube streaming behavior for smartphones.

@inproceedings{info3-inproceedings-2018-39, abstract = {Measuring the Quality of Experience (QoE) undergone by cellular network users has become paramount for cellular ISPs. Given its overwhelming dominance and ever-growing popularity, this paper focuses on the analysis of QoE for YouTube in mobile networks. Using a large-scale dataset of crowdsourced YouTube QoE measurements collected in smartphones with YoMoApp, we analyze the evolution of multiple relevant QoE-related metrics over time for YouTube mobile users. The dataset includes measurements from more than 360 users worldwide, spanning over the last five years. Our data-driven analysis shows a systematic performance and QoE improvement of YouTube in mobile devices over time, accompanied by an improvement of cellular network performance and by an optimization of the YouTube streaming behavior for smartphones.}, address = {Rome, Italy}, author = {Wehner, Nikolas and Wassermann, Sarah and Casas, Pedro and Seufert, Michael and Wamser, Florian}, booktitle = {14th International Conference on Network and Service Management (CNSM)}, keywords = {can}, month = 11, title = {Beauty is in the Eye of the Smartphone Holder - A Data Driven Analysis of YouTube Mobile QoE}, year = 2018 }

%0 Conference Paper %1 info3-inproceedings-2018-39 %A Wehner, Nikolas %A Wassermann, Sarah %A Casas, Pedro %A Seufert, Michael %A Wamser, Florian %B 14th International Conference on Network and Service Management (CNSM) %C Rome, Italy %D 2018 %T Beauty is in the Eye of the Smartphone Holder - A Data Driven Analysis of YouTube Mobile QoE %X Measuring the Quality of Experience (QoE) undergone by cellular network users has become paramount for cellular ISPs. Given its overwhelming dominance and ever-growing popularity, this paper focuses on the analysis of QoE for YouTube in mobile networks. Using a large-scale dataset of crowdsourced YouTube QoE measurements collected in smartphones with YoMoApp, we analyze the evolution of multiple relevant QoE-related metrics over time for YouTube mobile users. The dataset includes measurements from more than 360 users worldwide, spanning over the last five years. Our data-driven analysis shows a systematic performance and QoE improvement of YouTube in mobile devices over time, accompanied by an improvement of cellular network performance and by an optimization of the YouTube streaming behavior for smartphones.
Performance Evaluation of Service Functions Chain Placement Algorithms in Edge Cloud. Dinh-Xuan, Lam; Seufert, Michael; Wamser, Florian; Vassilakis, Constantinos; Zafeiropoulos, Anastasios; Tran-Gia, Phuoc. In 30th International Teletraffic Congress (ITC30). Vienna, Austria, 2018.
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The emergence of Network Function Virtualization (NFV) paradigm has become a potential solution dealing with the rapid growth of the global Internet traffic in the last decades. There, network appliances are transformed into Virtual Network Functions (VNF) running on a standard server. This promises to significantly reduce overall cost and energy consumption. Additionally, hardware-based network function chain is replaced by a chain of the VNFs, called Service Function Chain (SFC). The expected benefit of SFC is the reduction in the complexity when deploying heterogeneous network services. However, the considerable drawback of SFC is the distribution of the VNFs over different hosts. An inefficient placement of VNFs can induce a high latency within the chain and wasted server resources. In this work, we propose four placement algorithms that aim to efficiently place the SFC in servers with regard to minimizing service response time and resource utilization. Herein, heuristic approaches are evaluated against optimal solutions for the placement problems, which are formulated by using Integer Linear Programming. We evaluate and compare these placement strategies in a simulator. Our result shows that the optimized solutions produce lowest service response time and least server utilization in all types of simulated SFCs. On the other hand, the heuristic algorithms are also able to come close to the optimum by simple placing rules.

@inproceedings{info3-inproceedings-2018-14, abstract = {The emergence of Network Function Virtualization (NFV) paradigm has become a potential solution dealing with the rapid growth of the global Internet traffic in the last decades. There, network appliances are transformed into Virtual Network Functions (VNF) running on a standard server. This promises to significantly reduce overall cost and energy consumption. Additionally, hardware-based network function chain is replaced by a chain of the VNFs, called Service Function Chain (SFC). The expected benefit of SFC is the reduction in the complexity when deploying heterogeneous network services. However, the considerable drawback of SFC is the distribution of the VNFs over different hosts. An inefficient placement of VNFs can induce a high latency within the chain and wasted server resources. In this work, we propose four placement algorithms that aim to efficiently place the SFC in servers with regard to minimizing service response time and resource utilization. Herein, heuristic approaches are evaluated against optimal solutions for the placement problems, which are formulated by using Integer Linear Programming. We evaluate and compare these placement strategies in a simulator. Our result shows that the optimized solutions produce lowest service response time and least server utilization in all types of simulated SFCs. On the other hand, the heuristic algorithms are also able to come close to the optimum by simple placing rules.}, address = {Vienna, Austria}, author = {Dinh-Xuan, Lam and Seufert, Michael and Wamser, Florian and Vassilakis, Constantinos and Zafeiropoulos, Anastasios and Tran-Gia, Phuoc}, booktitle = {30th International Teletraffic Congress (ITC30)}, keywords = {can}, month = {09}, title = {Performance Evaluation of Service Functions Chain Placement Algorithms in Edge Cloud}, year = 2018 }

%0 Conference Paper %1 info3-inproceedings-2018-14 %A Dinh-Xuan, Lam %A Seufert, Michael %A Wamser, Florian %A Vassilakis, Constantinos %A Zafeiropoulos, Anastasios %A Tran-Gia, Phuoc %B 30th International Teletraffic Congress (ITC30) %C Vienna, Austria %D 2018 %T Performance Evaluation of Service Functions Chain Placement Algorithms in Edge Cloud %X The emergence of Network Function Virtualization (NFV) paradigm has become a potential solution dealing with the rapid growth of the global Internet traffic in the last decades. There, network appliances are transformed into Virtual Network Functions (VNF) running on a standard server. This promises to significantly reduce overall cost and energy consumption. Additionally, hardware-based network function chain is replaced by a chain of the VNFs, called Service Function Chain (SFC). The expected benefit of SFC is the reduction in the complexity when deploying heterogeneous network services. However, the considerable drawback of SFC is the distribution of the VNFs over different hosts. An inefficient placement of VNFs can induce a high latency within the chain and wasted server resources. In this work, we propose four placement algorithms that aim to efficiently place the SFC in servers with regard to minimizing service response time and resource utilization. Herein, heuristic approaches are evaluated against optimal solutions for the placement problems, which are formulated by using Integer Linear Programming. We evaluate and compare these placement strategies in a simulator. Our result shows that the optimized solutions produce lowest service response time and least server utilization in all types of simulated SFCs. On the other hand, the heuristic algorithms are also able to come close to the optimum by simple placing rules.
Investigating the Impact of Advertisement Banners and Clips on Video QoE. Zach, Ondrej; Slanina, Martin; Seufert, Michael. In 3rd Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE). Vienna, Austria, 2018.
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Although Quality of Experience (QoE) of Internet services can be affected by context influence factors, their actual impact is not widely investigated yet. In the context of online video services, web portals often display advertisement banners or clips to monetize their service. However, these advertisements can distract or annoy the users, which might degrade the QoE of the actual video service. In this work, two crowdsourcing studies were conducted to investigate the impact of advertisement banners and clips on video QoE. Therefore, both theoretical opinions on in-service advertisements and subjective quality ratings are evaluated. The findings confirm that advertisements are negatively perceived by users during service consumption, but a generally negative impact on video QoE cannot be supported, as the interplay of advertisement and the QoE of video services is rather complex.

@inproceedings{info3-inproceedings-2018-43, abstract = {Although Quality of Experience (QoE) of Internet services can be affected by context influence factors, their actual impact is not widely investigated yet. In the context of online video services, web portals often display advertisement banners or clips to monetize their service. However, these advertisements can distract or annoy the users, which might degrade the QoE of the actual video service. In this work, two crowdsourcing studies were conducted to investigate the impact of advertisement banners and clips on video QoE. Therefore, both theoretical opinions on in-service advertisements and subjective quality ratings are evaluated. The findings confirm that advertisements are negatively perceived by users during service consumption, but a generally negative impact on video QoE cannot be supported, as the interplay of advertisement and the QoE of video services is rather complex.}, address = {Vienna, Austria}, author = {Zach, Ondrej and Slanina, Martin and Seufert, Michael}, booktitle = {3rd Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE)}, keywords = {sys:hidden:inproceedings}, month = {07}, title = {Investigating the Impact of Advertisement Banners and Clips on Video QoE}, year = 2018 }

%0 Conference Paper %1 info3-inproceedings-2018-43 %A Zach, Ondrej %A Slanina, Martin %A Seufert, Michael %B 3rd Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE) %C Vienna, Austria %D 2018 %T Investigating the Impact of Advertisement Banners and Clips on Video QoE %X Although Quality of Experience (QoE) of Internet services can be affected by context influence factors, their actual impact is not widely investigated yet. In the context of online video services, web portals often display advertisement banners or clips to monetize their service. However, these advertisements can distract or annoy the users, which might degrade the QoE of the actual video service. In this work, two crowdsourcing studies were conducted to investigate the impact of advertisement banners and clips on video QoE. Therefore, both theoretical opinions on in-service advertisements and subjective quality ratings are evaluated. The findings confirm that advertisements are negatively perceived by users during service consumption, but a generally negative impact on video QoE cannot be supported, as the interplay of advertisement and the QoE of video services is rather complex.
Enhancing Machine Learning based QoE Prediction by Ensemble Models. Casas, Pedro; Seufert, Michael; Wehner, Nikolas; Schwind, Anika; Wamser, Florian. In 3rd Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE). Vienna, Austria, 2018.
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The number of smartphones connected to wireless networks and the volume of wireless network traffic generated by such devices have dramatically increased in the last few years, making it more challenging to tackle wireless network monitoring applications. The high-dimensionality of network data provided by current smartphone devices opens the door to the massive application of machine learning approaches to improve different wireless networking applications. In this paper we study the specific problem of Quality of Experience (QoE) prediction for popular smartphone apps, using machine learning models and in-smartphone measurements. We evaluate and compare different models for the analysis of smartphone generated data, including single models as well as machine learning ensembles such as bagging, boosting and stacking. Results suggest that, while decision-tree based models are the most accurate single models to predict QoE, ensemble learning models, and in particular stacking ones, are capable to significantly increase accuracy prediction and overall classification performance.

@inproceedings{info3-inproceedings-2018-29, abstract = {The number of smartphones connected to wireless networks and the volume of wireless network traffic generated by such devices have dramatically increased in the last few years, making it more challenging to tackle wireless network monitoring applications. The high-dimensionality of network data provided by current smartphone devices opens the door to the massive application of machine learning approaches to improve different wireless networking applications. In this paper we study the specific problem of Quality of Experience (QoE) prediction for popular smartphone apps, using machine learning models and in-smartphone measurements. We evaluate and compare different models for the analysis of smartphone generated data, including single models as well as machine learning ensembles such as bagging, boosting and stacking. Results suggest that, while decision-tree based models are the most accurate single models to predict QoE, ensemble learning models, and in particular stacking ones, are capable to significantly increase accuracy prediction and overall classification performance.}, address = {Vienna, Austria}, author = {Casas, Pedro and Seufert, Michael and Wehner, Nikolas and Schwind, Anika and Wamser, Florian}, booktitle = {3rd Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE)}, keywords = {can}, month = {07}, title = {Enhancing Machine Learning based QoE Prediction by Ensemble Models}, year = 2018 }

%0 Conference Paper %1 info3-inproceedings-2018-29 %A Casas, Pedro %A Seufert, Michael %A Wehner, Nikolas %A Schwind, Anika %A Wamser, Florian %B 3rd Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE) %C Vienna, Austria %D 2018 %T Enhancing Machine Learning based QoE Prediction by Ensemble Models %X The number of smartphones connected to wireless networks and the volume of wireless network traffic generated by such devices have dramatically increased in the last few years, making it more challenging to tackle wireless network monitoring applications. The high-dimensionality of network data provided by current smartphone devices opens the door to the massive application of machine learning approaches to improve different wireless networking applications. In this paper we study the specific problem of Quality of Experience (QoE) prediction for popular smartphone apps, using machine learning models and in-smartphone measurements. We evaluate and compare different models for the analysis of smartphone generated data, including single models as well as machine learning ensembles such as bagging, boosting and stacking. Results suggest that, while decision-tree based models are the most accurate single models to predict QoE, ensemble learning models, and in particular stacking ones, are capable to significantly increase accuracy prediction and overall classification performance.
Studying the Impact of HAS QoE Factors on the Standardized QoE Model P.1203. Seufert, Michael; Wehner, Nikolas; Casas, Pedro. In 3rd Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE). Vienna, Austria, 2018.
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P.1203 is a recent standardized model for assessing the Quality of Experience (QoE) of HTTP Adaptive Video Streaming (HAS). However, its complex definition does not allow for a straightforward identification of the underlying assumptions. To overcome this issue, this work investigates the impact of the well-known QoE factors of HAS, namely, initial delay, stalling, and adaptation, on the output QoE score of the model. Therefore, parameter studies are conducted using a reference implementation of P.1203, and the model response to variations of the input QoE factors are compared to results of previous QoE studies in order to get a deeper understanding of the standardized model and its inherent weighting of the QoE factors of HAS.

@inproceedings{info3-inproceedings-2018-44, abstract = {P.1203 is a recent standardized model for assessing the Quality of Experience (QoE) of HTTP Adaptive Video Streaming (HAS). However, its complex definition does not allow for a straightforward identification of the underlying assumptions. To overcome this issue, this work investigates the impact of the well-known QoE factors of HAS, namely, initial delay, stalling, and adaptation, on the output QoE score of the model. Therefore, parameter studies are conducted using a reference implementation of P.1203, and the model response to variations of the input QoE factors are compared to results of previous QoE studies in order to get a deeper understanding of the standardized model and its inherent weighting of the QoE factors of HAS.}, address = {Vienna, Austria}, author = {Seufert, Michael and Wehner, Nikolas and Casas, Pedro}, booktitle = {3rd Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE)}, keywords = {sys:hidden:inproceedings}, month = {07}, title = {Studying the Impact of HAS QoE Factors on the Standardized QoE Model P.1203}, year = 2018 }

%0 Conference Paper %1 info3-inproceedings-2018-44 %A Seufert, Michael %A Wehner, Nikolas %A Casas, Pedro %B 3rd Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE) %C Vienna, Austria %D 2018 %T Studying the Impact of HAS QoE Factors on the Standardized QoE Model P.1203 %X P.1203 is a recent standardized model for assessing the Quality of Experience (QoE) of HTTP Adaptive Video Streaming (HAS). However, its complex definition does not allow for a straightforward identification of the underlying assumptions. To overcome this issue, this work investigates the impact of the well-known QoE factors of HAS, namely, initial delay, stalling, and adaptation, on the output QoE score of the model. Therefore, parameter studies are conducted using a reference implementation of P.1203, and the model response to variations of the input QoE factors are compared to results of previous QoE studies in order to get a deeper understanding of the standardized model and its inherent weighting of the QoE factors of HAS.
Streaming Characteristics of Spotify Sessions. Schwind, Anika; Wamser, Florian; Gensler, Thomas; Seufert, Michael; Casas, Pedro; Tran-Gia, Phuoc. In The 2nd International Workshop on Quality of Experience Management. Sardinia, Italy, 2018.
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Internet Service Providers need a thorough understanding of a service to maximize the Quality of Experience (QoE) of their customers by network management. Instead of quantifying the user satisfaction with long and cost-intensive subjective user studies, the QoE can often be estimated with the help of dedicated measurements of application and network parameters. We designed a QoE measurement tool for the popular audio streaming service Spotify that runs inside a Docker software container. The container is able to run headlessly as active measurement probe and emulates a user who is streaming audio files via Spotify. While streaming, network and application parameters are collected that have a high correlation to the user's QoE. The results of the measurements are used to characterize audio streaming in Spotify on application and network layer, and to evaluate important QoE factors.

@inproceedings{info3-inproceedings-2018-13, abstract = {Internet Service Providers need a thorough understanding of a service to maximize the Quality of Experience (QoE) of their customers by network management. Instead of quantifying the user satisfaction with long and cost-intensive subjective user studies, the QoE can often be estimated with the help of dedicated measurements of application and network parameters. We designed a QoE measurement tool for the popular audio streaming service Spotify that runs inside a Docker software container. The container is able to run headlessly as active measurement probe and emulates a user who is streaming audio files via Spotify. While streaming, network and application parameters are collected that have a high correlation to the user's QoE. The results of the measurements are used to characterize audio streaming in Spotify on application and network layer, and to evaluate important QoE factors.}, address = {Sardinia, Italy}, author = {Schwind, Anika and Wamser, Florian and Gensler, Thomas and Seufert, Michael and Casas, Pedro and Tran-Gia, Phuoc}, booktitle = {The 2nd International Workshop on Quality of Experience Management}, keywords = {can}, month = {05}, title = {Streaming Characteristics of Spotify Sessions}, year = 2018 }

%0 Conference Paper %1 info3-inproceedings-2018-13 %A Schwind, Anika %A Wamser, Florian %A Gensler, Thomas %A Seufert, Michael %A Casas, Pedro %A Tran-Gia, Phuoc %B The 2nd International Workshop on Quality of Experience Management %C Sardinia, Italy %D 2018 %T Streaming Characteristics of Spotify Sessions %X Internet Service Providers need a thorough understanding of a service to maximize the Quality of Experience (QoE) of their customers by network management. Instead of quantifying the user satisfaction with long and cost-intensive subjective user studies, the QoE can often be estimated with the help of dedicated measurements of application and network parameters. We designed a QoE measurement tool for the popular audio streaming service Spotify that runs inside a Docker software container. The container is able to run headlessly as active measurement probe and emulates a user who is streaming audio files via Spotify. While streaming, network and application parameters are collected that have a high correlation to the user's QoE. The results of the measurements are used to characterize audio streaming in Spotify on application and network layer, and to evaluate important QoE factors.
A Wrapper for Automatic Measurements with YouTube’s Native Android App. Seufert, Michael; Zeidler, Bernd; Wamser, Florian; Karagkioules, Theodoros; Tsilimantos, Dimitrios; Loh, Frank; Tran-Gia, Phuoc; Valentin, Stefan. In Network Traffic Measurement and Analysis Conference (TMA). Vienna, Austria, 2018.
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YouTube is one of the most popular and demanding services in the Internet today. Thereby, a large portion of this traffic is generated by YouTube's mobile app. While past studies have shown how to monitor browser-based streaming on desktop PCs (e.g., YoMo) or mobile devices (e.g., YoMoApp), streaming in the native app has not been monitored yet. This paper presents an automated framework for monitoring the streaming in YouTube's native app for Android. The concept is based on a wrapper application and the Android Debug Bridge (adb), and can be also extended to automatic measurements with other apps. For YouTube, it allows to collect application-layer streaming data, such as current playtime, buffered playtime, video encoding, and quality switches. These data can be complemented with network measurements on the mobile access link to obtain a holistic view on mobile YouTube streaming on Android devices. In addition to describing the software design and testbed setup, this paper discusses an experimental measurement. This study analyzes the streaming in the native YouTube app and compares it to the streaming from the mobile YouTube website via YoMoApp.

@inproceedings{info3-article-2018-4, abstract = {YouTube is one of the most popular and demanding services in the Internet today. Thereby, a large portion of this traffic is generated by YouTube's mobile app. While past studies have shown how to monitor browser-based streaming on desktop PCs (e.g., YoMo) or mobile devices (e.g., YoMoApp), streaming in the native app has not been monitored yet. This paper presents an automated framework for monitoring the streaming in YouTube's native app for Android. The concept is based on a wrapper application and the Android Debug Bridge (adb), and can be also extended to automatic measurements with other apps. For YouTube, it allows to collect application-layer streaming data, such as current playtime, buffered playtime, video encoding, and quality switches. These data can be complemented with network measurements on the mobile access link to obtain a holistic view on mobile YouTube streaming on Android devices. In addition to describing the software design and testbed setup, this paper discusses an experimental measurement. This study analyzes the streaming in the native YouTube app and compares it to the streaming from the mobile YouTube website via YoMoApp.}, address = {Vienna, Austria}, author = {Seufert, Michael and Zeidler, Bernd and Wamser, Florian and Karagkioules, Theodoros and Tsilimantos, Dimitrios and Loh, Frank and Tran-Gia, Phuoc and Valentin, Stefan}, booktitle = {Network Traffic Measurement and Analysis Conference (TMA)}, keywords = {can}, month = {04}, title = {A Wrapper for Automatic Measurements with YouTube's Native Android App}, year = 2018 }

%0 Conference Paper %1 info3-article-2018-4 %A Seufert, Michael %A Zeidler, Bernd %A Wamser, Florian %A Karagkioules, Theodoros %A Tsilimantos, Dimitrios %A Loh, Frank %A Tran-Gia, Phuoc %A Valentin, Stefan %B Network Traffic Measurement and Analysis Conference (TMA) %C Vienna, Austria %D 2018 %T A Wrapper for Automatic Measurements with YouTube's Native Android App %X YouTube is one of the most popular and demanding services in the Internet today. Thereby, a large portion of this traffic is generated by YouTube's mobile app. While past studies have shown how to monitor browser-based streaming on desktop PCs (e.g., YoMo) or mobile devices (e.g., YoMoApp), streaming in the native app has not been monitored yet. This paper presents an automated framework for monitoring the streaming in YouTube's native app for Android. The concept is based on a wrapper application and the Android Debug Bridge (adb), and can be also extended to automatic measurements with other apps. For YouTube, it allows to collect application-layer streaming data, such as current playtime, buffered playtime, video encoding, and quality switches. These data can be complemented with network measurements on the mobile access link to obtain a holistic view on mobile YouTube streaming on Android devices. In addition to describing the software design and testbed setup, this paper discusses an experimental measurement. This study analyzes the streaming in the native YouTube app and compares it to the streaming from the mobile YouTube website via YoMoApp.
Quality of Experience and Access Network Traffic Management of HTTP Adaptive Video Streaming. Seufert, Michael; Tran-Gia, Phuoc. In IEEE/IFIP Network Operations and Management Symposium (NOMS), Best Dissertation Award. Taipei, Taiwan, 2018.
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The thesis focuses on Quality of Experience (QoE) of HTTP adaptive video streaming (HAS) and traffic management in access networks to improve the QoE of HAS. First, the QoE impact of adaptation parameters and time on layer was investigated with subjective crowdsourcing studies. The results were used to compute a QoE-optimal adaptation strategy for given video and network conditions. This allows video service providers to develop and benchmark improved adaptation logics for HAS. Furthermore, the thesis investigated concepts to monitor video QoE on application and network layer, which can be used by network providers in the QoE-aware traffic management cycle. Moreover, an analytic and simulative performance evaluation of QoE-aware traffic management on a bottleneck link was conducted. Finally, the thesis investigated socially-aware traffic management for HAS via Wi-Fi offloading of mobile HAS flows. A model for the distribution of public Wi-Fi hotspots and a platform for socially-aware traffic management on private home routers was presented. A simulative performance evaluation investigated the impact of Wi-Fi offloading on the QoE and energy consumption of mobile HAS.

@inproceedings{info3-inproceedings-2018-42, abstract = {The thesis focuses on Quality of Experience (QoE) of HTTP adaptive video streaming (HAS) and traffic management in access networks to improve the QoE of HAS. First, the QoE impact of adaptation parameters and time on layer was investigated with subjective crowdsourcing studies. The results were used to compute a QoE-optimal adaptation strategy for given video and network conditions. This allows video service providers to develop and benchmark improved adaptation logics for HAS. Furthermore, the thesis investigated concepts to monitor video QoE on application and network layer, which can be used by network providers in the QoE-aware traffic management cycle. Moreover, an analytic and simulative performance evaluation of QoE-aware traffic management on a bottleneck link was conducted. Finally, the thesis investigated socially-aware traffic management for HAS via Wi-Fi offloading of mobile HAS flows. A model for the distribution of public Wi-Fi hotspots and a platform for socially-aware traffic management on private home routers was presented. A simulative performance evaluation investigated the impact of Wi-Fi offloading on the QoE and energy consumption of mobile HAS.}, address = {Taipei, Taiwan}, author = {Seufert, Michael and Tran-Gia, Phuoc}, booktitle = {IEEE/IFIP Network Operations and Management Symposium (NOMS), Best Dissertation Award}, keywords = {sys:hidden:inproceedings}, month = {04}, title = {Quality of Experience and Access Network Traffic Management of HTTP Adaptive Video Streaming}, year = 2018 }

%0 Conference Paper %1 info3-inproceedings-2018-42 %A Seufert, Michael %A Tran-Gia, Phuoc %B IEEE/IFIP Network Operations and Management Symposium (NOMS), Best Dissertation Award %C Taipei, Taiwan %D 2018 %T Quality of Experience and Access Network Traffic Management of HTTP Adaptive Video Streaming %X The thesis focuses on Quality of Experience (QoE) of HTTP adaptive video streaming (HAS) and traffic management in access networks to improve the QoE of HAS. First, the QoE impact of adaptation parameters and time on layer was investigated with subjective crowdsourcing studies. The results were used to compute a QoE-optimal adaptation strategy for given video and network conditions. This allows video service providers to develop and benchmark improved adaptation logics for HAS. Furthermore, the thesis investigated concepts to monitor video QoE on application and network layer, which can be used by network providers in the QoE-aware traffic management cycle. Moreover, an analytic and simulative performance evaluation of QoE-aware traffic management on a bottleneck link was conducted. Finally, the thesis investigated socially-aware traffic management for HAS via Wi-Fi offloading of mobile HAS flows. A model for the distribution of public Wi-Fi hotspots and a platform for socially-aware traffic management on private home routers was presented. A simulative performance evaluation investigated the impact of Wi-Fi offloading on the QoE and energy consumption of mobile HAS.
Performance Evaluation of Mobile Crowdsensing for Event Detection. Hirth, Matthias; Lange, Stanislav; Seufert, Michael; Tran-Gia, Phuoc. In Proceedings of the 5th International Workshop on Crowd Assisted Sensing, Pervasive Systems and Communications. Athens, Greece, 2018.
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Crowdsensing offers a cost effective way to collect large amounts of sensor data. However, in contrast to fixed sensor deployments, the spatial distribution of the sensors can hardly be influence, as the sensors are carried by participants of the crowdsensing system. This in turn raises the question about the performance of such systems with respect to the detection probability and detection time of spatial events. In order to address this question, we analyze the performance of such a crowdsensing system by means of simulation. We use the traffic infrastructure of a small size city in Germany and simulate the inhabitants’ movement patterns with the well established SUMO mobility generator. Our results show that even if only a small share of inhabitants participates in crowdsensing, events, which have locations that are correlated with the population density, can be easily and quickly detected using such a system. On the contrary, events whose locations are uniformly randomly distributed are much harder to detect using a crowdsensing approach.

@inproceedings{info3-inproceedings-2017-21, abstract = {Crowdsensing offers a cost effective way to collect large amounts of sensor data. However, in contrast to fixed sensor deployments, the spatial distribution of the sensors can hardly be influence, as the sensors are carried by participants of the crowdsensing system. This in turn raises the question about the performance of such systems with respect to the detection probability and detection time of spatial events. In order to address this question, we analyze the performance of such a crowdsensing system by means of simulation. We use the traffic infrastructure of a small size city in Germany and simulate the inhabitants’ movement patterns with the well established SUMO mobility generator. Our results show that even if only a small share of inhabitants participates in crowdsensing, events, which have locations that are correlated with the population density, can be easily and quickly detected using such a system. On the contrary, events whose locations are uniformly randomly distributed are much harder to detect using a crowdsensing approach.}, address = {Athens, Greece}, author = {Hirth, Matthias and Lange, Stanislav and Seufert, Michael and Tran-Gia, Phuoc}, booktitle = {Proceedings of the 5th International Workshop on Crowd Assisted Sensing, Pervasive Systems and Communications}, keywords = {sys:hidden:inproceedings}, month = {03}, title = {Performance Evaluation of Mobile Crowdsensing for Event Detection}, year = 2018 }

%0 Conference Paper %1 info3-inproceedings-2017-21 %A Hirth, Matthias %A Lange, Stanislav %A Seufert, Michael %A Tran-Gia, Phuoc %B Proceedings of the 5th International Workshop on Crowd Assisted Sensing, Pervasive Systems and Communications %C Athens, Greece %D 2018 %T Performance Evaluation of Mobile Crowdsensing for Event Detection %X Crowdsensing offers a cost effective way to collect large amounts of sensor data. However, in contrast to fixed sensor deployments, the spatial distribution of the sensors can hardly be influence, as the sensors are carried by participants of the crowdsensing system. This in turn raises the question about the performance of such systems with respect to the detection probability and detection time of spatial events. In order to address this question, we analyze the performance of such a crowdsensing system by means of simulation. We use the traffic infrastructure of a small size city in Germany and simulate the inhabitants’ movement patterns with the well established SUMO mobility generator. Our results show that even if only a small share of inhabitants participates in crowdsensing, events, which have locations that are correlated with the population density, can be easily and quickly detected using such a system. On the contrary, events whose locations are uniformly randomly distributed are much harder to detect using a crowdsensing approach.
A Public Dataset for YouTube’s Mobile Streaming Client. Karagkioules, Theodoros; Tsilimantos, Dimitrios; Valentin, Stefan; Wamser, Florian; Zeidler, Bernd; Seufert, Michael; Loh, Frank; Tran-Gia, Phuoc. In Network Traffic Measurement and Analysis Conference (TMA). Vienna, Austria, 2018.
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@inproceedings{info3-inproceedings-2018-41, address = {Vienna, Austria}, author = {Karagkioules, Theodoros and Tsilimantos, Dimitrios and Valentin, Stefan and Wamser, Florian and Zeidler, Bernd and Seufert, Michael and Loh, Frank and Tran-Gia, Phuoc}, booktitle = {Network Traffic Measurement and Analysis Conference (TMA)}, keywords = {can}, title = {A Public Dataset for YouTube’s Mobile Streaming Client}, year = 2018 }

%0 Conference Paper %1 info3-inproceedings-2018-41 %A Karagkioules, Theodoros %A Tsilimantos, Dimitrios %A Valentin, Stefan %A Wamser, Florian %A Zeidler, Bernd %A Seufert, Michael %A Loh, Frank %A Tran-Gia, Phuoc %B Network Traffic Measurement and Analysis Conference (TMA) %C Vienna, Austria %D 2018 %T A Public Dataset for YouTube’s Mobile Streaming Client
Performance Evaluation of Selective Flow Monitoring in the ONOS Controller. Nguyen-Ngoc, Anh; Lange, Stanislav; Zinner, Thomas; Seufert, Michael; Tran-Gia, Phuoc; Aerts, Nieke; Hock, David. In 4th International Workshop on Management of SDN and NFV Systems (ManSDN/NFV). Tokio, Japan, 2017.
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- [ EndNote ]
One of the benefits when network operators adopt the Software Defined Networking (SDN) paradigm is the ability to monitor the traffic in the network without an additional network management system. Usually, SDN controllers utilize OpenFlow statistics messages in order to regularly gather information about all flows in the network. However, using the same polling interval for all flows does not take into account the heterogeneity of real world traffic and thus results in an imbalance between monitoring accuracy and control plane overhead. In particular, frequent querying results in a high resource consumption at the controller. This work proposes a Selective Flow Monitoring (SFM) mechanism that allows administrators to classify flows according to their individual requirements in terms of monitoring frequency, e.g., less frequent polling of elephant flows and frequent polling of QoS sensitive VoIP connections. We compare the performance of the SFM mechanism with the default monitoring scheme in a testbed featuring the Open Network Operating System (ONOS) controller. In this context, the CPU utilization of the controller is used as performance indicator. After identifying relevant influence factors like the number of flows and switches in the network, we investigate the viability of the approaches in different scenarios. Finally, we provide guidelines regarding their choice.

@inproceedings{info3-inproceedings-2017-20, abstract = {One of the benefits when network operators adopt the Software Defined Networking (SDN) paradigm is the ability to monitor the traffic in the network without an additional network management system. Usually, SDN controllers utilize OpenFlow statistics messages in order to regularly gather information about all flows in the network. However, using the same polling interval for all flows does not take into account the heterogeneity of real world traffic and thus results in an imbalance between monitoring accuracy and control plane overhead. In particular, frequent querying results in a high resource consumption at the controller. This work proposes a Selective Flow Monitoring (SFM) mechanism that allows administrators to classify flows according to their individual requirements in terms of monitoring frequency, e.g., less frequent polling of elephant flows and frequent polling of QoS sensitive VoIP connections. We compare the performance of the SFM mechanism with the default monitoring scheme in a testbed featuring the Open Network Operating System (ONOS) controller. In this context, the CPU utilization of the controller is used as performance indicator. After identifying relevant influence factors like the number of flows and switches in the network, we investigate the viability of the approaches in different scenarios. Finally, we provide guidelines regarding their choice.}, address = {Tokio, Japan}, author = {Nguyen-Ngoc, Anh and Lange, Stanislav and Zinner, Thomas and Seufert, Michael and Tran-Gia, Phuoc and Aerts, Nieke and Hock, David}, booktitle = {4th International Workshop on Management of SDN and NFV Systems (ManSDN/NFV)}, keywords = {sys:hidden:inproceedings}, month = 11, title = {Performance Evaluation of Selective Flow Monitoring in the ONOS Controller}, year = 2017 }

%0 Conference Paper %1 info3-inproceedings-2017-20 %A Nguyen-Ngoc, Anh %A Lange, Stanislav %A Zinner, Thomas %A Seufert, Michael %A Tran-Gia, Phuoc %A Aerts, Nieke %A Hock, David %B 4th International Workshop on Management of SDN and NFV Systems (ManSDN/NFV) %C Tokio, Japan %D 2017 %T Performance Evaluation of Selective Flow Monitoring in the ONOS Controller %X One of the benefits when network operators adopt the Software Defined Networking (SDN) paradigm is the ability to monitor the traffic in the network without an additional network management system. Usually, SDN controllers utilize OpenFlow statistics messages in order to regularly gather information about all flows in the network. However, using the same polling interval for all flows does not take into account the heterogeneity of real world traffic and thus results in an imbalance between monitoring accuracy and control plane overhead. In particular, frequent querying results in a high resource consumption at the controller. This work proposes a Selective Flow Monitoring (SFM) mechanism that allows administrators to classify flows according to their individual requirements in terms of monitoring frequency, e.g., less frequent polling of elephant flows and frequent polling of QoS sensitive VoIP connections. We compare the performance of the SFM mechanism with the default monitoring scheme in a testbed featuring the Open Network Operating System (ONOS) controller. In this context, the CPU utilization of the controller is used as performance indicator. After identifying relevant influence factors like the number of flows and switches in the network, we investigate the viability of the approaches in different scenarios. Finally, we provide guidelines regarding their choice.
Applicability and Limitations of a Simple WiFi Hotspot Model for Cities. Seufert, Michael; Moldovan, Christian; Burger, Valentin; Hoßfeld, Tobias. In 13th International Conference on Network and Service Management (CNSM). Tokio, Japan, 2017.
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Offloading mobile Internet data via WiFi has emerged as an omnipresent trend. WiFi networks are already widely deployed by many private and public institutions (e.g., libraries, cafes, restaurants) but also by commercial services to provide alternative Internet access for their customers and to mitigate the load on mobile networks. Moreover, smart cities start to install WiFi infrastructure for current and future civic services, e.g., based on sensor networks or the Internet of Things. A simple model for the distribution of WiFi hotspots in an urban environment is presented. The hotspot locations are modeled with a uniform distribution of the angle and an exponential distribution of the distance, which is truncated to the city limits. We compare the characteristics of this model in detail to the real distributions. Moreover, we show the applicability and the limitations of this model, and the results suggest that the model can be used in scenarios, which do not require an accurate spatial collocation of the hotspots, such as offloading potential, coverage, or signal strength.

@inproceedings{info3-inproceedings-2017-19, abstract = {Offloading mobile Internet data via WiFi has emerged as an omnipresent trend. WiFi networks are already widely deployed by many private and public institutions (e.g., libraries, cafes, restaurants) but also by commercial services to provide alternative Internet access for their customers and to mitigate the load on mobile networks. Moreover, smart cities start to install WiFi infrastructure for current and future civic services, e.g., based on sensor networks or the Internet of Things. A simple model for the distribution of WiFi hotspots in an urban environment is presented. The hotspot locations are modeled with a uniform distribution of the angle and an exponential distribution of the distance, which is truncated to the city limits. We compare the characteristics of this model in detail to the real distributions. Moreover, we show the applicability and the limitations of this model, and the results suggest that the model can be used in scenarios, which do not require an accurate spatial collocation of the hotspots, such as offloading potential, coverage, or signal strength.}, address = {Tokio, Japan}, author = {Seufert, Michael and Moldovan, Christian and Burger, Valentin and Hoßfeld, Tobias}, booktitle = {13th International Conference on Network and Service Management (CNSM)}, keywords = {can}, month = 11, title = {Applicability and Limitations of a Simple WiFi Hotspot Model for Cities}, year = 2017 }

%0 Conference Paper %1 info3-inproceedings-2017-19 %A Seufert, Michael %A Moldovan, Christian %A Burger, Valentin %A Hoßfeld, Tobias %B 13th International Conference on Network and Service Management (CNSM) %C Tokio, Japan %D 2017 %T Applicability and Limitations of a Simple WiFi Hotspot Model for Cities %X Offloading mobile Internet data via WiFi has emerged as an omnipresent trend. WiFi networks are already widely deployed by many private and public institutions (e.g., libraries, cafes, restaurants) but also by commercial services to provide alternative Internet access for their customers and to mitigate the load on mobile networks. Moreover, smart cities start to install WiFi infrastructure for current and future civic services, e.g., based on sensor networks or the Internet of Things. A simple model for the distribution of WiFi hotspots in an urban environment is presented. The hotspot locations are modeled with a uniform distribution of the angle and an exponential distribution of the distance, which is truncated to the city limits. We compare the characteristics of this model in detail to the real distributions. Moreover, we show the applicability and the limitations of this model, and the results suggest that the model can be used in scenarios, which do not require an accurate spatial collocation of the hotspots, such as offloading potential, coverage, or signal strength.
Automated Decision Making based on Pareto Frontiers in the Context of Service Placement in Networks. Seufert, Michael; Lange, Stanislav; Meixner, Markus. In 29th International Teletraffic Congress (ITC). Genoa, Italy, 2017.
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Virtualization paradigms like cloud computing, software defined networking (SDN), and network functions virtualization (NFV) provide advantages with respect to aspects like flexibility, costs, and scalability. However, management and orchestration of the resulting networks also introduce new challenges. The placement of services, such as virtual machines~(VMs), virtualized network functions~(VNFs), or SDN controllers, is a multi-objective optimization task that confronts operators with a multitude of possible solutions that are incomparable among each other. The goal of this work is to investigate mechanisms that enable automated decision making between such multi-dimensional solutions. To this end, we investigate techniques from the domain of multi-attribute decision making that aggregate the performance of placements to a single numeric score. A comparison between resulting rankings of placements shows that many techniques produce similar results. Hence, placements that achieve good rankings according to many approaches might be viable candidates in the context of automated decision making. In order to illustrate the functionality of the different scoring mechanisms, we perform a case study on a single network graph and a fixed number of objectives and service instances. Additionally, we present aggregated results from broad evaluations on the Internet Topology Zoo and a larger number of objectives as well as varying numbers of service instances. These allow making more reliable statements about the mechanisms' performance and agreement.

@inproceedings{info3-article-2017-6, abstract = {Virtualization paradigms like cloud computing, software defined networking (SDN), and network functions virtualization (NFV) provide advantages with respect to aspects like flexibility, costs, and scalability. However, management and orchestration of the resulting networks also introduce new challenges. The placement of services, such as virtual machines (VMs), virtualized network functions (VNFs), or SDN controllers, is a multi-objective optimization task that confronts operators with a multitude of possible solutions that are incomparable among each other. The goal of this work is to investigate mechanisms that enable automated decision making between such multi-dimensional solutions. To this end, we investigate techniques from the domain of multi-attribute decision making that aggregate the performance of placements to a single numeric score. A comparison between resulting rankings of placements shows that many techniques produce similar results. Hence, placements that achieve good rankings according to many approaches might be viable candidates in the context of automated decision making. In order to illustrate the functionality of the different scoring mechanisms, we perform a case study on a single network graph and a fixed number of objectives and service instances. Additionally, we present aggregated results from broad evaluations on the Internet Topology Zoo and a larger number of objectives as well as varying numbers of service instances. These allow making more reliable statements about the mechanisms' performance and agreement.}, address = {Genoa, Italy}, author = {Seufert, Michael and Lange, Stanislav and Meixner, Markus}, booktitle = {29th International Teletraffic Congress (ITC)}, keywords = {can}, month = {09}, title = {Automated Decision Making based on Pareto Frontiers in the Context of Service Placement in Networks}, year = 2017 }

%0 Conference Paper %1 info3-article-2017-6 %A Seufert, Michael %A Lange, Stanislav %A Meixner, Markus %B 29th International Teletraffic Congress (ITC) %C Genoa, Italy %D 2017 %T Automated Decision Making based on Pareto Frontiers in the Context of Service Placement in Networks %X Virtualization paradigms like cloud computing, software defined networking (SDN), and network functions virtualization (NFV) provide advantages with respect to aspects like flexibility, costs, and scalability. However, management and orchestration of the resulting networks also introduce new challenges. The placement of services, such as virtual machines~(VMs), virtualized network functions~(VNFs), or SDN controllers, is a multi-objective optimization task that confronts operators with a multitude of possible solutions that are incomparable among each other. The goal of this work is to investigate mechanisms that enable automated decision making between such multi-dimensional solutions. To this end, we investigate techniques from the domain of multi-attribute decision making that aggregate the performance of placements to a single numeric score. A comparison between resulting rankings of placements shows that many techniques produce similar results. Hence, placements that achieve good rankings according to many approaches might be viable candidates in the context of automated decision making. In order to illustrate the functionality of the different scoring mechanisms, we perform a case study on a single network graph and a fixed number of objectives and service instances. Additionally, we present aggregated results from broad evaluations on the Internet Topology Zoo and a larger number of objectives as well as varying numbers of service instances. These allow making more reliable statements about the mechanisms' performance and agreement.
Server and Content Selection for MPEG DASH Video Streaming with Client Information. Wamser, Florian; Höfner, Steffen; Seufert, Michael; Tran-Gia, Phuoc. In ACM SIGCOMM Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE). Los Angeles, CA, USA, 2017.
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In HTTP adaptive streaming (HAS), such as MPEG DASH, the video is split into chunks and is available in different quality levels. If the video chunks are stored or cached on different servers to deal with the high load in the network and the Quality of Experience (QoE) requirements of the users, the problem of content selection arises. In this paper, we evaluate client-side algorithms for dynamically selecting an appropriate content server during DASH video streaming. We present three algorithms with which the DASH client itself can determine the most appropriate server based on client-specific metrics, like actual latency or bandwidth to the content servers. We evaluate and discuss the proposed algorithms with respect to the resulting DASH streaming behavior in terms of buffer levels and quality level selection.

@inproceedings{info3-article-2017-3, abstract = {In HTTP adaptive streaming (HAS), such as MPEG DASH, the video is split into chunks and is available in different quality levels. If the video chunks are stored or cached on different servers to deal with the high load in the network and the Quality of Experience (QoE) requirements of the users, the problem of content selection arises. In this paper, we evaluate client-side algorithms for dynamically selecting an appropriate content server during DASH video streaming. We present three algorithms with which the DASH client itself can determine the most appropriate server based on client-specific metrics, like actual latency or bandwidth to the content servers. We evaluate and discuss the proposed algorithms with respect to the resulting DASH streaming behavior in terms of buffer levels and quality level selection.}, address = {Los Angeles, CA, USA}, author = {Wamser, Florian and Höfner, Steffen and Seufert, Michael and Tran-Gia, Phuoc}, booktitle = {ACM SIGCOMM Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE)}, keywords = {can}, month = {08}, title = {Server and Content Selection for MPEG DASH Video Streaming with Client Information}, year = 2017 }

%0 Conference Paper %1 info3-article-2017-3 %A Wamser, Florian %A Höfner, Steffen %A Seufert, Michael %A Tran-Gia, Phuoc %B ACM SIGCOMM Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE) %C Los Angeles, CA, USA %D 2017 %T Server and Content Selection for MPEG DASH Video Streaming with Client Information %X In HTTP adaptive streaming (HAS), such as MPEG DASH, the video is split into chunks and is available in different quality levels. If the video chunks are stored or cached on different servers to deal with the high load in the network and the Quality of Experience (QoE) requirements of the users, the problem of content selection arises. In this paper, we evaluate client-side algorithms for dynamically selecting an appropriate content server during DASH video streaming. We present three algorithms with which the DASH client itself can determine the most appropriate server based on client-specific metrics, like actual latency or bandwidth to the content servers. We evaluate and discuss the proposed algorithms with respect to the resulting DASH streaming behavior in terms of buffer levels and quality level selection.
EdgeNetworkCloudSim: Placement of Service Chains in Edge Clouds Using NetworkCloudSim. Seufert, Michael; Kamneng Kwam, Brice; Wamser, Florian; Tran-Gia, Phuoc. In 1st IEEE International Workshop on Network Programmability - From the Data Center to the Ground (NetFoG). Bologna, Italy, 2017.
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Edge cloud computing is a trending paradigm, which extends cloud computing by additionally utilizing computing resources at the network edge, e.g., at mobile base stations. Especially personalized services can be instantiated or migrated close to end users, which improves the latency and supports user mobility. However, the placement of the service chains is crucial for the performance of the services and the energy consumption of the edge cloud platform, and appropriate algorithms have to be designed. To support the simulative performance evaluation of such algorithms, EdgeNetworkCloudSim was developed. It is an extension of NetworkCloudSim, and allows to simulate and evaluate the orchestration and consolidation of service chains in an edge network cloud.

@inproceedings{info3-inproceedings-2017-12, abstract = {Edge cloud computing is a trending paradigm, which extends cloud computing by additionally utilizing computing resources at the network edge, e.g., at mobile base stations. Especially personalized services can be instantiated or migrated close to end users, which improves the latency and supports user mobility. However, the placement of the service chains is crucial for the performance of the services and the energy consumption of the edge cloud platform, and appropriate algorithms have to be designed. To support the simulative performance evaluation of such algorithms, EdgeNetworkCloudSim was developed. It is an extension of NetworkCloudSim, and allows to simulate and evaluate the orchestration and consolidation of service chains in an edge network cloud.}, address = {Bologna, Italy}, author = {Seufert, Michael and Kamneng Kwam, Brice and Wamser, Florian and Tran-Gia, Phuoc}, booktitle = {1st IEEE International Workshop on Network Programmability - From the Data Center to the Ground (NetFoG)}, keywords = {can}, month = {07}, title = {EdgeNetworkCloudSim: Placement of Service Chains in Edge Clouds Using NetworkCloudSim}, year = 2017 }

%0 Conference Paper %1 info3-inproceedings-2017-12 %A Seufert, Michael %A Kamneng Kwam, Brice %A Wamser, Florian %A Tran-Gia, Phuoc %B 1st IEEE International Workshop on Network Programmability - From the Data Center to the Ground (NetFoG) %C Bologna, Italy %D 2017 %T EdgeNetworkCloudSim: Placement of Service Chains in Edge Clouds Using NetworkCloudSim %X Edge cloud computing is a trending paradigm, which extends cloud computing by additionally utilizing computing resources at the network edge, e.g., at mobile base stations. Especially personalized services can be instantiated or migrated close to end users, which improves the latency and supports user mobility. However, the placement of the service chains is crucial for the performance of the services and the energy consumption of the edge cloud platform, and appropriate algorithms have to be designed. To support the simulative performance evaluation of such algorithms, EdgeNetworkCloudSim was developed. It is an extension of NetworkCloudSim, and allows to simulate and evaluate the orchestration and consolidation of service chains in an edge network cloud.
Concept and Implementation of Video QoE Measurements in a Mobile Broadband Testbed. Schwind, Anika; Seufert, Michael; Alay, Özgü; Casas, Pedro; Tran-Gia, Phuoc; Wamser, Florian. In IEEE/IFIP Workshop on Mobile Network Measurement (MNM’17). Dublin, Ireland, 2017.
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The MONROE testbed enables the objective performance assessment of MBB networks from the end-user perspective, using highly distributed measurements from fixed and mobile nodes. To quantify the performance of MBB networks for popular Internet services from a user-centric perspective, dedicated tools are needed. In this paper we extend the MONROE testbed to the Quality of Experience (QoE) domain, presenting the design and implementation of a QoE-capable measurement tool for YouTube video streaming. The measurement concept is based on emulating a virtual end-user device requesting video streams, which are then monitored at the network and application layers, on the basis of QoE-relevant features. The initial measurements conducted in the MONROE testbed and reported in this paper demonstrate the applicability of the implemented measurement concept.

@inproceedings{info3-inproceedings-2017-15, abstract = {The MONROE testbed enables the objective performance assessment of MBB networks from the end-user perspective, using highly distributed measurements from fixed and mobile nodes. To quantify the performance of MBB networks for popular Internet services from a user-centric perspective, dedicated tools are needed. In this paper we extend the MONROE testbed to the Quality of Experience (QoE) domain, presenting the design and implementation of a QoE-capable measurement tool for YouTube video streaming. The measurement concept is based on emulating a virtual end-user device requesting video streams, which are then monitored at the network and application layers, on the basis of QoE-relevant features. The initial measurements conducted in the MONROE testbed and reported in this paper demonstrate the applicability of the implemented measurement concept.}, address = {Dublin, Ireland}, author = {Schwind, Anika and Seufert, Michael and Alay, Özgü and Casas, Pedro and Tran-Gia, Phuoc and Wamser, Florian}, booktitle = {IEEE/IFIP Workshop on Mobile Network Measurement (MNM’17)}, keywords = {can}, month = {06}, title = {Concept and Implementation of Video QoE Measurements in a Mobile Broadband Testbed}, year = 2017 }

%0 Conference Paper %1 info3-inproceedings-2017-15 %A Schwind, Anika %A Seufert, Michael %A Alay, Özgü %A Casas, Pedro %A Tran-Gia, Phuoc %A Wamser, Florian %B IEEE/IFIP Workshop on Mobile Network Measurement (MNM’17) %C Dublin, Ireland %D 2017 %T Concept and Implementation of Video QoE Measurements in a Mobile Broadband Testbed %X The MONROE testbed enables the objective performance assessment of MBB networks from the end-user perspective, using highly distributed measurements from fixed and mobile nodes. To quantify the performance of MBB networks for popular Internet services from a user-centric perspective, dedicated tools are needed. In this paper we extend the MONROE testbed to the Quality of Experience (QoE) domain, presenting the design and implementation of a QoE-capable measurement tool for YouTube video streaming. The measurement concept is based on emulating a virtual end-user device requesting video streams, which are then monitored at the network and application layers, on the basis of QoE-relevant features. The initial measurements conducted in the MONROE testbed and reported in this paper demonstrate the applicability of the implemented measurement concept.
Study on the Accuracy of QoE Monitoring for HTTP Adaptive Video Streaming Using VNF. Dinh-Xuan, Lam; Seufert, Michael; Wamser, Florian; Tran-Gia, Phuoc. In 1st IFIP/IEEE International Workshop on Quality of Experience Management (QoE-Management). Lisbon, Portugal, 2017.
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The fast growth of HTTP video streaming is responsible for a huge amount of traffic over the past few years. Due to the variety and popularity of video content, more and more people are watching videos on the smart TV or on mobile devices. As a result, a potential market is emerging for video providers, which can significantly increase their revenues. In order to offer users a good experience, adaptive video streaming has been introduced to adapt the video quality to the network conditions. Nevertheless, it is still difficult for the network operators to assess the actual video quality on the device of the users and therefore they can not react to improve the service on the network. In this work, we propose a Virtual Network Function (VNF) to monitor the Quality of Experience (QoE) for online video service in the network. To conduct the study, on the one hand, we design a VNF monitoring to measure the video quality and estimate the QoE at the client machine. Our function is placed in two locations nearby and far away from the user to analyze the impact of geographical placement of the VNF on its performance. On the other hand, we set up a local testbed to examine the functional operation and measure the actual video buffer from a client web browser directly to validate the accuracy of the function. Our findings show that with respect to function placement, the VNF has high accuracy in estimating the QoE if it is deployed at the edge network close to the user. However, the VNF does not perform well when it operates far away from the users, e.g., at data centers. These insights help network vendors to more closely monitor the quality of the videos streamed to their customers.

@inproceedings{info3-inproceedings-2017-3, abstract = {The fast growth of HTTP video streaming is responsible for a huge amount of traffic over the past few years. Due to the variety and popularity of video content, more and more people are watching videos on the smart TV or on mobile devices. As a result, a potential market is emerging for video providers, which can significantly increase their revenues. In order to offer users a good experience, adaptive video streaming has been introduced to adapt the video quality to the network conditions. Nevertheless, it is still difficult for the network operators to assess the actual video quality on the device of the users and therefore they can not react to improve the service on the network. In this work, we propose a Virtual Network Function (VNF) to monitor the Quality of Experience (QoE) for online video service in the network. To conduct the study, on the one hand, we design a VNF monitoring to measure the video quality and estimate the QoE at the client machine. Our function is placed in two locations nearby and far away from the user to analyze the impact of geographical placement of the VNF on its performance. On the other hand, we set up a local testbed to examine the functional operation and measure the actual video buffer from a client web browser directly to validate the accuracy of the function. Our findings show that with respect to function placement, the VNF has high accuracy in estimating the QoE if it is deployed at the edge network close to the user. However, the VNF does not perform well when it operates far away from the users, e.g., at data centers. These insights help network vendors to more closely monitor the quality of the videos streamed to their customers.}, address = {Lisbon, Portugal}, author = {Dinh-Xuan, Lam and Seufert, Michael and Wamser, Florian and Tran-Gia, Phuoc}, booktitle = {1st IFIP/IEEE International Workshop on Quality of Experience Management (QoE-Management)}, keywords = {can}, month = {05}, title = {Study on the Accuracy of QoE Monitoring for HTTP Adaptive Video Streaming Using VNF}, year = 2017 }

%0 Conference Paper %1 info3-inproceedings-2017-3 %A Dinh-Xuan, Lam %A Seufert, Michael %A Wamser, Florian %A Tran-Gia, Phuoc %B 1st IFIP/IEEE International Workshop on Quality of Experience Management (QoE-Management) %C Lisbon, Portugal %D 2017 %T Study on the Accuracy of QoE Monitoring for HTTP Adaptive Video Streaming Using VNF %X The fast growth of HTTP video streaming is responsible for a huge amount of traffic over the past few years. Due to the variety and popularity of video content, more and more people are watching videos on the smart TV or on mobile devices. As a result, a potential market is emerging for video providers, which can significantly increase their revenues. In order to offer users a good experience, adaptive video streaming has been introduced to adapt the video quality to the network conditions. Nevertheless, it is still difficult for the network operators to assess the actual video quality on the device of the users and therefore they can not react to improve the service on the network. In this work, we propose a Virtual Network Function (VNF) to monitor the Quality of Experience (QoE) for online video service in the network. To conduct the study, on the one hand, we design a VNF monitoring to measure the video quality and estimate the QoE at the client machine. Our function is placed in two locations nearby and far away from the user to analyze the impact of geographical placement of the VNF on its performance. On the other hand, we set up a local testbed to examine the functional operation and measure the actual video buffer from a client web browser directly to validate the accuracy of the function. Our findings show that with respect to function placement, the VNF has high accuracy in estimating the QoE if it is deployed at the edge network close to the user. However, the VNF does not perform well when it operates far away from the users, e.g., at data centers. These insights help network vendors to more closely monitor the quality of the videos streamed to their customers.
Unsupervised QoE Field Study for Mobile YouTube Video Streaming with YoMoApp. Seufert, Michael; Wehner, Nikolas; Wamser, Florian; Casas, Pedro; D’Alconzo, Alessandro; Tran-Gia, Phuoc. In 9th International Conference on Quality of Multimedia Experience (QoMEX). Erfurt, Germany, 2017.
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YoMoApp (YouTube Monitoring App) is an Android app to monitor mobile YouTube video streaming on both application- and network-layer. Additionally, it allows to collect subjective Quality of Experience (QoE) feedback of end users. During the development of the app, the stable versions of YoMoApp were already available in the Google Play Store, and the app was downloaded, installed, and used on many devices to monitor streaming sessions. As the app was not advertised in special campaigns or used for dedicated QoE studies, the monitored streaming sessions of this period compose the data set of a large unsupervised field study. The collected data set is evaluated to characterize current mobile YouTube streaming on both application and network layers. Furthermore, the problems and methodology to obtain QoE results from such unsupervised field study are discussed together with the actual QoE results. Correlations between QoE factors are investigated, and the QoE of clusters of similar streaming sessions is analyzed.

@inproceedings{info3-inproceedings-2017-9, abstract = {YoMoApp (YouTube Monitoring App) is an Android app to monitor mobile YouTube video streaming on both application- and network-layer. Additionally, it allows to collect subjective Quality of Experience (QoE) feedback of end users. During the development of the app, the stable versions of YoMoApp were already available in the Google Play Store, and the app was downloaded, installed, and used on many devices to monitor streaming sessions. As the app was not advertised in special campaigns or used for dedicated QoE studies, the monitored streaming sessions of this period compose the data set of a large unsupervised field study. The collected data set is evaluated to characterize current mobile YouTube streaming on both application and network layers. Furthermore, the problems and methodology to obtain QoE results from such unsupervised field study are discussed together with the actual QoE results. Correlations between QoE factors are investigated, and the QoE of clusters of similar streaming sessions is analyzed.}, address = {Erfurt, Germany}, author = {Seufert, Michael and Wehner, Nikolas and Wamser, Florian and Casas, Pedro and D'Alconzo, Alessandro and Tran-Gia, Phuoc}, booktitle = {9th International Conference on Quality of Multimedia Experience (QoMEX)}, keywords = {can}, month = {05}, title = {Unsupervised QoE Field Study for Mobile YouTube Video Streaming with YoMoApp}, year = 2017 }

%0 Conference Paper %1 info3-inproceedings-2017-9 %A Seufert, Michael %A Wehner, Nikolas %A Wamser, Florian %A Casas, Pedro %A D'Alconzo, Alessandro %A Tran-Gia, Phuoc %B 9th International Conference on Quality of Multimedia Experience (QoMEX) %C Erfurt, Germany %D 2017 %T Unsupervised QoE Field Study for Mobile YouTube Video Streaming with YoMoApp %X YoMoApp (YouTube Monitoring App) is an Android app to monitor mobile YouTube video streaming on both application- and network-layer. Additionally, it allows to collect subjective Quality of Experience (QoE) feedback of end users. During the development of the app, the stable versions of YoMoApp were already available in the Google Play Store, and the app was downloaded, installed, and used on many devices to monitor streaming sessions. As the app was not advertised in special campaigns or used for dedicated QoE studies, the monitored streaming sessions of this period compose the data set of a large unsupervised field study. The collected data set is evaluated to characterize current mobile YouTube streaming on both application and network layers. Furthermore, the problems and methodology to obtain QoE results from such unsupervised field study are discussed together with the actual QoE results. Correlations between QoE factors are investigated, and the QoE of clusters of similar streaming sessions is analyzed.
An Approximation of the Backhaul Bandwidth Aggregation Potential Using a Partial Sharing Scheme. Burger, Valentin; Seufert, Michael; Zinner, Thomas; Tran-Gia, Phuoc. In 15th IFIP/IEEE International Symposium on Integrated Network Management (IM). Lisbon, Portugal, 2017.
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To cope with the increasing demands of mobile devices and the limited capacity of cellular networks, mobile connections are offloaded to WiFi. The access capacity is further increased by aggregating backhaul bandwidth of WiFi access links. To analyze the performance of aggregated access links we develop a model for two and more cooperating systems sharing capacities using an offloading scheme. The state probabilities of the different cooperating systems in the analytic model are determined by a fixed point iterative procedure. By investigating an inner and outer composite system we are able to analyze the system in imbalanced load conditions where the system reaches its full potential utilizing spare bandwidth. To evaluate the robustness of the system against users that try to exploit the system, the bandwidth received by prioritized users is quantified.

@inproceedings{info3-inproceedings-2017-1, abstract = {To cope with the increasing demands of mobile devices and the limited capacity of cellular networks, mobile connections are offloaded to WiFi. The access capacity is further increased by aggregating backhaul bandwidth of WiFi access links. To analyze the performance of aggregated access links we develop a model for two and more cooperating systems sharing capacities using an offloading scheme. The state probabilities of the different cooperating systems in the analytic model are determined by a fixed point iterative procedure. By investigating an inner and outer composite system we are able to analyze the system in imbalanced load conditions where the system reaches its full potential utilizing spare bandwidth. To evaluate the robustness of the system against users that try to exploit the system, the bandwidth received by prioritized users is quantified.}, address = {Lisbon, Portugal}, author = {Burger, Valentin and Seufert, Michael and Zinner, Thomas and Tran-Gia, Phuoc}, booktitle = {15th IFIP/IEEE International Symposium on Integrated Network Management (IM)}, keywords = {can}, month = {05}, title = {An Approximation of the Backhaul Bandwidth Aggregation Potential Using a Partial Sharing Scheme}, year = 2017 }

%0 Conference Paper %1 info3-inproceedings-2017-1 %A Burger, Valentin %A Seufert, Michael %A Zinner, Thomas %A Tran-Gia, Phuoc %B 15th IFIP/IEEE International Symposium on Integrated Network Management (IM) %C Lisbon, Portugal %D 2017 %T An Approximation of the Backhaul Bandwidth Aggregation Potential Using a Partial Sharing Scheme %X To cope with the increasing demands of mobile devices and the limited capacity of cellular networks, mobile connections are offloaded to WiFi. The access capacity is further increased by aggregating backhaul bandwidth of WiFi access links. To analyze the performance of aggregated access links we develop a model for two and more cooperating systems sharing capacities using an offloading scheme. The state probabilities of the different cooperating systems in the analytic model are determined by a fixed point iterative procedure. By investigating an inner and outer composite system we are able to analyze the system in imbalanced load conditions where the system reaches its full potential utilizing spare bandwidth. To evaluate the robustness of the system against users that try to exploit the system, the bandwidth received by prioritized users is quantified.
Unperturbed Video Streaming QoE Under Web Page Related Context Factors. Seufert, Michael; Zach, Ondrej; Slanina, Martin; Tran-Gia, Phuoc. In 9th International Conference on Quality of Multimedia Experience (QoMEX). Erfurt, Germany, 2017.
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Quality of Experience (QoE) of Internet services is affected by human, system, and context influence factors. While most QoE studies so far are focused on system factors only, this work will assess the impact of context factors of video streaming on QoE. As video streaming is mostly consumed from web pages, such as video portals, the investigated test conditions are applied to the web page, which embeds the video player. Therefore, the study of context factors is implicitly conducted within a crowdsourced QoE study. The test conditions considered different page load times, poster image qualities, and displayed advertisements on the web page, which are typical context factors when consuming a video streaming service. The results of the study show that the modification of the context factors on the streaming web page leaves the users' QoE rating unperturbed, which suggests that the investigated context factors have a negligible impact on video streaming QoE, or that the rating task of the subjective QoE study superimposed the context factors.

@inproceedings{info3-inproceedings-2017-11, abstract = {Quality of Experience (QoE) of Internet services is affected by human, system, and context influence factors. While most QoE studies so far are focused on system factors only, this work will assess the impact of context factors of video streaming on QoE. As video streaming is mostly consumed from web pages, such as video portals, the investigated test conditions are applied to the web page, which embeds the video player. Therefore, the study of context factors is implicitly conducted within a crowdsourced QoE study. The test conditions considered different page load times, poster image qualities, and displayed advertisements on the web page, which are typical context factors when consuming a video streaming service. The results of the study show that the modification of the context factors on the streaming web page leaves the users' QoE rating unperturbed, which suggests that the investigated context factors have a negligible impact on video streaming QoE, or that the rating task of the subjective QoE study superimposed the context factors.}, address = {Erfurt, Germany}, author = {Seufert, Michael and Zach, Ondrej and Slanina, Martin and Tran-Gia, Phuoc}, booktitle = {9th International Conference on Quality of Multimedia Experience (QoMEX)}, keywords = {can}, month = {05}, title = {Unperturbed Video Streaming QoE Under Web Page Related Context Factors}, year = 2017 }

%0 Conference Paper %1 info3-inproceedings-2017-11 %A Seufert, Michael %A Zach, Ondrej %A Slanina, Martin %A Tran-Gia, Phuoc %B 9th International Conference on Quality of Multimedia Experience (QoMEX) %C Erfurt, Germany %D 2017 %T Unperturbed Video Streaming QoE Under Web Page Related Context Factors %X Quality of Experience (QoE) of Internet services is affected by human, system, and context influence factors. While most QoE studies so far are focused on system factors only, this work will assess the impact of context factors of video streaming on QoE. As video streaming is mostly consumed from web pages, such as video portals, the investigated test conditions are applied to the web page, which embeds the video player. Therefore, the study of context factors is implicitly conducted within a crowdsourced QoE study. The test conditions considered different page load times, poster image qualities, and displayed advertisements on the web page, which are typical context factors when consuming a video streaming service. The results of the study show that the modification of the context factors on the streaming web page leaves the users' QoE rating unperturbed, which suggests that the investigated context factors have a negligible impact on video streaming QoE, or that the rating task of the subjective QoE study superimposed the context factors.
Predicting QoE in Cellular Networks using Machine Learning and in-Smartphone Measurements. Casas, Pedro; D’Alconzo, Alessandro; Wamser, Florian; Seufert, Michael; Gardlo, Bruno; Schwind, Anika; Tran-Gia, Phuoc; Schatz, Raimund. In 9th International Conference on Quality of Multimedia Experience (QoMEX). Erfurt, Germany, 2017.
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Monitoring the Quality of Experience (QoE) undergone by cellular network customers has become paramount for cellular ISPs, who need to ensure high quality levels to limit customer churn due to quality dissatisfaction. This paper tackles the problem of QoE monitoring, assessment and prediction in cellular networks, relying on end-user device (i.e., smartphone) QoS passive traffic measurements and QoE crowdsourced feedback. We conceive different QoE assessment models based on supervised machine learning techniques, which are capable to predict the QoE experienced by the end user of popular smartphone apps (e.g., YouTube and Facebook), using as input the passive in-device measurements. Using a rich QoE dataset derived from field trials in operational cellular networks, we benchmark the performance of multiple machine learning based predictors, and construct a decision-tree based model which is capable to predict the per-user overall experience and service acceptability with a success rate of 91% and 98% respectively. To the best of our knowledge, this is the first paper using end-user, in-device passive measurements and machine learning models to predict the QoE of smartphone users in operational cellular networks.

@inproceedings{info3-inproceedings-2017-10, abstract = {Monitoring the Quality of Experience (QoE) undergone by cellular network customers has become paramount for cellular ISPs, who need to ensure high quality levels to limit customer churn due to quality dissatisfaction. This paper tackles the problem of QoE monitoring, assessment and prediction in cellular networks, relying on end-user device (i.e., smartphone) QoS passive traffic measurements and QoE crowdsourced feedback. We conceive different QoE assessment models based on supervised machine learning techniques, which are capable to predict the QoE experienced by the end user of popular smartphone apps (e.g., YouTube and Facebook), using as input the passive in-device measurements. Using a rich QoE dataset derived from field trials in operational cellular networks, we benchmark the performance of multiple machine learning based predictors, and construct a decision-tree based model which is capable to predict the per-user overall experience and service acceptability with a success rate of 91% and 98% respectively. To the best of our knowledge, this is the first paper using end-user, in-device passive measurements and machine learning models to predict the QoE of smartphone users in operational cellular networks.}, address = {Erfurt, Germany}, author = {Casas, Pedro and D'Alconzo, Alessandro and Wamser, Florian and Seufert, Michael and Gardlo, Bruno and Schwind, Anika and Tran-Gia, Phuoc and Schatz, Raimund}, booktitle = {9th International Conference on Quality of Multimedia Experience (QoMEX)}, keywords = {can}, month = {05}, title = {Predicting QoE in Cellular Networks using Machine Learning and in-Smartphone Measurements}, year = 2017 }

%0 Conference Paper %1 info3-inproceedings-2017-10 %A Casas, Pedro %A D'Alconzo, Alessandro %A Wamser, Florian %A Seufert, Michael %A Gardlo, Bruno %A Schwind, Anika %A Tran-Gia, Phuoc %A Schatz, Raimund %B 9th International Conference on Quality of Multimedia Experience (QoMEX) %C Erfurt, Germany %D 2017 %T Predicting QoE in Cellular Networks using Machine Learning and in-Smartphone Measurements %X Monitoring the Quality of Experience (QoE) undergone by cellular network customers has become paramount for cellular ISPs, who need to ensure high quality levels to limit customer churn due to quality dissatisfaction. This paper tackles the problem of QoE monitoring, assessment and prediction in cellular networks, relying on end-user device (i.e., smartphone) QoS passive traffic measurements and QoE crowdsourced feedback. We conceive different QoE assessment models based on supervised machine learning techniques, which are capable to predict the QoE experienced by the end user of popular smartphone apps (e.g., YouTube and Facebook), using as input the passive in-device measurements. Using a rich QoE dataset derived from field trials in operational cellular networks, we benchmark the performance of multiple machine learning based predictors, and construct a decision-tree based model which is capable to predict the per-user overall experience and service acceptability with a success rate of 91% and 98% respectively. To the best of our knowledge, this is the first paper using end-user, in-device passive measurements and machine learning models to predict the QoE of smartphone users in operational cellular networks.
On Use of Crowdsourcing for H.264/AVC and H.265/HEVC Video Quality Evaluation. Zach, Ondrej; Seufert, Michael; Hirth, Matthias; Slanina, Martin; Tran-Gia, Phuoc. In Radioelektronika. Brno, Czech Republic, 2017.
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Crowdsourcing has become a popular method in the field of video quality evaluation. Gathering the opinion of the users using crowdsourcing is quick and relatively cheap but such a study has to be designed very carefully in order to give relevant results. So far, the majority of the QoE studies using crowdsourcing has been focusing on the performance of H.264/AVC algorithm in different situations (such as encoder settings, stalling effects, etc). Modern video coding methods, however, are only rarely tested using the crowdsourcing approach. We designed a study comparing the performance of both H.264/AVC and H.265/HEVC standards in the crowdsourcing environment. We deal with the possibilities of delivering and presenting the HEVC encoded content to the participants of the crowdsourcing study and potential challenges. Finally, the study was performed using Microworkers platform and gathered results are then compared with three different objective video quality metrics.

@inproceedings{info3-inproceedings-2017-7, abstract = {Crowdsourcing has become a popular method in the field of video quality evaluation. Gathering the opinion of the users using crowdsourcing is quick and relatively cheap but such a study has to be designed very carefully in order to give relevant results. So far, the majority of the QoE studies using crowdsourcing has been focusing on the performance of H.264/AVC algorithm in different situations (such as encoder settings, stalling effects, etc). Modern video coding methods, however, are only rarely tested using the crowdsourcing approach. We designed a study comparing the performance of both H.264/AVC and H.265/HEVC standards in the crowdsourcing environment. We deal with the possibilities of delivering and presenting the HEVC encoded content to the participants of the crowdsourcing study and potential challenges. Finally, the study was performed using Microworkers platform and gathered results are then compared with three different objective video quality metrics.}, address = {Brno, Czech Republic}, author = {Zach, Ondrej and Seufert, Michael and Hirth, Matthias and Slanina, Martin and Tran-Gia, Phuoc}, booktitle = {Radioelektronika}, keywords = {can}, month = {04}, title = {On Use of Crowdsourcing for H.264/AVC and H.265/HEVC Video Quality Evaluation}, year = 2017 }

%0 Conference Paper %1 info3-inproceedings-2017-7 %A Zach, Ondrej %A Seufert, Michael %A Hirth, Matthias %A Slanina, Martin %A Tran-Gia, Phuoc %B Radioelektronika %C Brno, Czech Republic %D 2017 %T On Use of Crowdsourcing for H.264/AVC and H.265/HEVC Video Quality Evaluation %X Crowdsourcing has become a popular method in the field of video quality evaluation. Gathering the opinion of the users using crowdsourcing is quick and relatively cheap but such a study has to be designed very carefully in order to give relevant results. So far, the majority of the QoE studies using crowdsourcing has been focusing on the performance of H.264/AVC algorithm in different situations (such as encoder settings, stalling effects, etc). Modern video coding methods, however, are only rarely tested using the crowdsourcing approach. We designed a study comparing the performance of both H.264/AVC and H.265/HEVC standards in the crowdsourcing environment. We deal with the possibilities of delivering and presenting the HEVC encoded content to the participants of the crowdsourcing study and potential challenges. Finally, the study was performed using Microworkers platform and gathered results are then compared with three different objective video quality metrics.
Evaluating the Impact of WiFi Offloading on Mobile Users of HTTP Adaptive Video Streaming. Seufert, Michael; Burger, Valentin; Kaup, Fabian. In 5th IEEE International Workshop on Quality of Experience for Multimedia Communications (QoEMC). Washington, DC, USA, 2016.
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In a recent trend to lessen the load on cellular networks in cities, users are offered to offload mobile connections to lower cost WiFi networks. In this work, we conduct a simulative performance evaluation of the impact of WiFi offloading for a mobile end user of a HTTP adaptive video streaming (HAS) service depending on availability and range of the WiFi hotspots. The simulation is based on connectivity measurements from a German city and evaluates the key performance indicators for the QoE of HAS, i.e., initial delay, stalling, and quality adaptation. Additionally, a smartphone energy model is applied to assess the energy consumption during the streaming. The results indicate that WiFi offloading of HAS connections to public WiFi hotspots is not attractive for end users both in terms of QoE and energy consumption. However, it can be shown that WiFi offloading can be beneficial also for end users in case high bandwidths can be received via WiFi.

@inproceedings{info3-inproceedings-2016-18, abstract = {In a recent trend to lessen the load on cellular networks in cities, users are offered to offload mobile connections to lower cost WiFi networks. In this work, we conduct a simulative performance evaluation of the impact of WiFi offloading for a mobile end user of a HTTP adaptive video streaming (HAS) service depending on availability and range of the WiFi hotspots. The simulation is based on connectivity measurements from a German city and evaluates the key performance indicators for the QoE of HAS, i.e., initial delay, stalling, and quality adaptation. Additionally, a smartphone energy model is applied to assess the energy consumption during the streaming. The results indicate that WiFi offloading of HAS connections to public WiFi hotspots is not attractive for end users both in terms of QoE and energy consumption. However, it can be shown that WiFi offloading can be beneficial also for end users in case high bandwidths can be received via WiFi.}, address = {Washington, DC, USA}, author = {Seufert, Michael and Burger, Valentin and Kaup, Fabian}, booktitle = {5th IEEE International Workshop on Quality of Experience for Multimedia Communications (QoEMC)}, keywords = {can}, month = 12, title = {Evaluating the Impact of WiFi Offloading on Mobile Users of HTTP Adaptive Video Streaming}, year = 2016 }

%0 Conference Paper %1 info3-inproceedings-2016-18 %A Seufert, Michael %A Burger, Valentin %A Kaup, Fabian %B 5th IEEE International Workshop on Quality of Experience for Multimedia Communications (QoEMC) %C Washington, DC, USA %D 2016 %T Evaluating the Impact of WiFi Offloading on Mobile Users of HTTP Adaptive Video Streaming %X In a recent trend to lessen the load on cellular networks in cities, users are offered to offload mobile connections to lower cost WiFi networks. In this work, we conduct a simulative performance evaluation of the impact of WiFi offloading for a mobile end user of a HTTP adaptive video streaming (HAS) service depending on availability and range of the WiFi hotspots. The simulation is based on connectivity measurements from a German city and evaluates the key performance indicators for the QoE of HAS, i.e., initial delay, stalling, and quality adaptation. Additionally, a smartphone energy model is applied to assess the energy consumption during the streaming. The results indicate that WiFi offloading of HAS connections to public WiFi hotspots is not attractive for end users both in terms of QoE and energy consumption. However, it can be shown that WiFi offloading can be beneficial also for end users in case high bandwidths can be received via WiFi.
Analytic Model for SDN Controller Traffic and Switch Table Occupancy. Metter, Christopher; Seufert, Michael; Wamser, Florian; Zinner, Thomas; Tran-Gia, Phuoc. In 12th International Conference on Network and Service Management (CNSM). Best Paper Award, Montreal, Canada, 2016.
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Software Defined Networking (SDN) is a major paradigm in the field of current communication networks. SDN is used as the basis of many new networks although few performance models are available in the literature, and the majority of performance evaluations are based primarily on practical measurements. To fill this gap, we develop an analytical model to assess SDN control plane traffic as well as the occupancy of the flow table of an SDN switch. The contribution of this work is the formulation of the model for the performance-decisive parameters control-plane traffic and flow table occupancy and the application of the model for different data plane traffic characteristics. In the end, there is a discussion about the setting of time-out values for storing flow entries in the switch flow table depending on the traffic characteristics in the data plane. The trade-off between the signaling traffic in the control plane and the occupancy of the flow table is discussed in order to minimize both.

@inproceedings{info3-inproceedings-2016-17, abstract = {Software Defined Networking (SDN) is a major paradigm in the field of current communication networks. SDN is used as the basis of many new networks although few performance models are available in the literature, and the majority of performance evaluations are based primarily on practical measurements. To fill this gap, we develop an analytical model to assess SDN control plane traffic as well as the occupancy of the flow table of an SDN switch. The contribution of this work is the formulation of the model for the performance-decisive parameters control-plane traffic and flow table occupancy and the application of the model for different data plane traffic characteristics. In the end, there is a discussion about the setting of time-out values for storing flow entries in the switch flow table depending on the traffic characteristics in the data plane. The trade-off between the signaling traffic in the control plane and the occupancy of the flow table is discussed in order to minimize both.}, address = {Best Paper Award, Montreal, Canada}, author = {Metter, Christopher and Seufert, Michael and Wamser, Florian and Zinner, Thomas and Tran-Gia, Phuoc}, booktitle = {12th International Conference on Network and Service Management (CNSM)}, keywords = {can}, month = 10, title = {Analytic Model for SDN Controller Traffic and Switch Table Occupancy}, year = 2016 }

%0 Conference Paper %1 info3-inproceedings-2016-17 %A Metter, Christopher %A Seufert, Michael %A Wamser, Florian %A Zinner, Thomas %A Tran-Gia, Phuoc %B 12th International Conference on Network and Service Management (CNSM) %C Best Paper Award, Montreal, Canada %D 2016 %T Analytic Model for SDN Controller Traffic and Switch Table Occupancy %X Software Defined Networking (SDN) is a major paradigm in the field of current communication networks. SDN is used as the basis of many new networks although few performance models are available in the literature, and the majority of performance evaluations are based primarily on practical measurements. To fill this gap, we develop an analytical model to assess SDN control plane traffic as well as the occupancy of the flow table of an SDN switch. The contribution of this work is the formulation of the model for the performance-decisive parameters control-plane traffic and flow table occupancy and the application of the model for different data plane traffic characteristics. In the end, there is a discussion about the setting of time-out values for storing flow entries in the switch flow table depending on the traffic characteristics in the data plane. The trade-off between the signaling traffic in the control plane and the occupancy of the flow table is discussed in order to minimize both.
Automated Decision Making Methods for the Multi-objective Optimization Task of Cloud Service Placement. Seufert, Michael; Lange, Stanislav; Meixner, Markus. In 1st International Workshop on Programmability for Cloud Networks and Applications (PROCON). Würzburg, Germany, 2016.
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The network functions virtualization (NFV) paradigm provides advantages with respect to aspects like flexibility, costs, and scalability of networks. However, management and orchestration of the resulting networks also introduce new challenges. The placement of services and virtualized network functions (VNFs) is a multi-objective optimization task that confronts operators with a multitude of possible solutions that are incomparable among each other. The goal of this work is to investigate mechanisms that enable automated decision making between such multi dimensional solutions. To this end, we investigate techniques from the domain of multi attribute decision making that aggregate the performance of placements to a single numeric score. A comparison between resulting rankings of placements shows that many techniques produce similar results. Hence, placements that achieve good rankings according to many approaches might be viable candidates in the context of automated decision making.

@inproceedings{info3-inproceedings-2016-12, abstract = {The network functions virtualization (NFV) paradigm provides advantages with respect to aspects like flexibility, costs, and scalability of networks. However, management and orchestration of the resulting networks also introduce new challenges. The placement of services and virtualized network functions (VNFs) is a multi-objective optimization task that confronts operators with a multitude of possible solutions that are incomparable among each other. The goal of this work is to investigate mechanisms that enable automated decision making between such multi dimensional solutions. To this end, we investigate techniques from the domain of multi attribute decision making that aggregate the performance of placements to a single numeric score. A comparison between resulting rankings of placements shows that many techniques produce similar results. Hence, placements that achieve good rankings according to many approaches might be viable candidates in the context of automated decision making.}, address = {Würzburg, Germany}, author = {Seufert, Michael and Lange, Stanislav and Meixner, Markus}, booktitle = {1st International Workshop on Programmability for Cloud Networks and Applications (PROCON)}, keywords = {can}, month = {09}, title = {Automated Decision Making Methods for the Multi-objective Optimization Task of Cloud Service Placement}, year = 2016 }

%0 Conference Paper %1 info3-inproceedings-2016-12 %A Seufert, Michael %A Lange, Stanislav %A Meixner, Markus %B 1st International Workshop on Programmability for Cloud Networks and Applications (PROCON) %C Würzburg, Germany %D 2016 %T Automated Decision Making Methods for the Multi-objective Optimization Task of Cloud Service Placement %X The network functions virtualization (NFV) paradigm provides advantages with respect to aspects like flexibility, costs, and scalability of networks. However, management and orchestration of the resulting networks also introduce new challenges. The placement of services and virtualized network functions (VNFs) is a multi-objective optimization task that confronts operators with a multitude of possible solutions that are incomparable among each other. The goal of this work is to investigate mechanisms that enable automated decision making between such multi dimensional solutions. To this end, we investigate techniques from the domain of multi attribute decision making that aggregate the performance of placements to a single numeric score. A comparison between resulting rankings of placements shows that many techniques produce similar results. Hence, placements that achieve good rankings according to many approaches might be viable candidates in the context of automated decision making.
One Shot Crowdtesting: Approaching the Extremes of Crowdsourced Subjective Quality Testing. Seufert, Michael; Hoßfeld, Tobias. In 5th ISCA/DEGA Workshop on Perceptual Quality of Systems (PQS). Berlin, Germany, 2016.
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Crowdsourcing studies for subjective quality testing have become a particularly useful tool for Quality of Experience researchers. Typically, crowdsouring studies are conducted by many unsupervised workers, which rate the perceived quality of several test conditions during one session (mixed within-subject test design). However, those studies often show to be very sensitive, for example, to test instructions, design, and filtering of unreliable participants. Moreover, the exposure of several test conditions to single workers potentially leads to an implicit training and anchoring of ratings. Therefore, this works investigates the extreme case of presenting only a single test condition to each worker (completely between-subjects test design). The results are compared to a typical crowdsourcing study design with multiple test conditions to discuss training effects in crowdsourcing studies. Thus, this work investigates if it is possible to use a simple ``one shot'' design with only one rating of a large number of workers instead of sophisticated (mixed or within-subject) test designs in crowdsourcing.

@inproceedings{info3-inproceedings-2016-11, abstract = {Crowdsourcing studies for subjective quality testing have become a particularly useful tool for Quality of Experience researchers. Typically, crowdsouring studies are conducted by many unsupervised workers, which rate the perceived quality of several test conditions during one session (mixed within-subject test design). However, those studies often show to be very sensitive, for example, to test instructions, design, and filtering of unreliable participants. Moreover, the exposure of several test conditions to single workers potentially leads to an implicit training and anchoring of ratings. Therefore, this works investigates the extreme case of presenting only a single test condition to each worker (completely between-subjects test design). The results are compared to a typical crowdsourcing study design with multiple test conditions to discuss training effects in crowdsourcing studies. Thus, this work investigates if it is possible to use a simple ``one shot'' design with only one rating of a large number of workers instead of sophisticated (mixed or within-subject) test designs in crowdsourcing.}, address = {Berlin, Germany}, author = {Seufert, Michael and Hoßfeld, Tobias}, booktitle = {5th ISCA/DEGA Workshop on Perceptual Quality of Systems (PQS)}, keywords = {can}, month = {08}, title = {One Shot Crowdtesting: Approaching the Extremes of Crowdsourced Subjective Quality Testing}, year = 2016 }

%0 Conference Paper %1 info3-inproceedings-2016-11 %A Seufert, Michael %A Hoßfeld, Tobias %B 5th ISCA/DEGA Workshop on Perceptual Quality of Systems (PQS) %C Berlin, Germany %D 2016 %T One Shot Crowdtesting: Approaching the Extremes of Crowdsourced Subjective Quality Testing %X Crowdsourcing studies for subjective quality testing have become a particularly useful tool for Quality of Experience researchers. Typically, crowdsouring studies are conducted by many unsupervised workers, which rate the perceived quality of several test conditions during one session (mixed within-subject test design). However, those studies often show to be very sensitive, for example, to test instructions, design, and filtering of unreliable participants. Moreover, the exposure of several test conditions to single workers potentially leads to an implicit training and anchoring of ratings. Therefore, this works investigates the extreme case of presenting only a single test condition to each worker (completely between-subjects test design). The results are compared to a typical crowdsourcing study design with multiple test conditions to discuss training effects in crowdsourcing studies. Thus, this work investigates if it is possible to use a simple ``one shot'' design with only one rating of a large number of workers instead of sophisticated (mixed or within-subject) test designs in crowdsourcing.
Concept for Client-initiated Selection of Cloud Instances for Improving QoE of Distributed Cloud Services. Wamser, Florian; Seufert, Michael; Höfner, Steffen; Tran-Gia, Phuoc. In ACM SIGCOMM Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE). Florianópolis, Brazil, 2016.
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We introduce a concept for client-initiated selection of service location and service quality for improving the Quality of Experience (QoE) of general cloud services. It is loosely based on the HTTP adaptive streaming approach (e.g., MPEG DASH). A manifest file compiled by the cloud service provider specifies the available service locations and qualities, from which the user selects the optimal service instance based on contextual information obtained from client measurements and user preferences. The proposed concept is defined and is implemented in two client-based decision algorithms for improving the QoE of a simple picture gallery cloud service. These decision algorithms are evaluated and their impact on the service delivery is discussed. The evaluation shows that it is possible to improve the service location and quality selection by light-weight client-based algorithms.

@inproceedings{info3-inproceedings-2016-14, abstract = {We introduce a concept for client-initiated selection of service location and service quality for improving the Quality of Experience (QoE) of general cloud services. It is loosely based on the HTTP adaptive streaming approach (e.g., MPEG DASH). A manifest file compiled by the cloud service provider specifies the available service locations and qualities, from which the user selects the optimal service instance based on contextual information obtained from client measurements and user preferences. The proposed concept is defined and is implemented in two client-based decision algorithms for improving the QoE of a simple picture gallery cloud service. These decision algorithms are evaluated and their impact on the service delivery is discussed. The evaluation shows that it is possible to improve the service location and quality selection by light-weight client-based algorithms.}, address = {Florianópolis, Brazil}, author = {Wamser, Florian and Seufert, Michael and Höfner, Steffen and Tran-Gia, Phuoc}, booktitle = {ACM SIGCOMM Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE)}, keywords = {can}, month = {08}, title = {Concept for Client-initiated Selection of Cloud Instances for Improving QoE of Distributed Cloud Services}, year = 2016 }

%0 Conference Paper %1 info3-inproceedings-2016-14 %A Wamser, Florian %A Seufert, Michael %A Höfner, Steffen %A Tran-Gia, Phuoc %B ACM SIGCOMM Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE) %C Florianópolis, Brazil %D 2016 %T Concept for Client-initiated Selection of Cloud Instances for Improving QoE of Distributed Cloud Services %X We introduce a concept for client-initiated selection of service location and service quality for improving the Quality of Experience (QoE) of general cloud services. It is loosely based on the HTTP adaptive streaming approach (e.g., MPEG DASH). A manifest file compiled by the cloud service provider specifies the available service locations and qualities, from which the user selects the optimal service instance based on contextual information obtained from client measurements and user preferences. The proposed concept is defined and is implemented in two client-based decision algorithms for improving the QoE of a simple picture gallery cloud service. These decision algorithms are evaluated and their impact on the service delivery is discussed. The evaluation shows that it is possible to improve the service location and quality selection by light-weight client-based algorithms.
QoE Aware Placement of Content in Edge Networks on the Example of a Photo Album Cloud Service. Dinh-Xuan, Lam; Seufert, Michael; Wamser, Florian; Tran-Gia, Phuoc. In IEEE 6th International Conference on Communications and Electronics (ICCE). Ha Long, Vietnam, 2016.
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The paradigm of Software as a Service has gained great achievements in the last decade. By transferring computation and storage to the cloud and migrating services to the edge network, users benefit from using demanding services on lightweight devices. However, the user perceived quality of experience (QoE) for these services is facing the challenges of network impairments and the accessibility of users. Unlike a typical PC-based software, the cloud provides users a location-aware, flexible placement of resource for a cost effective service. The geographical placement of content is therefore one of the key factors that affects the user's satisfaction. The closer the content to the user geographically is, the faster it will be delivered to the user that will also increase the user perceived QoE. In this work, we estimate more precisely the QoE for photo loading time in a particular usage of a photo album cloud service with regard to the influence of various parameters. Firstly, we validate a TCP throughput model and use it to calculate the photo loading time from a given photo size and network QoS. Thereafter, we formulate a mapping function to calculate the MOS value from a QoE model adding the output of the TCP model. From this mapping function, we can estimate QoE for photo loading time from a given photo size, its placement and network QoS. Our main contribution is to determine the trade-off between the size of photo and its placement to acquire a high QoE for photo loading time, which is important for the development of a photo album cloud service.

@inproceedings{info3-inproceedings-2016-16, abstract = {The paradigm of Software as a Service has gained great achievements in the last decade. By transferring computation and storage to the cloud and migrating services to the edge network, users benefit from using demanding services on lightweight devices. However, the user perceived quality of experience (QoE) for these services is facing the challenges of network impairments and the accessibility of users. Unlike a typical PC-based software, the cloud provides users a location-aware, flexible placement of resource for a cost effective service. The geographical placement of content is therefore one of the key factors that affects the user's satisfaction. The closer the content to the user geographically is, the faster it will be delivered to the user that will also increase the user perceived QoE. In this work, we estimate more precisely the QoE for photo loading time in a particular usage of a photo album cloud service with regard to the influence of various parameters. Firstly, we validate a TCP throughput model and use it to calculate the photo loading time from a given photo size and network QoS. Thereafter, we formulate a mapping function to calculate the MOS value from a QoE model adding the output of the TCP model. From this mapping function, we can estimate QoE for photo loading time from a given photo size, its placement and network QoS. Our main contribution is to determine the trade-off between the size of photo and its placement to acquire a high QoE for photo loading time, which is important for the development of a photo album cloud service.}, address = {Ha Long, Vietnam}, author = {Dinh-Xuan, Lam and Seufert, Michael and Wamser, Florian and Tran-Gia, Phuoc}, booktitle = {IEEE 6th International Conference on Communications and Electronics (ICCE)}, keywords = {can}, month = {07}, title = {QoE Aware Placement of Content in Edge Networks on the Example of a Photo Album Cloud Service}, year = 2016 }

%0 Conference Paper %1 info3-inproceedings-2016-16 %A Dinh-Xuan, Lam %A Seufert, Michael %A Wamser, Florian %A Tran-Gia, Phuoc %B IEEE 6th International Conference on Communications and Electronics (ICCE) %C Ha Long, Vietnam %D 2016 %T QoE Aware Placement of Content in Edge Networks on the Example of a Photo Album Cloud Service %X The paradigm of Software as a Service has gained great achievements in the last decade. By transferring computation and storage to the cloud and migrating services to the edge network, users benefit from using demanding services on lightweight devices. However, the user perceived quality of experience (QoE) for these services is facing the challenges of network impairments and the accessibility of users. Unlike a typical PC-based software, the cloud provides users a location-aware, flexible placement of resource for a cost effective service. The geographical placement of content is therefore one of the key factors that affects the user's satisfaction. The closer the content to the user geographically is, the faster it will be delivered to the user that will also increase the user perceived QoE. In this work, we estimate more precisely the QoE for photo loading time in a particular usage of a photo album cloud service with regard to the influence of various parameters. Firstly, we validate a TCP throughput model and use it to calculate the photo loading time from a given photo size and network QoS. Thereafter, we formulate a mapping function to calculate the MOS value from a QoE model adding the output of the TCP model. From this mapping function, we can estimate QoE for photo loading time from a given photo size, its placement and network QoS. Our main contribution is to determine the trade-off between the size of photo and its placement to acquire a high QoE for photo loading time, which is important for the development of a photo album cloud service.
Application-Layer Monitoring of QoE Parameters for Mobile YouTube Video Streaming in the Field. Seufert, Michael; Casas, Pedro; Wamser, Florian; Wehner, Nikolas; Schatz, Raimund; Tran-Gia, Phuoc. In IEEE 6th International Conference on Communications and Electronics (ICCE). Ha Long, Vietnam, 2016.
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YouTube video streaming is one of the most popular and most demanding services in cellular networks. Thus, operators are concerned about the quality of the streaming delivered by their networks and would like to monitor the Quality of Experience (QoE) of the end users. In this work, we conduct a field study of mobile YouTube video streaming, in which both network flow parameters and application-layer streaming parameters were monitored, and present the characteristics of current mobile YouTube streaming. The impact of both approaches is investigated showing that monitoring network parameters is not sufficient to directly infer the resulting QoE. In contrast, the streaming parameters, which can be obtained from application-layer monitoring, show high correlations to the subjectively experienced quality, and thus, are better suited for QoE monitoring.

@inproceedings{info3-inproceedings-2016-9, abstract = {YouTube video streaming is one of the most popular and most demanding services in cellular networks. Thus, operators are concerned about the quality of the streaming delivered by their networks and would like to monitor the Quality of Experience (QoE) of the end users. In this work, we conduct a field study of mobile YouTube video streaming, in which both network flow parameters and application-layer streaming parameters were monitored, and present the characteristics of current mobile YouTube streaming. The impact of both approaches is investigated showing that monitoring network parameters is not sufficient to directly infer the resulting QoE. In contrast, the streaming parameters, which can be obtained from application-layer monitoring, show high correlations to the subjectively experienced quality, and thus, are better suited for QoE monitoring.}, address = {Ha Long, Vietnam}, author = {Seufert, Michael and Casas, Pedro and Wamser, Florian and Wehner, Nikolas and Schatz, Raimund and Tran-Gia, Phuoc}, booktitle = {IEEE 6th International Conference on Communications and Electronics (ICCE)}, keywords = {can}, month = {07}, title = {Application-Layer Monitoring of QoE Parameters for Mobile YouTube Video Streaming in the Field}, year = 2016 }

%0 Conference Paper %1 info3-inproceedings-2016-9 %A Seufert, Michael %A Casas, Pedro %A Wamser, Florian %A Wehner, Nikolas %A Schatz, Raimund %A Tran-Gia, Phuoc %B IEEE 6th International Conference on Communications and Electronics (ICCE) %C Ha Long, Vietnam %D 2016 %T Application-Layer Monitoring of QoE Parameters for Mobile YouTube Video Streaming in the Field %X YouTube video streaming is one of the most popular and most demanding services in cellular networks. Thus, operators are concerned about the quality of the streaming delivered by their networks and would like to monitor the Quality of Experience (QoE) of the end users. In this work, we conduct a field study of mobile YouTube video streaming, in which both network flow parameters and application-layer streaming parameters were monitored, and present the characteristics of current mobile YouTube streaming. The impact of both approaches is investigated showing that monitoring network parameters is not sufficient to directly infer the resulting QoE. In contrast, the streaming parameters, which can be obtained from application-layer monitoring, show high correlations to the subjectively experienced quality, and thus, are better suited for QoE monitoring.
Impact of Test Condition Selection in Adaptive Crowdsourcing Studies on Subjective Quality. Seufert, Michael; Zach, Ondrej; Hoßfeld, Tobias; Slanina, Martin; Tran-Gia, Phuoc. In 8th International Conference on Quality of Multimedia Experience (QoMEX). Lisbon, Portugal, 2016.
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Adaptive crowdsourcing is a new approach to crowdsourced Quality of Experience (QoE) studies, which aims to improve the certainty of resulting QoE models by adaptively distributing a fixed budget of user ratings to the test conditions. The main idea of the adaptation is to dynamically allocate the next rating to a condition, for which the submitted ratings so far show a low certainty. This paper investigates the effects of statistical adaptation on the distribution of ratings and the goodness of the resulting QoE models. Thereby, it gives methodological advice how to select test conditions for future crowdsourced QoE studies.

@inproceedings{info3-inproceedings-2016-10, abstract = {Adaptive crowdsourcing is a new approach to crowdsourced Quality of Experience (QoE) studies, which aims to improve the certainty of resulting QoE models by adaptively distributing a fixed budget of user ratings to the test conditions. The main idea of the adaptation is to dynamically allocate the next rating to a condition, for which the submitted ratings so far show a low certainty. This paper investigates the effects of statistical adaptation on the distribution of ratings and the goodness of the resulting QoE models. Thereby, it gives methodological advice how to select test conditions for future crowdsourced QoE studies.}, address = {Lisbon, Portugal}, author = {Seufert, Michael and Zach, Ondrej and Hoßfeld, Tobias and Slanina, Martin and Tran-Gia, Phuoc}, booktitle = {8th International Conference on Quality of Multimedia Experience (QoMEX)}, keywords = {can}, month = {06}, title = {Impact of Test Condition Selection in Adaptive Crowdsourcing Studies on Subjective Quality}, year = 2016 }

%0 Conference Paper %1 info3-inproceedings-2016-10 %A Seufert, Michael %A Zach, Ondrej %A Hoßfeld, Tobias %A Slanina, Martin %A Tran-Gia, Phuoc %B 8th International Conference on Quality of Multimedia Experience (QoMEX) %C Lisbon, Portugal %D 2016 %T Impact of Test Condition Selection in Adaptive Crowdsourcing Studies on Subjective Quality %X Adaptive crowdsourcing is a new approach to crowdsourced Quality of Experience (QoE) studies, which aims to improve the certainty of resulting QoE models by adaptively distributing a fixed budget of user ratings to the test conditions. The main idea of the adaptation is to dynamically allocate the next rating to a condition, for which the submitted ratings so far show a low certainty. This paper investigates the effects of statistical adaptation on the distribution of ratings and the goodness of the resulting QoE models. Thereby, it gives methodological advice how to select test conditions for future crowdsourced QoE studies.
Load Dynamics of a Multiplayer Online Battle Area and Simulative Assessment of Edge Server Placements. Burger, Valentin; Frances Pajo, Jane; Sanchez, Odnan Ref; Seufert, Michael; Schwartz, Christian; Wamser, Florian; Davoli, Franco; Tran-Gia, Phuoc. In ACM Multimedia Systems Conference (MMSys). Klagenfurt, Austria, 2016.
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Free-to-play models, streaming of games and eSports are reasons for online gaming to grow in popularity recently. On the forefront are multiplayer online battle arenas, which gain high popularity by introducing a competitive format that is easy to access and requires cooperation and team play. These games highly rely on fast reaction of the players, which makes latency the key performance indicator of such applications. To obtain low latency, this paper proposes moving game servers close to players towards the edge of the network. The performance of such mechanism highly depends on the geographic distribution of players. By analyzing match histories and statistics, we develop models for the arrival process and location of game requests. This allows us to evaluate the performance of edge server resource migration policies in an event based simulation. Our results show that a high number of edge servers is preferable compared to few larger edge servers to reduce the latency of players. This supports approaches that allow deploying virtual server instances in the back-haul.

@inproceedings{info3-inproceedings-2016-2, abstract = {Free-to-play models, streaming of games and eSports are reasons for online gaming to grow in popularity recently. On the forefront are multiplayer online battle arenas, which gain high popularity by introducing a competitive format that is easy to access and requires cooperation and team play. These games highly rely on fast reaction of the players, which makes latency the key performance indicator of such applications. To obtain low latency, this paper proposes moving game servers close to players towards the edge of the network. The performance of such mechanism highly depends on the geographic distribution of players. By analyzing match histories and statistics, we develop models for the arrival process and location of game requests. This allows us to evaluate the performance of edge server resource migration policies in an event based simulation. Our results show that a high number of edge servers is preferable compared to few larger edge servers to reduce the latency of players. This supports approaches that allow deploying virtual server instances in the back-haul.}, address = {Klagenfurt, Austria}, author = {Burger, Valentin and Frances Pajo, Jane and Sanchez, Odnan Ref and Seufert, Michael and Schwartz, Christian and Wamser, Florian and Davoli, Franco and Tran-Gia, Phuoc}, booktitle = {ACM Multimedia Systems Conference (MMSys)}, keywords = {can}, month = {05}, title = {Load Dynamics of a Multiplayer Online Battle Area and Simulative Assessment of Edge Server Placements}, year = 2016 }

%0 Conference Paper %1 info3-inproceedings-2016-2 %A Burger, Valentin %A Frances Pajo, Jane %A Sanchez, Odnan Ref %A Seufert, Michael %A Schwartz, Christian %A Wamser, Florian %A Davoli, Franco %A Tran-Gia, Phuoc %B ACM Multimedia Systems Conference (MMSys) %C Klagenfurt, Austria %D 2016 %T Load Dynamics of a Multiplayer Online Battle Area and Simulative Assessment of Edge Server Placements %X Free-to-play models, streaming of games and eSports are reasons for online gaming to grow in popularity recently. On the forefront are multiplayer online battle arenas, which gain high popularity by introducing a competitive format that is easy to access and requires cooperation and team play. These games highly rely on fast reaction of the players, which makes latency the key performance indicator of such applications. To obtain low latency, this paper proposes moving game servers close to players towards the edge of the network. The performance of such mechanism highly depends on the geographic distribution of players. By analyzing match histories and statistics, we develop models for the arrival process and location of game requests. This allows us to evaluate the performance of edge server resource migration policies in an event based simulation. Our results show that a high number of edge servers is preferable compared to few larger edge servers to reduce the latency of players. This supports approaches that allow deploying virtual server instances in the back-haul.
Group-based Communication in WhatsApp. Seufert, Michael; Hoßfeld, Tobias; Schwind, Anika; Burger, Valentin; Tran-Gia, Phuoc. In 1st IFIP Internet of People Workshop (IoP). Vienna, Austria, 2016.
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WhatsApp is a very popular mobile messaging application, which dominates today’s mobile communication. Especially the feature of group chats contributes to its success and changes the way people communicate. The group-based communication paradigm is investigated in this work, particularly focusing on the usage of WhatsApp, communication in group chats, and implications on mobile network traffic.

@inproceedings{info3-inproceedings-2016-1, abstract = {WhatsApp is a very popular mobile messaging application, which dominates today’s mobile communication. Especially the feature of group chats contributes to its success and changes the way people communicate. The group-based communication paradigm is investigated in this work, particularly focusing on the usage of WhatsApp, communication in group chats, and implications on mobile network traffic.}, address = {Vienna, Austria}, author = {Seufert, Michael and Hoßfeld, Tobias and Schwind, Anika and Burger, Valentin and Tran-Gia, Phuoc}, booktitle = {1st IFIP Internet of People Workshop (IoP)}, keywords = {can}, month = {05}, title = {Group-based Communication in WhatsApp}, year = 2016 }

%0 Conference Paper %1 info3-inproceedings-2016-1 %A Seufert, Michael %A Hoßfeld, Tobias %A Schwind, Anika %A Burger, Valentin %A Tran-Gia, Phuoc %B 1st IFIP Internet of People Workshop (IoP) %C Vienna, Austria %D 2016 %T Group-based Communication in WhatsApp %X WhatsApp is a very popular mobile messaging application, which dominates today’s mobile communication. Especially the feature of group chats contributes to its success and changes the way people communicate. The group-based communication paradigm is investigated in this work, particularly focusing on the usage of WhatsApp, communication in group chats, and implications on mobile network traffic.
Taming QoE in Cellular Networks: from Subjective Lab Studies to Measurements in the Field. Casas, Pedro; Gardlo, Bruno; Seufert, Michael; Wamser, Florian; Schatz, Raimund. In 11th International Conference on Network and Service Management (CNSM). Barcelona, Spain, 2015.
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A quarter of the world population will be using smartphones to access the Internet in the near future. In this context, understanding the Quality of Experience (QoE) of popular apps in such devices becomes paramount to cellular network operators, who need to offer high quality levels to reduce the risks of customers churning for quality dissatisfaction. In this paper we address the problem of QoE provisioning in smartphones from a double perspective, combining the results obtained from subjective lab tests with end-device passive measurements and QoE crowd-sourced feedback obtained in operational cellular networks. The study addresses the impact of the downlink bandwidth on the QoE of three popular smartphone apps: YouTube, Facebook and Google Maps. As a main contribution, we show that the results obtained in the lab are highly applicable in the live scenario, as mappings track the QoE provided by users in real networks. We additionally provide hints and bandwidth thresholds for good QoE levels on such apps, as well as discussion on end-device passive measurements and analysis. The results presented in this paper provide a sound basis to better understand the QoE requirements of popular mobile apps, as well as for monitoring the underlying provisioning network. To the best of our knowledge, this is the first paper providing such a comprehensive analysis of QoE in mobile devices, combining network measurements with users QoE feedback in lab tests and operational networks.

@inproceedings{info3-inproceedings-2015-531, abstract = {A quarter of the world population will be using smartphones to access the Internet in the near future. In this context, understanding the Quality of Experience (QoE) of popular apps in such devices becomes paramount to cellular network operators, who need to offer high quality levels to reduce the risks of customers churning for quality dissatisfaction. In this paper we address the problem of QoE provisioning in smartphones from a double perspective, combining the results obtained from subjective lab tests with end-device passive measurements and QoE crowd-sourced feedback obtained in operational cellular networks. The study addresses the impact of the downlink bandwidth on the QoE of three popular smartphone apps: YouTube, Facebook and Google Maps. As a main contribution, we show that the results obtained in the lab are highly applicable in the live scenario, as mappings track the QoE provided by users in real networks. We additionally provide hints and bandwidth thresholds for good QoE levels on such apps, as well as discussion on end-device passive measurements and analysis. The results presented in this paper provide a sound basis to better understand the QoE requirements of popular mobile apps, as well as for monitoring the underlying provisioning network. To the best of our knowledge, this is the first paper providing such a comprehensive analysis of QoE in mobile devices, combining network measurements with users QoE feedback in lab tests and operational networks.}, address = {Barcelona, Spain}, author = {Casas, Pedro and Gardlo, Bruno and Seufert, Michael and Wamser, Florian and Schatz, Raimund}, booktitle = {11th International Conference on Network and Service Management (CNSM)}, keywords = {can}, month = 11, title = {Taming QoE in Cellular Networks: from Subjective Lab Studies to Measurements in the Field}, year = 2015 }

%0 Conference Paper %1 info3-inproceedings-2015-531 %A Casas, Pedro %A Gardlo, Bruno %A Seufert, Michael %A Wamser, Florian %A Schatz, Raimund %B 11th International Conference on Network and Service Management (CNSM) %C Barcelona, Spain %D 2015 %T Taming QoE in Cellular Networks: from Subjective Lab Studies to Measurements in the Field %X A quarter of the world population will be using smartphones to access the Internet in the near future. In this context, understanding the Quality of Experience (QoE) of popular apps in such devices becomes paramount to cellular network operators, who need to offer high quality levels to reduce the risks of customers churning for quality dissatisfaction. In this paper we address the problem of QoE provisioning in smartphones from a double perspective, combining the results obtained from subjective lab tests with end-device passive measurements and QoE crowd-sourced feedback obtained in operational cellular networks. The study addresses the impact of the downlink bandwidth on the QoE of three popular smartphone apps: YouTube, Facebook and Google Maps. As a main contribution, we show that the results obtained in the lab are highly applicable in the live scenario, as mappings track the QoE provided by users in real networks. We additionally provide hints and bandwidth thresholds for good QoE levels on such apps, as well as discussion on end-device passive measurements and analysis. The results presented in this paper provide a sound basis to better understand the QoE requirements of popular mobile apps, as well as for monitoring the underlying provisioning network. To the best of our knowledge, this is the first paper providing such a comprehensive analysis of QoE in mobile devices, combining network measurements with users QoE feedback in lab tests and operational networks.
Impact of Intermediate Layer on Quality of Experience of HTTP Adaptive Streaming. Seufert, Michael; Hoßfeld, Tobias; Sieber, Christian. In 11th International Conference on Network and Service Management (CNSM). Barcelona, Spain, 2015.
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HTTP Adaptive Streaming (HAS) adapts the video quality to the current network condition by switching between different quality layers. As HAS was shown to perform better than classical video streaming, it is becoming increasingly popular. Recent research showed that quality switch amplitude and time on layer have an impact on the Quality of Experience (QoE) of HAS. However, those studies focused only on adaptation between two layers so far. This work extends these findings by taking adaptation between three layers into account. Thereby, especially the impact of an intermediate layer on user perceived quality is investigated. Crowdsourcing experiments were conducted in order to collect subjective ratings for adaptation between three layers. The results indicate that the quality of each layer and the time on each layer are important QoE parameters. This encourages the usage of temporal pooling approaches for QoE prediction and QoE-aware traffic management. Therefore, mean pooling of per-frame metrics will be applied and its performance will be validated with the subjective crowdsourcing results.

@inproceedings{info3-inproceedings-2015-532, abstract = {HTTP Adaptive Streaming (HAS) adapts the video quality to the current network condition by switching between different quality layers. As HAS was shown to perform better than classical video streaming, it is becoming increasingly popular. Recent research showed that quality switch amplitude and time on layer have an impact on the Quality of Experience (QoE) of HAS. However, those studies focused only on adaptation between two layers so far. This work extends these findings by taking adaptation between three layers into account. Thereby, especially the impact of an intermediate layer on user perceived quality is investigated. Crowdsourcing experiments were conducted in order to collect subjective ratings for adaptation between three layers. The results indicate that the quality of each layer and the time on each layer are important QoE parameters. This encourages the usage of temporal pooling approaches for QoE prediction and QoE-aware traffic management. Therefore, mean pooling of per-frame metrics will be applied and its performance will be validated with the subjective crowdsourcing results.}, address = {Barcelona, Spain}, author = {Seufert, Michael and Hoßfeld, Tobias and Sieber, Christian}, booktitle = {11th International Conference on Network and Service Management (CNSM)}, keywords = {can}, month = 11, title = {Impact of Intermediate Layer on Quality of Experience of HTTP Adaptive Streaming}, year = 2015 }

%0 Conference Paper %1 info3-inproceedings-2015-532 %A Seufert, Michael %A Hoßfeld, Tobias %A Sieber, Christian %B 11th International Conference on Network and Service Management (CNSM) %C Barcelona, Spain %D 2015 %T Impact of Intermediate Layer on Quality of Experience of HTTP Adaptive Streaming %X HTTP Adaptive Streaming (HAS) adapts the video quality to the current network condition by switching between different quality layers. As HAS was shown to perform better than classical video streaming, it is becoming increasingly popular. Recent research showed that quality switch amplitude and time on layer have an impact on the Quality of Experience (QoE) of HAS. However, those studies focused only on adaptation between two layers so far. This work extends these findings by taking adaptation between three layers into account. Thereby, especially the impact of an intermediate layer on user perceived quality is investigated. Crowdsourcing experiments were conducted in order to collect subjective ratings for adaptation between three layers. The results indicate that the quality of each layer and the time on each layer are important QoE parameters. This encourages the usage of temporal pooling approaches for QoE prediction and QoE-aware traffic management. Therefore, mean pooling of per-frame metrics will be applied and its performance will be validated with the subjective crowdsourcing results.
Trade-Off between QoE and Operational Cost in Edge Resource Supported Video Streaming. Burger, Valentin; Darzanos, George; Papafili, Ioanna; Seufert, Michael. In 10th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC). Krakow, Poland, 2015.
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The largest share of today`s consumer Internet traffic is video streaming and its demand on content delivery networks is continuously growing. To cope with the increasing demand of video streaming, recent work proposes mitigating end-user equipment to support content delivery at the edge of the network. The throughput of end-user equipment supporting content delivery is limited by the uplink of the users Internet connection.Especially for video streaming insufficient throughput causes the video to stall and affects the Quality of Experience (QoE) of end-users.To prevent video streams from stalling, we consider a tiered caching architecture, which requests higher tier caches to support content delivery, if the uplink throughput drops below a certain threshold. We conduct a simulative performance evaluation of the mechanism to investigate its impact on the QoE of end-users. Our results show that especially if the upload bandwidth of end-user equipment is low the setting of the threshold has a high impact. This can be used by operators to achieve the desired trade-off between QoE and operational cost for cache resources.

@inproceedings{info3-inproceedings-2015-530, abstract = {The largest share of today`s consumer Internet traffic is video streaming and its demand on content delivery networks is continuously growing. To cope with the increasing demand of video streaming, recent work proposes mitigating end-user equipment to support content delivery at the edge of the network. The throughput of end-user equipment supporting content delivery is limited by the uplink of the users Internet connection.Especially for video streaming insufficient throughput causes the video to stall and affects the Quality of Experience (QoE) of end-users.To prevent video streams from stalling, we consider a tiered caching architecture, which requests higher tier caches to support content delivery, if the uplink throughput drops below a certain threshold. We conduct a simulative performance evaluation of the mechanism to investigate its impact on the QoE of end-users. Our results show that especially if the upload bandwidth of end-user equipment is low the setting of the threshold has a high impact. This can be used by operators to achieve the desired trade-off between QoE and operational cost for cache resources.}, address = {Krakow, Poland}, author = {Burger, Valentin and Darzanos, George and Papafili, Ioanna and Seufert, Michael}, booktitle = {10th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC)}, keywords = {can}, month = 11, title = {Trade-Off between QoE and Operational Cost in Edge Resource Supported Video Streaming}, year = 2015 }

%0 Conference Paper %1 info3-inproceedings-2015-530 %A Burger, Valentin %A Darzanos, George %A Papafili, Ioanna %A Seufert, Michael %B 10th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC) %C Krakow, Poland %D 2015 %T Trade-Off between QoE and Operational Cost in Edge Resource Supported Video Streaming %X The largest share of today`s consumer Internet traffic is video streaming and its demand on content delivery networks is continuously growing. To cope with the increasing demand of video streaming, recent work proposes mitigating end-user equipment to support content delivery at the edge of the network. The throughput of end-user equipment supporting content delivery is limited by the uplink of the users Internet connection.Especially for video streaming insufficient throughput causes the video to stall and affects the Quality of Experience (QoE) of end-users.To prevent video streams from stalling, we consider a tiered caching architecture, which requests higher tier caches to support content delivery, if the uplink throughput drops below a certain threshold. We conduct a simulative performance evaluation of the mechanism to investigate its impact on the QoE of end-users. Our results show that especially if the upload bandwidth of end-user equipment is low the setting of the threshold has a high impact. This can be used by operators to achieve the desired trade-off between QoE and operational cost for cache resources.
Augmenting Home Routers for Socially-Aware Traffic Management. Lareida, Andri; Petropoulos, George; Burger, Valentin; Seufert, Michael; Soursos, Sergios; Stiller, Burkhard. In 40th Annual IEEE Conference on Local Computer Networks (LCN). Clearwater Beach, FL, USA, 2015.
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Mobile users' Quality-of-Experience (QoE) is degrading as network usage increases while Internet Service Providers (ISP) face increased inter-domain traffic. This paper presents a network traffic management mechanism, named RB-HORST, addressing these inefficiencies. RB-HORST exploits home routers by using them as caches and forming an overlay network between them to transfer content. To shift traffic from peak hours, RB-HORST employs predictions based on social network properties and based on similarity in the overlay network. To further improve user QoE, home routers allow trusted mobile devices to offload their mobile connection to the local WiFi. Simulation results show that an overlay is imperative for the success of the proposed caching mechanism. Especially ISPs with a large number of customers can benefit if only every thousandth user shares its router, reducing inter-domain traffic by half and superseding an ISP operated cache. The presented implementation proves that the concept is technically feasible and can be deployed and run on constrained devices.

@inproceedings{info3-inproceedings-2015-518, abstract = {Mobile users' Quality-of-Experience (QoE) is degrading as network usage increases while Internet Service Providers (ISP) face increased inter-domain traffic. This paper presents a network traffic management mechanism, named RB-HORST, addressing these inefficiencies. RB-HORST exploits home routers by using them as caches and forming an overlay network between them to transfer content. To shift traffic from peak hours, RB-HORST employs predictions based on social network properties and based on similarity in the overlay network. To further improve user QoE, home routers allow trusted mobile devices to offload their mobile connection to the local WiFi. Simulation results show that an overlay is imperative for the success of the proposed caching mechanism. Especially ISPs with a large number of customers can benefit if only every thousandth user shares its router, reducing inter-domain traffic by half and superseding an ISP operated cache. The presented implementation proves that the concept is technically feasible and can be deployed and run on constrained devices.}, address = {Clearwater Beach, FL, USA}, author = {Lareida, Andri and Petropoulos, George and Burger, Valentin and Seufert, Michael and Soursos, Sergios and Stiller, Burkhard}, booktitle = {40th Annual IEEE Conference on Local Computer Networks (LCN)}, keywords = {smartenit}, month = 10, title = {Augmenting Home Routers for Socially-Aware Traffic Management}, year = 2015 }

%0 Conference Paper %1 info3-inproceedings-2015-518 %A Lareida, Andri %A Petropoulos, George %A Burger, Valentin %A Seufert, Michael %A Soursos, Sergios %A Stiller, Burkhard %B 40th Annual IEEE Conference on Local Computer Networks (LCN) %C Clearwater Beach, FL, USA %D 2015 %T Augmenting Home Routers for Socially-Aware Traffic Management %X Mobile users' Quality-of-Experience (QoE) is degrading as network usage increases while Internet Service Providers (ISP) face increased inter-domain traffic. This paper presents a network traffic management mechanism, named RB-HORST, addressing these inefficiencies. RB-HORST exploits home routers by using them as caches and forming an overlay network between them to transfer content. To shift traffic from peak hours, RB-HORST employs predictions based on social network properties and based on similarity in the overlay network. To further improve user QoE, home routers allow trusted mobile devices to offload their mobile connection to the local WiFi. Simulation results show that an overlay is imperative for the success of the proposed caching mechanism. Especially ISPs with a large number of customers can benefit if only every thousandth user shares its router, reducing inter-domain traffic by half and superseding an ISP operated cache. The presented implementation proves that the concept is technically feasible and can be deployed and run on constrained devices.
Energy Considerations for WiFi Offloading of Video Streaming. Burger, Valentin; Kaup, Fabian; Seufert, Michael; Wichtlhuber, Matthias; Hausheer, David; Tran-Gia, Phuoc. In 7th EAI International Conference on Mobile Networks and Management (MONAMI). Santander, Spain, 2015.
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The load on cellular networks is constantly increasing. Especially video streaming applications, whose demands and requirements keep growing, put high loads on cellular networks. A solution to mitigate the cellular load in urban environments is offloading mobile connections to WiFi access points, which is followed by many providers recently. Because of the large number of mobile users and devices there is also a high potential to save energy by WiFi offloading. In this work, we develop a model to assess the energy consumption of mobile devices during video sessions. We evaluate the potential of WiFi offloading in an urban environment and the implications of offloading connections on energy consumption of mobile devices. Our results show that, although WiFi is more energy efficient than 3G and 4G for equal data rates, the energy consumption increases with the amount of connections offloaded to WiFi, due to poor data rates obtained for WiFi in the streets. This suggests further deployment of WiFi access points or WiFi sharing incentives to increase data rates for WiFi and energy efficiency of mobile access.

@inproceedings{info3-inproceedings-2015-524, abstract = {The load on cellular networks is constantly increasing. Especially video streaming applications, whose demands and requirements keep growing, put high loads on cellular networks. A solution to mitigate the cellular load in urban environments is offloading mobile connections to WiFi access points, which is followed by many providers recently. Because of the large number of mobile users and devices there is also a high potential to save energy by WiFi offloading. In this work, we develop a model to assess the energy consumption of mobile devices during video sessions. We evaluate the potential of WiFi offloading in an urban environment and the implications of offloading connections on energy consumption of mobile devices. Our results show that, although WiFi is more energy efficient than 3G and 4G for equal data rates, the energy consumption increases with the amount of connections offloaded to WiFi, due to poor data rates obtained for WiFi in the streets. This suggests further deployment of WiFi access points or WiFi sharing incentives to increase data rates for WiFi and energy efficiency of mobile access.}, address = {Santander, Spain}, author = {Burger, Valentin and Kaup, Fabian and Seufert, Michael and Wichtlhuber, Matthias and Hausheer, David and Tran-Gia, Phuoc}, booktitle = {7th EAI International Conference on Mobile Networks and Management (MONAMI)}, keywords = {smartenit}, month = {09}, title = {Energy Considerations for WiFi Offloading of Video Streaming}, year = 2015 }

%0 Conference Paper %1 info3-inproceedings-2015-524 %A Burger, Valentin %A Kaup, Fabian %A Seufert, Michael %A Wichtlhuber, Matthias %A Hausheer, David %A Tran-Gia, Phuoc %B 7th EAI International Conference on Mobile Networks and Management (MONAMI) %C Santander, Spain %D 2015 %T Energy Considerations for WiFi Offloading of Video Streaming %X The load on cellular networks is constantly increasing. Especially video streaming applications, whose demands and requirements keep growing, put high loads on cellular networks. A solution to mitigate the cellular load in urban environments is offloading mobile connections to WiFi access points, which is followed by many providers recently. Because of the large number of mobile users and devices there is also a high potential to save energy by WiFi offloading. In this work, we develop a model to assess the energy consumption of mobile devices during video sessions. We evaluate the potential of WiFi offloading in an urban environment and the implications of offloading connections on energy consumption of mobile devices. Our results show that, although WiFi is more energy efficient than 3G and 4G for equal data rates, the energy consumption increases with the amount of connections offloaded to WiFi, due to poor data rates obtained for WiFi in the streets. This suggests further deployment of WiFi access points or WiFi sharing incentives to increase data rates for WiFi and energy efficiency of mobile access.
Analysis of Group-based Communication in WhatsApp. Seufert, Michael; Schwind, Anika; Hoßfeld, Tobias; Tran-Gia, Phuoc. In 7th EAI International Conference on Mobile Networks and Management (MONAMI). Santander, Spain, 2015.
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This work investigates group-based communication in WhatsApp based on a survey and the analysis of messaging logs. The characteristics of WhatsApp group chats in terms of usage and topics are outlined. We present a classification based on the topic of the group and classify anonymized messaging logs based on message statistics. Finally, we model WhatsApp group communication with a semi-Markov process, which can be used to generate network traffic similar to real messaging logs.

@inproceedings{info3-inproceedings-2015-523, abstract = {This work investigates group-based communication in WhatsApp based on a survey and the analysis of messaging logs. The characteristics of WhatsApp group chats in terms of usage and topics are outlined. We present a classification based on the topic of the group and classify anonymized messaging logs based on message statistics. Finally, we model WhatsApp group communication with a semi-Markov process, which can be used to generate network traffic similar to real messaging logs.}, address = {Santander, Spain}, author = {Seufert, Michael and Schwind, Anika and Hoßfeld, Tobias and Tran-Gia, Phuoc}, booktitle = {7th EAI International Conference on Mobile Networks and Management (MONAMI)}, keywords = {smartenit}, month = {09}, title = {Analysis of Group-based Communication in WhatsApp}, year = 2015 }

%0 Conference Paper %1 info3-inproceedings-2015-523 %A Seufert, Michael %A Schwind, Anika %A Hoßfeld, Tobias %A Tran-Gia, Phuoc %B 7th EAI International Conference on Mobile Networks and Management (MONAMI) %C Santander, Spain %D 2015 %T Analysis of Group-based Communication in WhatsApp %X This work investigates group-based communication in WhatsApp based on a survey and the analysis of messaging logs. The characteristics of WhatsApp group chats in terms of usage and topics are outlined. We present a classification based on the topic of the group and classify anonymized messaging logs based on message statistics. Finally, we model WhatsApp group communication with a semi-Markov process, which can be used to generate network traffic similar to real messaging logs.
YouTube QoE on Mobile Devices: Subjective Analysis of Classical vs. Adaptive Video Streaming. Seufert, Michael; Wamser, Florian; Casas, Pedro; Irmer, Ralf; Tran-Gia, Phuoc; Schatz, Raimund. In 6th International Workshop on Traffic Analysis and Characterization (TRAC). Dubrovnik, Croatia, 2015.
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YouTube is the most popular service in the Internet and is increasingly consumed on mobile devices. With emerging adaptive video streaming technology, the question arises whether it should be also employed in the mobile context, which shows different characteristics in terms of display sizes and reliability of Internet connection. This paper compares YouTube QoE on mobile devices for both classical and adaptive video streaming based on a subjective lab experiment, in which different network conditions were emulated. Our results show that adaptive video streaming provides almost excellent results for the poorest network conditions. Thereby, it clearly outperforms classical video streaming, and thus, should be considered to achieve higher QoE in future mobile streaming applications.

@inproceedings{info3-inproceedings-2015-515, abstract = {YouTube is the most popular service in the Internet and is increasingly consumed on mobile devices. With emerging adaptive video streaming technology, the question arises whether it should be also employed in the mobile context, which shows different characteristics in terms of display sizes and reliability of Internet connection. This paper compares YouTube QoE on mobile devices for both classical and adaptive video streaming based on a subjective lab experiment, in which different network conditions were emulated. Our results show that adaptive video streaming provides almost excellent results for the poorest network conditions. Thereby, it clearly outperforms classical video streaming, and thus, should be considered to achieve higher QoE in future mobile streaming applications.}, address = {Dubrovnik, Croatia}, author = {Seufert, Michael and Wamser, Florian and Casas, Pedro and Irmer, Ralf and Tran-Gia, Phuoc and Schatz, Raimund}, booktitle = {6th International Workshop on Traffic Analysis and Characterization (TRAC)}, keywords = {can}, month = {08}, title = {YouTube QoE on Mobile Devices: Subjective Analysis of Classical vs. Adaptive Video Streaming}, year = 2015 }

%0 Conference Paper %1 info3-inproceedings-2015-515 %A Seufert, Michael %A Wamser, Florian %A Casas, Pedro %A Irmer, Ralf %A Tran-Gia, Phuoc %A Schatz, Raimund %B 6th International Workshop on Traffic Analysis and Characterization (TRAC) %C Dubrovnik, Croatia %D 2015 %T YouTube QoE on Mobile Devices: Subjective Analysis of Classical vs. Adaptive Video Streaming %X YouTube is the most popular service in the Internet and is increasingly consumed on mobile devices. With emerging adaptive video streaming technology, the question arises whether it should be also employed in the mobile context, which shows different characteristics in terms of display sizes and reliability of Internet connection. This paper compares YouTube QoE on mobile devices for both classical and adaptive video streaming based on a subjective lab experiment, in which different network conditions were emulated. Our results show that adaptive video streaming provides almost excellent results for the poorest network conditions. Thereby, it clearly outperforms classical video streaming, and thus, should be considered to achieve higher QoE in future mobile streaming applications.
Exploring QoE in Cellular Networks: How Much Bandwidth do you Need for Popular Smartphone Apps?. Casas, Pedro; Schatz, Raimund; Wamser, Florian; Seufert, Michael; Irmer, Ralf. In 5th ACM SIGCOMM Workshop on All Things Cellular: Operations, Applications and Challenges. London, UK, 2015.
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A quarter of the world population will be using smartphones to access the Internet in the near future. In this context, understanding the Quality of Experience (QoE) of popular services in such devices becomes paramount for cellular network operators, who need to offer high quality levels to reduce the risks of customers churning for quality dissatisfaction. In this paper we study the problemof QoE provisioning in smartphones, presenting the results obtained from subjective lab tests performed for five popular apps: YouTube, Facebook, Web browsing through Chrome, Google Maps, and WhatsApp. The analysis addresses the impact of the access downlink bandwidth on the QoE of these apps when accessed through smartphones. The results presented in this paper provide a sound basis for better understanding the QoE requirements of popular services and mobile apps, as well as for dimensioning the underlying provisioning network. To the best of our knowledge, this is the first paper providing such a comprehensive analysis of QoE in mobile devices.

@inproceedings{info3-inproceedings-2015-516, abstract = {A quarter of the world population will be using smartphones to access the Internet in the near future. In this context, understanding the Quality of Experience (QoE) of popular services in such devices becomes paramount for cellular network operators, who need to offer high quality levels to reduce the risks of customers churning for quality dissatisfaction. In this paper we study the problemof QoE provisioning in smartphones, presenting the results obtained from subjective lab tests performed for five popular apps: YouTube, Facebook, Web browsing through Chrome, Google Maps, and WhatsApp. The analysis addresses the impact of the access downlink bandwidth on the QoE of these apps when accessed through smartphones. The results presented in this paper provide a sound basis for better understanding the QoE requirements of popular services and mobile apps, as well as for dimensioning the underlying provisioning network. To the best of our knowledge, this is the first paper providing such a comprehensive analysis of QoE in mobile devices.}, address = {London, UK}, author = {Casas, Pedro and Schatz, Raimund and Wamser, Florian and Seufert, Michael and Irmer, Ralf}, booktitle = {5th ACM SIGCOMM Workshop on All Things Cellular: Operations, Applications and Challenges}, keywords = {can}, month = {08}, title = {Exploring QoE in Cellular Networks: How Much Bandwidth do you Need for Popular Smartphone Apps?}, year = 2015 }

%0 Conference Paper %1 info3-inproceedings-2015-516 %A Casas, Pedro %A Schatz, Raimund %A Wamser, Florian %A Seufert, Michael %A Irmer, Ralf %B 5th ACM SIGCOMM Workshop on All Things Cellular: Operations, Applications and Challenges %C London, UK %D 2015 %T Exploring QoE in Cellular Networks: How Much Bandwidth do you Need for Popular Smartphone Apps? %X A quarter of the world population will be using smartphones to access the Internet in the near future. In this context, understanding the Quality of Experience (QoE) of popular services in such devices becomes paramount for cellular network operators, who need to offer high quality levels to reduce the risks of customers churning for quality dissatisfaction. In this paper we study the problemof QoE provisioning in smartphones, presenting the results obtained from subjective lab tests performed for five popular apps: YouTube, Facebook, Web browsing through Chrome, Google Maps, and WhatsApp. The analysis addresses the impact of the access downlink bandwidth on the QoE of these apps when accessed through smartphones. The results presented in this paper provide a sound basis for better understanding the QoE requirements of popular services and mobile apps, as well as for dimensioning the underlying provisioning network. To the best of our knowledge, this is the first paper providing such a comprehensive analysis of QoE in mobile devices.
Impact of WiFi Offloading on Video Streaming QoE in Urban Environments. Burger, Valentin; Seufert, Michael; Kaup, Fabian; Wichtlhuber, Matthias; Hausheer, David; Tran-Gia, Phuoc. In IEEE Workshop on Quality of Experience-based Management for Future Internet Applications and Services (QoE-FI). London, UK, 2015.
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Video streaming is the most popular application in today's mobile Internet and its growing demands and popularity put more and more load on cellular networks. In a recent trend to mitigate the cellular load, followed by many providers, users are offered to offload mobile connections to WiFi hotspots, which are predominately deployed in urban environments. In this work, we conduct a simulative performance evaluation of the impact of WiFi offloading on the Quality of Experience (QoE) of video streaming. The evaluation is based on connectivity measurements from a German city and uses a simple QoE model for estimating the perceived quality of video streaming. Our findings show that, despite its benefits for operators, offloading to WiFi has a negative impact on video streaming QoE for some users when 3G/4G coverage is available. Only in the case of 2G coverage, WiFi offloading can significantly improve the perceived quality for users.

@inproceedings{info3-inproceedings-2015-511, abstract = {Video streaming is the most popular application in today's mobile Internet and its growing demands and popularity put more and more load on cellular networks. In a recent trend to mitigate the cellular load, followed by many providers, users are offered to offload mobile connections to WiFi hotspots, which are predominately deployed in urban environments. In this work, we conduct a simulative performance evaluation of the impact of WiFi offloading on the Quality of Experience (QoE) of video streaming. The evaluation is based on connectivity measurements from a German city and uses a simple QoE model for estimating the perceived quality of video streaming. Our findings show that, despite its benefits for operators, offloading to WiFi has a negative impact on video streaming QoE for some users when 3G/4G coverage is available. Only in the case of 2G coverage, WiFi offloading can significantly improve the perceived quality for users.}, address = {London, UK}, author = {Burger, Valentin and Seufert, Michael and Kaup, Fabian and Wichtlhuber, Matthias and Hausheer, David and Tran-Gia, Phuoc}, booktitle = {IEEE Workshop on Quality of Experience-based Management for Future Internet Applications and Services (QoE-FI)}, keywords = {smartenit}, month = {06}, title = {Impact of WiFi Offloading on Video Streaming QoE in Urban Environments}, year = 2015 }

%0 Conference Paper %1 info3-inproceedings-2015-511 %A Burger, Valentin %A Seufert, Michael %A Kaup, Fabian %A Wichtlhuber, Matthias %A Hausheer, David %A Tran-Gia, Phuoc %B IEEE Workshop on Quality of Experience-based Management for Future Internet Applications and Services (QoE-FI) %C London, UK %D 2015 %T Impact of WiFi Offloading on Video Streaming QoE in Urban Environments %X Video streaming is the most popular application in today's mobile Internet and its growing demands and popularity put more and more load on cellular networks. In a recent trend to mitigate the cellular load, followed by many providers, users are offered to offload mobile connections to WiFi hotspots, which are predominately deployed in urban environments. In this work, we conduct a simulative performance evaluation of the impact of WiFi offloading on the Quality of Experience (QoE) of video streaming. The evaluation is based on connectivity measurements from a German city and uses a simple QoE model for estimating the perceived quality of video streaming. Our findings show that, despite its benefits for operators, offloading to WiFi has a negative impact on video streaming QoE for some users when 3G/4G coverage is available. Only in the case of 2G coverage, WiFi offloading can significantly improve the perceived quality for users.
Utilizing Home Router Caches to Augment CDNs towards Information-Centric Networking. Seufert, Michael; Burger, Valentin; Wamser, Florian; Tran-Gia, Phuoc; Moldovan, Christian; Hoßfeld, Tobias. In European Conference on Networks and Communications (EuCNC). Paris, France, 2015.
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To implement improved Quality of Service (QoS) and Quality of Experience (QoE) management for content-heavy services like video streaming, content has to be moved closer to the edge. The concept of information-centric networking (ICN) would be a prospective enabler but is currently not practically feasible yet. We propose a hierarchical caching architecture utilizing caches on home routers to augment existing content delivery network (CDN) infrastructure. This approach can be implemented via Software-defined Networking (SDN) and brings current CDNs closer towards ICN. Based on a simulation study, we confirm that our approach is able to serve content more locally, which results in QoS and QoE benefits for end users as well as inter-domain traffic savings for network operators.

@inproceedings{info3-inproceedings-2015-514, abstract = {To implement improved Quality of Service (QoS) and Quality of Experience (QoE) management for content-heavy services like video streaming, content has to be moved closer to the edge. The concept of information-centric networking (ICN) would be a prospective enabler but is currently not practically feasible yet. We propose a hierarchical caching architecture utilizing caches on home routers to augment existing content delivery network (CDN) infrastructure. This approach can be implemented via Software-defined Networking (SDN) and brings current CDNs closer towards ICN. Based on a simulation study, we confirm that our approach is able to serve content more locally, which results in QoS and QoE benefits for end users as well as inter-domain traffic savings for network operators.}, address = {Paris, France}, author = {Seufert, Michael and Burger, Valentin and Wamser, Florian and Tran-Gia, Phuoc and Moldovan, Christian and Hoßfeld, Tobias}, booktitle = {European Conference on Networks and Communications (EuCNC)}, keywords = {can}, month = {06}, title = {Utilizing Home Router Caches to Augment CDNs towards Information-Centric Networking}, year = 2015 }

%0 Conference Paper %1 info3-inproceedings-2015-514 %A Seufert, Michael %A Burger, Valentin %A Wamser, Florian %A Tran-Gia, Phuoc %A Moldovan, Christian %A Hoßfeld, Tobias %B European Conference on Networks and Communications (EuCNC) %C Paris, France %D 2015 %T Utilizing Home Router Caches to Augment CDNs towards Information-Centric Networking %X To implement improved Quality of Service (QoS) and Quality of Experience (QoE) management for content-heavy services like video streaming, content has to be moved closer to the edge. The concept of information-centric networking (ICN) would be a prospective enabler but is currently not practically feasible yet. We propose a hierarchical caching architecture utilizing caches on home routers to augment existing content delivery network (CDN) infrastructure. This approach can be implemented via Software-defined Networking (SDN) and brings current CDNs closer towards ICN. Based on a simulation study, we confirm that our approach is able to serve content more locally, which results in QoS and QoE benefits for end users as well as inter-domain traffic savings for network operators.
YoMoApp: a Tool for Analyzing QoE of YouTube HTTP Adaptive Streaming in Mobile Networks. Wamser, Florian; Seufert, Michael; Casas, Pedro; Irmer, Ralf; Tran-Gia, Phuoc; Schatz, Raimund. In European Conference on Networks and Communications (EuCNC). Paris, France, 2015.
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The performance of YouTube in mobile networks is crucial to network operators, who try to find a trade-off between cost-efficient handling of the huge traffic amounts and high perceived end-user Quality of Experience (QoE). This paper introduces YoMoApp (YouTube Performance Monitoring Application), an Android application, which passively monitors key performance indicators (KPIs) of YouTube adaptive video streaming on end-user smartphones. The monitored KPIs (i.e., player state/events, buffer, and video quality level) can be used to analyze the QoE of mobile YouTube video sessions. YoMoApp is a valuable tool to assess the performance of mobile networks with respect to YouTube traffic, as well as to develop optimizations and QoE models for mobile HTTP adaptive streaming. We test YoMoApp through real subjective QoE tests showing that the tool is accurate to capture the experience of end-users watching YouTube on smartphones.

@inproceedings{info3-inproceedings-2015-513, abstract = {The performance of YouTube in mobile networks is crucial to network operators, who try to find a trade-off between cost-efficient handling of the huge traffic amounts and high perceived end-user Quality of Experience (QoE). This paper introduces YoMoApp (YouTube Performance Monitoring Application), an Android application, which passively monitors key performance indicators (KPIs) of YouTube adaptive video streaming on end-user smartphones. The monitored KPIs (i.e., player state/events, buffer, and video quality level) can be used to analyze the QoE of mobile YouTube video sessions. YoMoApp is a valuable tool to assess the performance of mobile networks with respect to YouTube traffic, as well as to develop optimizations and QoE models for mobile HTTP adaptive streaming. We test YoMoApp through real subjective QoE tests showing that the tool is accurate to capture the experience of end-users watching YouTube on smartphones.}, address = {Paris, France}, author = {Wamser, Florian and Seufert, Michael and Casas, Pedro and Irmer, Ralf and Tran-Gia, Phuoc and Schatz, Raimund}, booktitle = {European Conference on Networks and Communications (EuCNC)}, keywords = {demobenefit}, month = {06}, title = {YoMoApp: a Tool for Analyzing QoE of YouTube HTTP Adaptive Streaming in Mobile Networks}, year = 2015 }

%0 Conference Paper %1 info3-inproceedings-2015-513 %A Wamser, Florian %A Seufert, Michael %A Casas, Pedro %A Irmer, Ralf %A Tran-Gia, Phuoc %A Schatz, Raimund %B European Conference on Networks and Communications (EuCNC) %C Paris, France %D 2015 %T YoMoApp: a Tool for Analyzing QoE of YouTube HTTP Adaptive Streaming in Mobile Networks %X The performance of YouTube in mobile networks is crucial to network operators, who try to find a trade-off between cost-efficient handling of the huge traffic amounts and high perceived end-user Quality of Experience (QoE). This paper introduces YoMoApp (YouTube Performance Monitoring Application), an Android application, which passively monitors key performance indicators (KPIs) of YouTube adaptive video streaming on end-user smartphones. The monitored KPIs (i.e., player state/events, buffer, and video quality level) can be used to analyze the QoE of mobile YouTube video sessions. YoMoApp is a valuable tool to assess the performance of mobile networks with respect to YouTube traffic, as well as to develop optimizations and QoE models for mobile HTTP adaptive streaming. We test YoMoApp through real subjective QoE tests showing that the tool is accurate to capture the experience of end-users watching YouTube on smartphones.
The Impact of Adaptation Strategies on Perceived Quality of HTTP Adaptive Streaming. Egger, Sebastian; Gardlo, Bruno; Seufert, Michael; Schatz, Raimund. In 1st Workshop on Design, Quality and Deployment of Adaptive Video Streaming (VideoNext). Sydney, Australia, 2014.
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Changing network conditions like bandwidth fluctuations and resulting bad user experience issues (e.g. video freezes) pose severe challenges to Internet video streaming. To address this problem, an increasing number of video services utilizes HTTP adaptive streaming (HAS). HAS enables service providers to improve Quality of Experience (QoE) and resource utilization by incorporating information from different layers. However, these adaptation possibilities of HAS also introduce new perceivable impairments such as the fluctuation of audiovisual quality levels over time, which in turn lead to novel QoE-related research questions.The main contribution of this paper is the formulation of open research questions as well as a thorough systematic user-centric analysis of different quality adaptation dimensions and strategies. The underlying data has been acquired through two crowdsourcing and one lab study. The results provide guidance w.r.t. which encoding dimensions are combined best for the creation of the adaptation set and what type of adaptation strategy should be used. Furthermore it provides insights on the impact of adaptation frequency and the true QoE gain of adaptation over stallings.

@inproceedings{info3-inproceedings-2014-507, abstract = {Changing network conditions like bandwidth fluctuations and resulting bad user experience issues (e.g. video freezes) pose severe challenges to Internet video streaming. To address this problem, an increasing number of video services utilizes HTTP adaptive streaming (HAS). HAS enables service providers to improve Quality of Experience (QoE) and resource utilization by incorporating information from different layers. However, these adaptation possibilities of HAS also introduce new perceivable impairments such as the fluctuation of audiovisual quality levels over time, which in turn lead to novel QoE-related research questions.The main contribution of this paper is the formulation of open research questions as well as a thorough systematic user-centric analysis of different quality adaptation dimensions and strategies. The underlying data has been acquired through two crowdsourcing and one lab study. The results provide guidance w.r.t. which encoding dimensions are combined best for the creation of the adaptation set and what type of adaptation strategy should be used. Furthermore it provides insights on the impact of adaptation frequency and the true QoE gain of adaptation over stallings.}, address = {Sydney, Australia}, author = {Egger, Sebastian and Gardlo, Bruno and Seufert, Michael and Schatz, Raimund}, booktitle = {1st Workshop on Design, Quality and Deployment of Adaptive Video Streaming (VideoNext)}, keywords = {sys:hidden:inproceedings}, month = 12, title = {The Impact of Adaptation Strategies on Perceived Quality of HTTP Adaptive Streaming}, year = 2014 }

%0 Conference Paper %1 info3-inproceedings-2014-507 %A Egger, Sebastian %A Gardlo, Bruno %A Seufert, Michael %A Schatz, Raimund %B 1st Workshop on Design, Quality and Deployment of Adaptive Video Streaming (VideoNext) %C Sydney, Australia %D 2014 %T The Impact of Adaptation Strategies on Perceived Quality of HTTP Adaptive Streaming %X Changing network conditions like bandwidth fluctuations and resulting bad user experience issues (e.g. video freezes) pose severe challenges to Internet video streaming. To address this problem, an increasing number of video services utilizes HTTP adaptive streaming (HAS). HAS enables service providers to improve Quality of Experience (QoE) and resource utilization by incorporating information from different layers. However, these adaptation possibilities of HAS also introduce new perceivable impairments such as the fluctuation of audiovisual quality levels over time, which in turn lead to novel QoE-related research questions.The main contribution of this paper is the formulation of open research questions as well as a thorough systematic user-centric analysis of different quality adaptation dimensions and strategies. The underlying data has been acquired through two crowdsourcing and one lab study. The results provide guidance w.r.t. which encoding dimensions are combined best for the creation of the adaptation set and what type of adaptation strategy should be used. Furthermore it provides insights on the impact of adaptation frequency and the true QoE gain of adaptation over stallings.
Assessing Effect Sizes of Influence Factors Towards a QoE Model for HTTP Adaptive Streaming. Hoßfeld, Tobias; Seufert, Michael; Sieber, Christian; Zinner, Thomas. In 6th International Workshop on Quality of Multimedia Experience (QoMEX). Singapore, 2014.
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HTTP Adaptive Streaming (HAS) is employed by more and more video streaming services in the Internet. It allows to adapt the downloaded video quality to the current network conditions, and thus, avoids stalling (i.e., playback interruptions) to the greatest possible extend. The adaptation of video streams is done by switching between different quality representation levels, which influences the user perceived quality of the video stream. In this work, the influence of several adaptation parameters, namely, switch amplitude (i.e., quality level difference), switching frequency, and recency effects, on Quality of Experience (QoE) is investigated. Therefore, crowdsourcing experiments were conducted in order to collect subjective ratings for different adaptation-related test conditions. The results of these subjective studies indicate the influence of the adaptation parameters, and based on these findings a simplified QoE model for HAS is presented, which only relies on the switch amplitude and the playback time of each layer.

@inproceedings{info3-inproceedings-2014-503, abstract = {HTTP Adaptive Streaming (HAS) is employed by more and more video streaming services in the Internet. It allows to adapt the downloaded video quality to the current network conditions, and thus, avoids stalling (i.e., playback interruptions) to the greatest possible extend. The adaptation of video streams is done by switching between different quality representation levels, which influences the user perceived quality of the video stream. In this work, the influence of several adaptation parameters, namely, switch amplitude (i.e., quality level difference), switching frequency, and recency effects, on Quality of Experience (QoE) is investigated. Therefore, crowdsourcing experiments were conducted in order to collect subjective ratings for different adaptation-related test conditions. The results of these subjective studies indicate the influence of the adaptation parameters, and based on these findings a simplified QoE model for HAS is presented, which only relies on the switch amplitude and the playback time of each layer.}, address = {Singapore}, author = {Hoßfeld, Tobias and Seufert, Michael and Sieber, Christian and Zinner, Thomas}, booktitle = {6th International Workshop on Quality of Multimedia Experience (QoMEX)}, keywords = {smartenit}, month = {09}, title = {Assessing Effect Sizes of Influence Factors Towards a QoE Model for HTTP Adaptive Streaming}, year = 2014 }

%0 Conference Paper %1 info3-inproceedings-2014-503 %A Hoßfeld, Tobias %A Seufert, Michael %A Sieber, Christian %A Zinner, Thomas %B 6th International Workshop on Quality of Multimedia Experience (QoMEX) %C Singapore %D 2014 %T Assessing Effect Sizes of Influence Factors Towards a QoE Model for HTTP Adaptive Streaming %X HTTP Adaptive Streaming (HAS) is employed by more and more video streaming services in the Internet. It allows to adapt the downloaded video quality to the current network conditions, and thus, avoids stalling (i.e., playback interruptions) to the greatest possible extend. The adaptation of video streams is done by switching between different quality representation levels, which influences the user perceived quality of the video stream. In this work, the influence of several adaptation parameters, namely, switch amplitude (i.e., quality level difference), switching frequency, and recency effects, on Quality of Experience (QoE) is investigated. Therefore, crowdsourcing experiments were conducted in order to collect subjective ratings for different adaptation-related test conditions. The results of these subjective studies indicate the influence of the adaptation parameters, and based on these findings a simplified QoE model for HAS is presented, which only relies on the switch amplitude and the playback time of each layer.
Socially-aware Management of New Overlay Applications Traffic - The Optimization Potentials of the SmartenIT Approach. Wajda, Krzysztof; Stankiewicz, Rafal; Dulinski, Zbigniew; Hoßfeld, Tobias; Seufert, Michael; Hausheer, David; Wichtlhuber, Matthias; Papafili, Ioanna; Dramitinos, Manos; Cruschelli, Paolo; Soursos, Sergios; Lapacz, Roman; Stiller, Burkhard. In 6th International Conference on Mobile Networks and Management (MONAMI). Würzburg, Germany, 2014.
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Today`s overlay-based mobile cloud applications determine a challenge to operators and cloud providers in terms of increasing traffic demands and energy costs. The social-aware management of overlay traffic is a promising optimization approach, which shows potential for improvements by exploiting social information. This paper identifies key stakeholders and their roles in the service provisioning value chain and outlines major markets and optimization potentials. Accordingly, two scenarios are developed: the end user focused scenario aming at increased QoE for end users, and the operator focused scenario targeting at the highest operating efficiency in terms of low cost and high revenue for the operator. The energy efficiency plays a major role as a key performance metric in both scenarios. SmartenIT`s socially-aware management approach is illustrated based on two example mechanisms for traffic optimization: the home router sharing mechanism (HORST) on the end user side, as well as the dynamic traffic management mechanism (DTM) on the operator side. The paper is concluded by a first sketch of SmartenIT`s architecture and its mapping to the two scenarios.

@inproceedings{info3-inproceedings-2014-501, abstract = {Today`s overlay-based mobile cloud applications determine a challenge to operators and cloud providers in terms of increasing traffic demands and energy costs. The social-aware management of overlay traffic is a promising optimization approach, which shows potential for improvements by exploiting social information. This paper identifies key stakeholders and their roles in the service provisioning value chain and outlines major markets and optimization potentials. Accordingly, two scenarios are developed: the end user focused scenario aming at increased QoE for end users, and the operator focused scenario targeting at the highest operating efficiency in terms of low cost and high revenue for the operator. The energy efficiency plays a major role as a key performance metric in both scenarios. SmartenIT`s socially-aware management approach is illustrated based on two example mechanisms for traffic optimization: the home router sharing mechanism (HORST) on the end user side, as well as the dynamic traffic management mechanism (DTM) on the operator side. The paper is concluded by a first sketch of SmartenIT`s architecture and its mapping to the two scenarios.}, address = {Würzburg, Germany}, author = {Wajda, Krzysztof and Stankiewicz, Rafal and Dulinski, Zbigniew and Hoßfeld, Tobias and Seufert, Michael and Hausheer, David and Wichtlhuber, Matthias and Papafili, Ioanna and Dramitinos, Manos and Cruschelli, Paolo and Soursos, Sergios and Lapacz, Roman and Stiller, Burkhard}, booktitle = {6th International Conference on Mobile Networks and Management (MONAMI)}, keywords = {smartenit}, month = {09}, title = {Socially-aware Management of New Overlay Applications Traffic - The Optimization Potentials of the SmartenIT Approach}, year = 2014 }

%0 Conference Paper %1 info3-inproceedings-2014-501 %A Wajda, Krzysztof %A Stankiewicz, Rafal %A Dulinski, Zbigniew %A Hoßfeld, Tobias %A Seufert, Michael %A Hausheer, David %A Wichtlhuber, Matthias %A Papafili, Ioanna %A Dramitinos, Manos %A Cruschelli, Paolo %A Soursos, Sergios %A Lapacz, Roman %A Stiller, Burkhard %B 6th International Conference on Mobile Networks and Management (MONAMI) %C Würzburg, Germany %D 2014 %T Socially-aware Management of New Overlay Applications Traffic - The Optimization Potentials of the SmartenIT Approach %X Today`s overlay-based mobile cloud applications determine a challenge to operators and cloud providers in terms of increasing traffic demands and energy costs. The social-aware management of overlay traffic is a promising optimization approach, which shows potential for improvements by exploiting social information. This paper identifies key stakeholders and their roles in the service provisioning value chain and outlines major markets and optimization potentials. Accordingly, two scenarios are developed: the end user focused scenario aming at increased QoE for end users, and the operator focused scenario targeting at the highest operating efficiency in terms of low cost and high revenue for the operator. The energy efficiency plays a major role as a key performance metric in both scenarios. SmartenIT`s socially-aware management approach is illustrated based on two example mechanisms for traffic optimization: the home router sharing mechanism (HORST) on the end user side, as well as the dynamic traffic management mechanism (DTM) on the operator side. The paper is concluded by a first sketch of SmartenIT`s architecture and its mapping to the two scenarios.
An Overview of Application Traffic Management Approaches: Challenges and Potential Extensions. Papafili, Ioanna; Wajda, Krzysztof; Lapacz, Roman; Predieri, Alessandro; Bocek, Thomas; Seufert, Michael. In 8th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS). Birmingham, UK, 2014.
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The Internet has seen a strong move to support overlay applications and services, which demand a coherent and integrated control in underlying heterogeneous networks in a scalable, resilient, and energy-efficient manner. To do so, a tighter integration of network management and overlay service functionality can lead to cross-layer optimization of operations and management, which is a promising approach and may offer a large business potential in operational perspectives for all players involved. Therefore, the objective of this paper is to present and discuss the impact of new paradigms such as cloud computing and software-defined networking which will play central role in the Future Internet, discuss major traffic trends and identify key challenges due to the adoption and operation of the new applications. Translating the key challenges to requirements for Future Internet traffic management mechanisms, the paper provides an extensive overview of existing mechanisms in literature, assesses them w.r.t. the aforementioned requirements, and qualitatively estimates the expected optimization potential and gain, as well as provides hint for their potential extension and exploitation within the challenging environment of the Future Internet.

@inproceedings{info3-inproceedings-2014-489, abstract = {The Internet has seen a strong move to support overlay applications and services, which demand a coherent and integrated control in underlying heterogeneous networks in a scalable, resilient, and energy-efficient manner. To do so, a tighter integration of network management and overlay service functionality can lead to cross-layer optimization of operations and management, which is a promising approach and may offer a large business potential in operational perspectives for all players involved. Therefore, the objective of this paper is to present and discuss the impact of new paradigms such as cloud computing and software-defined networking which will play central role in the Future Internet, discuss major traffic trends and identify key challenges due to the adoption and operation of the new applications. Translating the key challenges to requirements for Future Internet traffic management mechanisms, the paper provides an extensive overview of existing mechanisms in literature, assesses them w.r.t. the aforementioned requirements, and qualitatively estimates the expected optimization potential and gain, as well as provides hint for their potential extension and exploitation within the challenging environment of the Future Internet.}, address = {Birmingham, UK}, author = {Papafili, Ioanna and Wajda, Krzysztof and Lapacz, Roman and Predieri, Alessandro and Bocek, Thomas and Seufert, Michael}, booktitle = {8th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS)}, keywords = {smartenit}, month = {07}, title = {An Overview of Application Traffic Management Approaches: Challenges and Potential Extensions}, year = 2014 }

%0 Conference Paper %1 info3-inproceedings-2014-489 %A Papafili, Ioanna %A Wajda, Krzysztof %A Lapacz, Roman %A Predieri, Alessandro %A Bocek, Thomas %A Seufert, Michael %B 8th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS) %C Birmingham, UK %D 2014 %T An Overview of Application Traffic Management Approaches: Challenges and Potential Extensions %X The Internet has seen a strong move to support overlay applications and services, which demand a coherent and integrated control in underlying heterogeneous networks in a scalable, resilient, and energy-efficient manner. To do so, a tighter integration of network management and overlay service functionality can lead to cross-layer optimization of operations and management, which is a promising approach and may offer a large business potential in operational perspectives for all players involved. Therefore, the objective of this paper is to present and discuss the impact of new paradigms such as cloud computing and software-defined networking which will play central role in the Future Internet, discuss major traffic trends and identify key challenges due to the adoption and operation of the new applications. Translating the key challenges to requirements for Future Internet traffic management mechanisms, the paper provides an extensive overview of existing mechanisms in literature, assesses them w.r.t. the aforementioned requirements, and qualitatively estimates the expected optimization potential and gain, as well as provides hint for their potential extension and exploitation within the challenging environment of the Future Internet.
Crowdsourcing 2.0: Enhancing Execution Speed and Reliability of Web-based QoE Testing. Gardlo, Bruno; Egger, Sebastian; Seufert, Michael; Schatz, Raimund. In IEEE International Conference on Communications (ICC). Sydney, Australia, 2014.
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Since its introduction a few years ago, the concept of 'Crowdsourcing' has been heralded as highly attractive alternative approach towards evaluating the Quality of Experience (QoE) of networked multimedia services. The main reason is that, in comparison to traditional laboratory-based subjective quality testing, crowd-based QoE assessment over the Internet promises to be not only much more cost-effective (no lab facilities required, less cost per subject) but also much faster in terms of shorter campaign setup and turnaround times. However, the reliability of remote test subjects and consequently, the trustworthiness of study results is still an issue that prevents the widespread adoption of crowd-based QoE testing. Various ideas for improving user rating reliability and test efficiency have been proposed, with the majority of them relying on a posteriori analysis of results. However, such methods introduce a major lag that significantly affects efficiency of campaign execution. In this paper we address these shortcomings by introducing in momento methods for crowdsourced video QoE assessment, which yield improvements of results reliability by the factor two and campaign execution efficiency by the factor ten. The proposed in momento methods are applicable to existing crowd-based QoE testing approaches and suitable for a variety of service scenarios.

@inproceedings{info3-inproceedings-2014-488, abstract = {Since its introduction a few years ago, the concept of 'Crowdsourcing' has been heralded as highly attractive alternative approach towards evaluating the Quality of Experience (QoE) of networked multimedia services. The main reason is that, in comparison to traditional laboratory-based subjective quality testing, crowd-based QoE assessment over the Internet promises to be not only much more cost-effective (no lab facilities required, less cost per subject) but also much faster in terms of shorter campaign setup and turnaround times. However, the reliability of remote test subjects and consequently, the trustworthiness of study results is still an issue that prevents the widespread adoption of crowd-based QoE testing. Various ideas for improving user rating reliability and test efficiency have been proposed, with the majority of them relying on a posteriori analysis of results. However, such methods introduce a major lag that significantly affects efficiency of campaign execution. In this paper we address these shortcomings by introducing in momento methods for crowdsourced video QoE assessment, which yield improvements of results reliability by the factor two and campaign execution efficiency by the factor ten. The proposed in momento methods are applicable to existing crowd-based QoE testing approaches and suitable for a variety of service scenarios.}, address = {Sydney, Australia}, author = {Gardlo, Bruno and Egger, Sebastian and Seufert, Michael and Schatz, Raimund}, booktitle = {IEEE International Conference on Communications (ICC)}, keywords = {sys:hidden:inproceedings}, month = {06}, title = {Crowdsourcing 2.0: Enhancing Execution Speed and Reliability of Web-based QoE Testing}, year = 2014 }

%0 Conference Paper %1 info3-inproceedings-2014-488 %A Gardlo, Bruno %A Egger, Sebastian %A Seufert, Michael %A Schatz, Raimund %B IEEE International Conference on Communications (ICC) %C Sydney, Australia %D 2014 %T Crowdsourcing 2.0: Enhancing Execution Speed and Reliability of Web-based QoE Testing %X Since its introduction a few years ago, the concept of 'Crowdsourcing' has been heralded as highly attractive alternative approach towards evaluating the Quality of Experience (QoE) of networked multimedia services. The main reason is that, in comparison to traditional laboratory-based subjective quality testing, crowd-based QoE assessment over the Internet promises to be not only much more cost-effective (no lab facilities required, less cost per subject) but also much faster in terms of shorter campaign setup and turnaround times. However, the reliability of remote test subjects and consequently, the trustworthiness of study results is still an issue that prevents the widespread adoption of crowd-based QoE testing. Various ideas for improving user rating reliability and test efficiency have been proposed, with the majority of them relying on a posteriori analysis of results. However, such methods introduce a major lag that significantly affects efficiency of campaign execution. In this paper we address these shortcomings by introducing in momento methods for crowdsourced video QoE assessment, which yield improvements of results reliability by the factor two and campaign execution efficiency by the factor ten. The proposed in momento methods are applicable to existing crowd-based QoE testing approaches and suitable for a variety of service scenarios.
Gamification Framework for Personalized Surveys on Relationships in Online Social Networks. Seufert, Michael; Lorey, Karl; Hirth, Matthias; Hoßfeld, Tobias. In 1st International Workshop on Crowdsourcing and Gamification in the Cloud (CGCloud). Dresden, Germany, 2013.
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The estimation of psychological properties of relationships (e.g., popularity, influence, or trust) only from objective data in online social networks (OSNs) is a rather vague approach. A subjective assessment produces more accurate results, but it requires very complex and cumbersome surveys. The key contribution of this paper is a framework for personalized surveys on relationships in OSNs which follows a gamification approach. A game was developed and integrated into Facebook as an app, which makes it possible to obtain subjective ratings of users' relationships and objective data about the users, their interactions, and their social network. The combination of both subjective and objective data facilitates a deeper understanding of the psychological properties of relationships in OSNs, and lays the foundations for future research of subjective aspects within OSNs.

@inproceedings{info3-inproceedings-2013-484, abstract = {The estimation of psychological properties of relationships (e.g., popularity, influence, or trust) only from objective data in online social networks (OSNs) is a rather vague approach. A subjective assessment produces more accurate results, but it requires very complex and cumbersome surveys. The key contribution of this paper is a framework for personalized surveys on relationships in OSNs which follows a gamification approach. A game was developed and integrated into Facebook as an app, which makes it possible to obtain subjective ratings of users' relationships and objective data about the users, their interactions, and their social network. The combination of both subjective and objective data facilitates a deeper understanding of the psychological properties of relationships in OSNs, and lays the foundations for future research of subjective aspects within OSNs.}, address = {Dresden, Germany}, author = {Seufert, Michael and Lorey, Karl and Hirth, Matthias and Hoßfeld, Tobias}, booktitle = {1st International Workshop on Crowdsourcing and Gamification in the Cloud (CGCloud)}, keywords = {smartenit}, month = 12, title = {Gamification Framework for Personalized Surveys on Relationships in Online Social Networks}, year = 2013 }

%0 Conference Paper %1 info3-inproceedings-2013-484 %A Seufert, Michael %A Lorey, Karl %A Hirth, Matthias %A Hoßfeld, Tobias %B 1st International Workshop on Crowdsourcing and Gamification in the Cloud (CGCloud) %C Dresden, Germany %D 2013 %T Gamification Framework for Personalized Surveys on Relationships in Online Social Networks %X The estimation of psychological properties of relationships (e.g., popularity, influence, or trust) only from objective data in online social networks (OSNs) is a rather vague approach. A subjective assessment produces more accurate results, but it requires very complex and cumbersome surveys. The key contribution of this paper is a framework for personalized surveys on relationships in OSNs which follows a gamification approach. A game was developed and integrated into Facebook as an app, which makes it possible to obtain subjective ratings of users' relationships and objective data about the users, their interactions, and their social network. The combination of both subjective and objective data facilitates a deeper understanding of the psychological properties of relationships in OSNs, and lays the foundations for future research of subjective aspects within OSNs.
HORST - Home Router Sharing based on Trust. Seufert, Michael; Burger, Valentin; Hoßfeld, Tobias. In Workshop on Social-aware Economic Traffic Management for Overlay and Cloud Applications (SETM). Zurich, Switzerland, 2013.
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Today’s Internet services are increasingly accessed from mobile devices, thus being responsible for growing load in mobile networks. At the same time, more and more WiFi routers are deployed such that a dense coverage of WiFi is available. Results from different related works suggest that there is a high potential of reducing load on the mobile networks by offloading data to WiFi networks, thereby improving mobile users’ quality of experience (QoE) with Internet services. Additionally, the storage of the router could be used for content caching and delivery close to the end user, which is more energy efficient compared to classical content servers, and saves costs for network operators by reducing traffic between autonomous systems. Going one step beyond, we foresee that merging these approaches and augmenting them with social information from online social networks (OSNs) will result both in even less costs for network operators and increased QoE of end users. Therefore, we propose home router sharing based on trust (HORST) - a socially-aware traffic management solution which targets three popular use cases: data offloading to WiFi, content caching/prefetching, and content delivery.

@inproceedings{info3-inproceedings-2013-476, abstract = {Today’s Internet services are increasingly accessed from mobile devices, thus being responsible for growing load in mobile networks. At the same time, more and more WiFi routers are deployed such that a dense coverage of WiFi is available. Results from different related works suggest that there is a high potential of reducing load on the mobile networks by offloading data to WiFi networks, thereby improving mobile users’ quality of experience (QoE) with Internet services. Additionally, the storage of the router could be used for content caching and delivery close to the end user, which is more energy efficient compared to classical content servers, and saves costs for network operators by reducing traffic between autonomous systems. Going one step beyond, we foresee that merging these approaches and augmenting them with social information from online social networks (OSNs) will result both in even less costs for network operators and increased QoE of end users. Therefore, we propose home router sharing based on trust (HORST) - a socially-aware traffic management solution which targets three popular use cases: data offloading to WiFi, content caching/prefetching, and content delivery.}, address = {Zurich, Switzerland}, author = {Seufert, Michael and Burger, Valentin and Hoßfeld, Tobias}, booktitle = {Workshop on Social-aware Economic Traffic Management for Overlay and Cloud Applications (SETM)}, keywords = {can}, month = 10, title = {HORST - Home Router Sharing based on Trust}, year = 2013 }

%0 Conference Paper %1 info3-inproceedings-2013-476 %A Seufert, Michael %A Burger, Valentin %A Hoßfeld, Tobias %B Workshop on Social-aware Economic Traffic Management for Overlay and Cloud Applications (SETM) %C Zurich, Switzerland %D 2013 %T HORST - Home Router Sharing based on Trust %X Today’s Internet services are increasingly accessed from mobile devices, thus being responsible for growing load in mobile networks. At the same time, more and more WiFi routers are deployed such that a dense coverage of WiFi is available. Results from different related works suggest that there is a high potential of reducing load on the mobile networks by offloading data to WiFi networks, thereby improving mobile users’ quality of experience (QoE) with Internet services. Additionally, the storage of the router could be used for content caching and delivery close to the end user, which is more energy efficient compared to classical content servers, and saves costs for network operators by reducing traffic between autonomous systems. Going one step beyond, we foresee that merging these approaches and augmenting them with social information from online social networks (OSNs) will result both in even less costs for network operators and increased QoE of end users. Therefore, we propose home router sharing based on trust (HORST) - a socially-aware traffic management solution which targets three popular use cases: data offloading to WiFi, content caching/prefetching, and content delivery.
YOUQMON: A System for On-line Monitoring of YouTube QoE in Operational 3G Networks. Casas, Pedro; Seufert, Michael; Schatz, Raimund. In 31st International Symposium on Computer Performance, Modeling, Measurements and Evaluation (IFIP Performance). Vienna, Austria, 2013.
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YouTube is changing the way operators manage network performance monitoring. In this paper we present YOUQMON, a novel on-line monitoring system for assessing the Quality of Experience (QoE) undergone by HSPA/3G users watching YouTube videos, using network-layer measurements only. YOUQMON combines passive traffic analysis techniques to detect stalling events in YouTube video streams, with a QoE model to map stallings into a Mean Opinion Score reflecting the end-user experience. We evaluate the stalling detection performance of YOUQMON with hundreds of YouTube video streams, and present results showing the feasibility of performing real-time YouTube QoE monitoring in an operational mobile broadband network.

@inproceedings{info3-inproceedings-2013-472, abstract = {YouTube is changing the way operators manage network performance monitoring. In this paper we present YOUQMON, a novel on-line monitoring system for assessing the Quality of Experience (QoE) undergone by HSPA/3G users watching YouTube videos, using network-layer measurements only. YOUQMON combines passive traffic analysis techniques to detect stalling events in YouTube video streams, with a QoE model to map stallings into a Mean Opinion Score reflecting the end-user experience. We evaluate the stalling detection performance of YOUQMON with hundreds of YouTube video streams, and present results showing the feasibility of performing real-time YouTube QoE monitoring in an operational mobile broadband network.}, address = {Vienna, Austria}, author = {Casas, Pedro and Seufert, Michael and Schatz, Raimund}, booktitle = {31st International Symposium on Computer Performance, Modeling, Measurements and Evaluation (IFIP Performance)}, keywords = {demobenefit}, month = {09}, title = {YOUQMON: A System for On-line Monitoring of YouTube QoE in Operational 3G Networks}, year = 2013 }

%0 Conference Paper %1 info3-inproceedings-2013-472 %A Casas, Pedro %A Seufert, Michael %A Schatz, Raimund %B 31st International Symposium on Computer Performance, Modeling, Measurements and Evaluation (IFIP Performance) %C Vienna, Austria %D 2013 %T YOUQMON: A System for On-line Monitoring of YouTube QoE in Operational 3G Networks %X YouTube is changing the way operators manage network performance monitoring. In this paper we present YOUQMON, a novel on-line monitoring system for assessing the Quality of Experience (QoE) undergone by HSPA/3G users watching YouTube videos, using network-layer measurements only. YOUQMON combines passive traffic analysis techniques to detect stalling events in YouTube video streams, with a QoE model to map stallings into a Mean Opinion Score reflecting the end-user experience. We evaluate the stalling detection performance of YOUQMON with hundreds of YouTube video streams, and present results showing the feasibility of performing real-time YouTube QoE monitoring in an operational mobile broadband network.
Asking Costs Little? The Impact of Tasks in Video QoE Studies on User Behavior and User Ratings. Sackl, Andreas; Seufert, Michael; Hoßfeld, Tobias. In 4th International Workshop on Perceptual Quality of Systems (PQS). Vienna, Austria, 2013.
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Three crowdsourcing video QoE studies have been conducted to investigate the influence of tasks on user behavior and quality perception. Different dimensions of tasks have been applied to impaired video clips and their impact on task success, focus time, and QoE was measured. Our findings suggest that task presence or absence has no influence on the user. However, continuous tasks can improve the focus times of users, and hard tasks are suitable to filter unreliable participants.

@inproceedings{info3-inproceedings-2013-467, abstract = {Three crowdsourcing video QoE studies have been conducted to investigate the influence of tasks on user behavior and quality perception. Different dimensions of tasks have been applied to impaired video clips and their impact on task success, focus time, and QoE was measured. Our findings suggest that task presence or absence has no influence on the user. However, continuous tasks can improve the focus times of users, and hard tasks are suitable to filter unreliable participants.}, address = {Vienna, Austria}, author = {Sackl, Andreas and Seufert, Michael and Hoßfeld, Tobias}, booktitle = {4th International Workshop on Perceptual Quality of Systems (PQS)}, keywords = {oekonet}, month = {09}, title = {Asking Costs Little? The Impact of Tasks in Video QoE Studies on User Behavior and User Ratings}, year = 2013 }

%0 Conference Paper %1 info3-inproceedings-2013-467 %A Sackl, Andreas %A Seufert, Michael %A Hoßfeld, Tobias %B 4th International Workshop on Perceptual Quality of Systems (PQS) %C Vienna, Austria %D 2013 %T Asking Costs Little? The Impact of Tasks in Video QoE Studies on User Behavior and User Ratings %X Three crowdsourcing video QoE studies have been conducted to investigate the influence of tasks on user behavior and quality perception. Different dimensions of tasks have been applied to impaired video clips and their impact on task success, focus time, and QoE was measured. Our findings suggest that task presence or absence has no influence on the user. However, continuous tasks can improve the focus times of users, and hard tasks are suitable to filter unreliable participants.
Socially-Aware Traffic Management. Seufert, Michael; Darzanos, George; Burger, Valentin; Papafili, Ioanna; Hoßfeld, Tobias. In Workshop Sozioinformatik. Koblenz, Germany, 2013.
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Socially-aware traffic management exploits social signals to optimize traffic management in the Internet in terms of traffic load, energy consumption, or end-user satisfaction. Several use cases can benefit from socially-aware traffic management and the performance of overlay applications can be enhanced. In the talk we show interdisciplinary efforts between communication networks and social network analysis. Specifically, we give an overview on existing use cases and solutions, but also raise discussions at the workshop on additional benefits from the integration of social information into traffic management.

@inproceedings{info3-inproceedings-2013-471, abstract = {Socially-aware traffic management exploits social signals to optimize traffic management in the Internet in terms of traffic load, energy consumption, or end-user satisfaction. Several use cases can benefit from socially-aware traffic management and the performance of overlay applications can be enhanced. In the talk we show interdisciplinary efforts between communication networks and social network analysis. Specifically, we give an overview on existing use cases and solutions, but also raise discussions at the workshop on additional benefits from the integration of social information into traffic management.}, address = {Koblenz, Germany}, author = {Seufert, Michael and Darzanos, George and Burger, Valentin and Papafili, Ioanna and Hoßfeld, Tobias}, booktitle = {Workshop Sozioinformatik}, keywords = {smartenit}, month = {09}, title = {Socially-Aware Traffic Management}, year = 2013 }

%0 Conference Paper %1 info3-inproceedings-2013-471 %A Seufert, Michael %A Darzanos, George %A Burger, Valentin %A Papafili, Ioanna %A Hoßfeld, Tobias %B Workshop Sozioinformatik %C Koblenz, Germany %D 2013 %T Socially-Aware Traffic Management %X Socially-aware traffic management exploits social signals to optimize traffic management in the Internet in terms of traffic load, energy consumption, or end-user satisfaction. Several use cases can benefit from socially-aware traffic management and the performance of overlay applications can be enhanced. In the talk we show interdisciplinary efforts between communication networks and social network analysis. Specifically, we give an overview on existing use cases and solutions, but also raise discussions at the workshop on additional benefits from the integration of social information into traffic management.
Resilience in Enterprise Social Networks. Burger, Valentin; Hoßfeld, Tobias; Garcia, David; Seufert, Michael; Scholtes, Ingo; Hock, David. In Workshop Sozioinformatik 2013. Koblenz, Germany, 2013.
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The goal of human resource management is to ensure an effective company environment. Crucial for a good corporate culture is a comfortable atmosphere and positive social relationships between the employees. The interactions of the people and groups working in the company define their relationships and are reflected in the company's social network. Projections of such networks are Enterprise Social Networks which are more and more integrated in companies. These social networks can be a powerful tool to analyse the structure of a company and indicate potential problems. This extended abstract poses research questions to identify and quantify mechanisms that have an impact on the social network of a company to ensure resilience. To address these questions we make assumptions based on real-world observations for a subsequent model.

@inproceedings{info3-inproceedings-2013-473, abstract = {The goal of human resource management is to ensure an effective company environment. Crucial for a good corporate culture is a comfortable atmosphere and positive social relationships between the employees. The interactions of the people and groups working in the company define their relationships and are reflected in the company's social network. Projections of such networks are Enterprise Social Networks which are more and more integrated in companies. These social networks can be a powerful tool to analyse the structure of a company and indicate potential problems. This extended abstract poses research questions to identify and quantify mechanisms that have an impact on the social network of a company to ensure resilience. To address these questions we make assumptions based on real-world observations for a subsequent model.}, address = {Koblenz, Germany}, author = {Burger, Valentin and Hoßfeld, Tobias and Garcia, David and Seufert, Michael and Scholtes, Ingo and Hock, David}, booktitle = {Workshop Sozioinformatik 2013}, keywords = {sys:hidden:inproceedings}, month = {09}, title = {Resilience in Enterprise Social Networks}, year = 2013 }

%0 Conference Paper %1 info3-inproceedings-2013-473 %A Burger, Valentin %A Hoßfeld, Tobias %A Garcia, David %A Seufert, Michael %A Scholtes, Ingo %A Hock, David %B Workshop Sozioinformatik 2013 %C Koblenz, Germany %D 2013 %T Resilience in Enterprise Social Networks %X The goal of human resource management is to ensure an effective company environment. Crucial for a good corporate culture is a comfortable atmosphere and positive social relationships between the employees. The interactions of the people and groups working in the company define their relationships and are reflected in the company's social network. Projections of such networks are Enterprise Social Networks which are more and more integrated in companies. These social networks can be a powerful tool to analyse the structure of a company and indicate potential problems. This extended abstract poses research questions to identify and quantify mechanisms that have an impact on the social network of a company to ensure resilience. To address these questions we make assumptions based on real-world observations for a subsequent model.
To Pool or not to Pool: A Comparison of Temporal Pooling Methods for HTTP Adaptive Video Streaming. Seufert, Michael; Slanina, Martin; Egger, Sebastian; Kottkamp, Meik. In 5th International Workshop on Quality of Multimedia Experience (QoMEX). Klagenfurt, Austria, 2013.
- [ Abstract ]
- [ BibTeX ]
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- [ Download ]
Current objective video quality metrics typically estimate video quality for short video sequences (10 to 15 sec) of constant quality. However, customers of video services typically watch longer sequences of videos which are more and more delivered via adaptive streaming methods such as HTTP adaptive streaming (HAS). Typically a viewing session in such a setting contains several different video qualities over time. In order to express this in an overall score for the whole viewing session several temporal pooling methods have been proposed in the related work. Within this paper we set out to compare the performance of different temporal pooling methods for the prediction of Quality of Experience (QoE) for HTTP video streams with varying qualities. We perform this comparison based on ground truth rating data gathered in a crowdsourcing study in the context of the NGMN P-SERQU project. As input data for the models we use bjective video quality metrics such as PSNR, SSIM but also very basic inputs such as the bitrate of the clips only. Our results show that certain pooling methods perform clearly better than others. These results can help in identifying well performing temporal pooling methods in the context of HAS.

@inproceedings{info3-inproceedings-2013-465, abstract = {Current objective video quality metrics typically estimate video quality for short video sequences (10 to 15 sec) of constant quality. However, customers of video services typically watch longer sequences of videos which are more and more delivered via adaptive streaming methods such as HTTP adaptive streaming (HAS). Typically a viewing session in such a setting contains several different video qualities over time. In order to express this in an overall score for the whole viewing session several temporal pooling methods have been proposed in the related work. Within this paper we set out to compare the performance of different temporal pooling methods for the prediction of Quality of Experience (QoE) for HTTP video streams with varying qualities. We perform this comparison based on ground truth rating data gathered in a crowdsourcing study in the context of the NGMN P-SERQU project. As input data for the models we use bjective video quality metrics such as PSNR, SSIM but also very basic inputs such as the bitrate of the clips only. Our results show that certain pooling methods perform clearly better than others. These results can help in identifying well performing temporal pooling methods in the context of HAS.}, address = {Klagenfurt, Austria}, author = {Seufert, Michael and Slanina, Martin and Egger, Sebastian and Kottkamp, Meik}, booktitle = {5th International Workshop on Quality of Multimedia Experience (QoMEX)}, keywords = {sys:hidden:inproceedings}, month = {07}, title = {To Pool or not to Pool: A Comparison of Temporal Pooling Methods for HTTP Adaptive Video Streaming}, year = 2013 }

%0 Conference Paper %1 info3-inproceedings-2013-465 %A Seufert, Michael %A Slanina, Martin %A Egger, Sebastian %A Kottkamp, Meik %B 5th International Workshop on Quality of Multimedia Experience (QoMEX) %C Klagenfurt, Austria %D 2013 %T To Pool or not to Pool: A Comparison of Temporal Pooling Methods for HTTP Adaptive Video Streaming %X Current objective video quality metrics typically estimate video quality for short video sequences (10 to 15 sec) of constant quality. However, customers of video services typically watch longer sequences of videos which are more and more delivered via adaptive streaming methods such as HTTP adaptive streaming (HAS). Typically a viewing session in such a setting contains several different video qualities over time. In order to express this in an overall score for the whole viewing session several temporal pooling methods have been proposed in the related work. Within this paper we set out to compare the performance of different temporal pooling methods for the prediction of Quality of Experience (QoE) for HTTP video streams with varying qualities. We perform this comparison based on ground truth rating data gathered in a crowdsourcing study in the context of the NGMN P-SERQU project. As input data for the models we use bjective video quality metrics such as PSNR, SSIM but also very basic inputs such as the bitrate of the clips only. Our results show that certain pooling methods perform clearly better than others. These results can help in identifying well performing temporal pooling methods in the context of HAS.
Quality of Experience in Remote Virtual Desktop Services. Casas, Pedro; Seufert, Michael; Egger, Sebastian; Schatz, Raimund. In IFIP/IEEE International Workshop on Quality of Experience Centric Management (QCMan). Ghent, Belgium, 2013.
- [ Abstract ]
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Remote Virtual Desktop (RVD) services provide flexible and cost-effective means to deliver virtual PCs to end-users. RVD services have been traditionally deployed in enterprise LAN scenarios, where network performance is optimal and the Quality of Experience (QoE) undergone by its users is generally not an issue. However, the need for mobility of RVD users (e.g., remote office, home office, etc.) and the explosion of Cloud-based services have pushed RVD to WAN scenarios, and nowadays it is common to find RVD services running at large datacenters in the Cloud. In such a context, network delay and bandwidth are very dynamic and difficult to guarantee or even to control, and QoE becomes a real bottleneck. In this paper we present a complete study of the QoE undergone by 52 RVD users in controlled subjective lab tests. The study is performed on a dedicated RVD testbed based on Citrix technology, which is the de-facto RVD solution used in enterprise scenarios. The study permits not only to better understand the interplays between network performance (i.e., network delay and bandwidth) and QoE in RVD services, but also provides results on the behavior of RVD users when confronted to variable network conditions w.r.t. their behavior on standard local desktops.

@inproceedings{info3-inproceedings-2013-463, abstract = {Remote Virtual Desktop (RVD) services provide flexible and cost-effective means to deliver virtual PCs to end-users. RVD services have been traditionally deployed in enterprise LAN scenarios, where network performance is optimal and the Quality of Experience (QoE) undergone by its users is generally not an issue. However, the need for mobility of RVD users (e.g., remote office, home office, etc.) and the explosion of Cloud-based services have pushed RVD to WAN scenarios, and nowadays it is common to find RVD services running at large datacenters in the Cloud. In such a context, network delay and bandwidth are very dynamic and difficult to guarantee or even to control, and QoE becomes a real bottleneck. In this paper we present a complete study of the QoE undergone by 52 RVD users in controlled subjective lab tests. The study is performed on a dedicated RVD testbed based on Citrix technology, which is the de-facto RVD solution used in enterprise scenarios. The study permits not only to better understand the interplays between network performance (i.e., network delay and bandwidth) and QoE in RVD services, but also provides results on the behavior of RVD users when confronted to variable network conditions w.r.t. their behavior on standard local desktops.}, address = {Ghent, Belgium}, author = {Casas, Pedro and Seufert, Michael and Egger, Sebastian and Schatz, Raimund}, booktitle = {IFIP/IEEE International Workshop on Quality of Experience Centric Management (QCMan)}, keywords = {sys:hidden:inproceedings}, month = {05}, title = {Quality of Experience in Remote Virtual Desktop Services}, year = 2013 }

%0 Conference Paper %1 info3-inproceedings-2013-463 %A Casas, Pedro %A Seufert, Michael %A Egger, Sebastian %A Schatz, Raimund %B IFIP/IEEE International Workshop on Quality of Experience Centric Management (QCMan) %C Ghent, Belgium %D 2013 %T Quality of Experience in Remote Virtual Desktop Services %X Remote Virtual Desktop (RVD) services provide flexible and cost-effective means to deliver virtual PCs to end-users. RVD services have been traditionally deployed in enterprise LAN scenarios, where network performance is optimal and the Quality of Experience (QoE) undergone by its users is generally not an issue. However, the need for mobility of RVD users (e.g., remote office, home office, etc.) and the explosion of Cloud-based services have pushed RVD to WAN scenarios, and nowadays it is common to find RVD services running at large datacenters in the Cloud. In such a context, network delay and bandwidth are very dynamic and difficult to guarantee or even to control, and QoE becomes a real bottleneck. In this paper we present a complete study of the QoE undergone by 52 RVD users in controlled subjective lab tests. The study is performed on a dedicated RVD testbed based on Citrix technology, which is the de-facto RVD solution used in enterprise scenarios. The study permits not only to better understand the interplays between network performance (i.e., network delay and bandwidth) and QoE in RVD services, but also provides results on the behavior of RVD users when confronted to variable network conditions w.r.t. their behavior on standard local desktops.
Performance Optimization in Access Networks Using a Combined Control Strategy. Wamser, Florian; Hock, David; Seufert, Michael; Pries, Rastin; Tran-Gia, Phuoc. In 12th Würzburg Workshop on IP: ITG Workshop ’Visions of Future Generation Networks’ (Euroview). Würzburg, Germany, 2012.
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@inproceedings{info3-inproceedings-2012-454, address = {Würzburg, Germany}, author = {Wamser, Florian and Hock, David and Seufert, Michael and Pries, Rastin and Tran-Gia, Phuoc}, booktitle = {12th Würzburg Workshop on IP: ITG Workshop 'Visions of Future Generation Networks' (Euroview)}, keywords = {sys:hidden:inproceedings}, month = {07}, title = {Performance Optimization in Access Networks Using a Combined Control Strategy}, year = 2012 }

%0 Conference Paper %1 info3-inproceedings-2012-454 %A Wamser, Florian %A Hock, David %A Seufert, Michael %A Pries, Rastin %A Tran-Gia, Phuoc %B 12th Würzburg Workshop on IP: ITG Workshop 'Visions of Future Generation Networks' (Euroview) %C Würzburg, Germany %D 2012 %T Performance Optimization in Access Networks Using a Combined Control Strategy
Quantification of YouTube QoE via Crowdsourcing. Hoßfeld, Tobias; Schatz, Raimund; Seufert, Michael; Hirth, Matthias; Zinner, Thomas; Tran-Gia, Phuoc. In IEEE International Workshop on Multimedia Quality of Experience - Modeling, Evaluation, and Directions (MQoE). Dana Point, CA, USA, 2011.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
- [ Download ]
This paper addresses the challenge of assessing and modeling Quality of Experience (QoE) for online video services that are based on TCP-streaming. We present a dedicated QoE model for YouTube that takes into account the key influence factors (such as stalling events caused by network bottlenecks) that shape quality perception of this service. As second contribution, we propose a generic subjective QoE assessment methodology for multimedia applications (like online video) that is based on crowdsourcing - a highly cost-efficient, fast and flexible way of conducting user experiments. We demonstrate how our approach successfully leverages the inherent strengths of crowdsourcing while addressing critical aspects such as the reliability of the experimental data obtained. Our results suggest that, crowdsourcing is a highly effective QoE assessment method not only for online video, but also for a wide range of other current and future Internet applications.

@inproceedings{info3-inproceedings-2011-426, abstract = {This paper addresses the challenge of assessing and modeling Quality of Experience (QoE) for online video services that are based on TCP-streaming. We present a dedicated QoE model for YouTube that takes into account the key influence factors (such as stalling events caused by network bottlenecks) that shape quality perception of this service. As second contribution, we propose a generic subjective QoE assessment methodology for multimedia applications (like online video) that is based on crowdsourcing - a highly cost-efficient, fast and flexible way of conducting user experiments. We demonstrate how our approach successfully leverages the inherent strengths of crowdsourcing while addressing critical aspects such as the reliability of the experimental data obtained. Our results suggest that, crowdsourcing is a highly effective QoE assessment method not only for online video, but also for a wide range of other current and future Internet applications.}, address = {Dana Point, CA, USA}, author = {Hoßfeld, Tobias and Schatz, Raimund and Seufert, Michael and Hirth, Matthias and Zinner, Thomas and Tran-Gia, Phuoc}, booktitle = {IEEE International Workshop on Multimedia Quality of Experience - Modeling, Evaluation, and Directions (MQoE)}, keywords = {demobenefit}, month = 12, title = {Quantification of YouTube QoE via Crowdsourcing}, year = 2011 }

%0 Conference Paper %1 info3-inproceedings-2011-426 %A Hoßfeld, Tobias %A Schatz, Raimund %A Seufert, Michael %A Hirth, Matthias %A Zinner, Thomas %A Tran-Gia, Phuoc %B IEEE International Workshop on Multimedia Quality of Experience - Modeling, Evaluation, and Directions (MQoE) %C Dana Point, CA, USA %D 2011 %T Quantification of YouTube QoE via Crowdsourcing %X This paper addresses the challenge of assessing and modeling Quality of Experience (QoE) for online video services that are based on TCP-streaming. We present a dedicated QoE model for YouTube that takes into account the key influence factors (such as stalling events caused by network bottlenecks) that shape quality perception of this service. As second contribution, we propose a generic subjective QoE assessment methodology for multimedia applications (like online video) that is based on crowdsourcing - a highly cost-efficient, fast and flexible way of conducting user experiments. We demonstrate how our approach successfully leverages the inherent strengths of crowdsourcing while addressing critical aspects such as the reliability of the experimental data obtained. Our results suggest that, crowdsourcing is a highly effective QoE assessment method not only for online video, but also for a wide range of other current and future Internet applications.

Software/Demos

Let me Decrypt your Beauty: Real-time Prediction of Video Resolution and Bitrate for Encrypted Video Streaming. Wassermann, Sarah; Seufert, Michael; Casas, Pedro; Li, Gang; Kuang, Li. Paris, France, 2019, June.
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- [ EndNote ]
@misc{info3-software-2019-1, address = {Paris, France}, author = {Wassermann, Sarah and Seufert, Michael and Casas, Pedro and Li, Gang and Kuang, Li}, booktitle = {Network Traffic Measurement and Analysis Conference (TMA)}, keywords = {sys:hidden:software}, month = {06}, title = {Let me Decrypt your Beauty: Real-time Prediction of Video Resolution and Bitrate for Encrypted Video Streaming}, year = 2019 }

%0 Generic %1 info3-software-2019-1 %A Wassermann, Sarah %A Seufert, Michael %A Casas, Pedro %A Li, Gang %A Kuang, Li %B Network Traffic Measurement and Analysis Conference (TMA) %C Paris, France %D 2019 %T Let me Decrypt your Beauty: Real-time Prediction of Video Resolution and Bitrate for Encrypted Video Streaming
YouTube QoE Monitoring with YoMoApp: A Web-Based Data Interface for Researchers, Best Demo Award TMA 2018. Wamser, Florian; Wehner, Nikolas; Seufert, Michael; Casas, Pedro; Tran-Gia, Phuoc. 2018, June.
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@misc{info3-inproceedings-2018-52, author = {Wamser, Florian and Wehner, Nikolas and Seufert, Michael and Casas, Pedro and Tran-Gia, Phuoc}, booktitle = {018 Network Traffic Measurement and Analysis Conference (TMA)}, keywords = {sys:hidden:software}, month = {06}, title = {YouTube QoE Monitoring with YoMoApp: A Web-Based Data Interface for Researchers, Best Demo Award TMA 2018}, year = 2018 }

%0 Generic %1 info3-inproceedings-2018-52 %A Wamser, Florian %A Wehner, Nikolas %A Seufert, Michael %A Casas, Pedro %A Tran-Gia, Phuoc %B 018 Network Traffic Measurement and Analysis Conference (TMA) %D 2018 %T YouTube QoE Monitoring with YoMoApp: A Web-Based Data Interface for Researchers, Best Demo Award TMA 2018
App for Dynamic Crowdsourced QoE Studies of HTTP Adaptive Streaming on Mobile Devices. Seufert, Michael; Wehner, Nikolas; Casas, Pedro. Vienna, Austria, 2018, June.
- [ BibTeX ]
- [ EndNote ]
@misc{info3-software-2018-2, address = {Vienna, Austria}, author = {Seufert, Michael and Wehner, Nikolas and Casas, Pedro}, booktitle = {Network Traffic Measurement and Analysis Conference (TMA)}, keywords = {sys:hidden:software}, month = {06}, title = {App for Dynamic Crowdsourced QoE Studies of HTTP Adaptive Streaming on Mobile Devices}, year = 2018 }

%0 Generic %1 info3-software-2018-2 %A Seufert, Michael %A Wehner, Nikolas %A Casas, Pedro %B Network Traffic Measurement and Analysis Conference (TMA) %C Vienna, Austria %D 2018 %T App for Dynamic Crowdsourced QoE Studies of HTTP Adaptive Streaming on Mobile Devices
A Wrapper for Automated Measurements with YouTube’s Native App. Loh, Frank; Karagkioules, Theodoros; Seufert, Michael; Zeidler, Bernd; Tsilimantos, Dimitrios; Tran-Gia, Phuoc; Valentin, Stefan; Wamser, Florian. Taipei, Taiwan, 2018, April.
- [ Abstract ]
- [ BibTeX ]
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- [ Download ]
This demo introduces a wrapper used for automated measurements of mobile video streaming in the Android YouTube app. The difference to traditional measurement techniques is that the measurement is done with the native YouTube app as it is provided in the Google Play Store. In addition to bandwidth or packet loss detection, the QoE of the video stream can be measured and quantified. For this, the amount of quality changes, the current playtime, the buffer level, and statistics like video and audio format are captured. Thus, detailed relationships between network parameters and streaming behavior based on many factors can be detected within the native app available in the Play Store.

@misc{info3-demo-2018-1, abstract = {This demo introduces a wrapper used for automated measurements of mobile video streaming in the Android YouTube app. The difference to traditional measurement techniques is that the measurement is done with the native YouTube app as it is provided in the Google Play Store. In addition to bandwidth or packet loss detection, the QoE of the video stream can be measured and quantified. For this, the amount of quality changes, the current playtime, the buffer level, and statistics like video and audio format are captured. Thus, detailed relationships between network parameters and streaming behavior based on many factors can be detected within the native app available in the Play Store.}, address = {Taipei, Taiwan}, author = {Loh, Frank and Karagkioules, Theodoros and Seufert, Michael and Zeidler, Bernd and Tsilimantos, Dimitrios and Tran-Gia, Phuoc and Valentin, Stefan and Wamser, Florian}, booktitle = {IEEE/IFIP NOMS 2018}, keywords = {can}, month = {04}, title = {A Wrapper for Automated Measurements with YouTube’s Native App}, year = 2018 }

%0 Generic %1 info3-demo-2018-1 %A Loh, Frank %A Karagkioules, Theodoros %A Seufert, Michael %A Zeidler, Bernd %A Tsilimantos, Dimitrios %A Tran-Gia, Phuoc %A Valentin, Stefan %A Wamser, Florian %B IEEE/IFIP NOMS 2018 %C Taipei, Taiwan %D 2018 %T A Wrapper for Automated Measurements with YouTube’s Native App %X This demo introduces a wrapper used for automated measurements of mobile video streaming in the Android YouTube app. The difference to traditional measurement techniques is that the measurement is done with the native YouTube app as it is provided in the Google Play Store. In addition to bandwidth or packet loss detection, the QoE of the video stream can be measured and quantified. For this, the amount of quality changes, the current playtime, the buffer level, and statistics like video and audio format are captured. Thus, detailed relationships between network parameters and streaming behavior based on many factors can be detected within the native app available in the Play Store.
Dynamic Cloud Service Placement for Live Video Streaming with a Remote-Controlled Drone. Wamser, Florian; Loh, Frank; Bruschi, Roberto; Lago, Paolo; Seufert, Michael; Tran-Gia, Phuoc. Best Demo Award, Lisbon, Portugal, 2017, May.
- [ Abstract ]
- [ BibTeX ]
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- [ Download ]
The continuous growth of Internet content, applications and services has led to ever more demanding requirements in the networks. To meet this, there have been significant developments in the migration of applications and services towards the cloud. The cloud not only provides applications, but also offers dynamic adaptability, scalability, and optimization with respect to the location of the application by migrating storage and application containers. In particular, cloud services can typically be placed and orchestrated at a variety of locations in the cloud. This demonstration shows a dynamic placement of a cloud service with video streaming and real-time control commands for a remote-controlled drone. We control a drone with the help of a cloud service which, in addition to the control commands, also returns a camera image to the operator. The requirements of this cloud application are groundbreaking. The camera requires high data rates from the drone to the cloud and from the cloud to the operator, so that the image can be transmitted in acceptable quality. For the control of the drone, a short delay must also be given in the direction of the drone so that the control can be carried out in real time.

@misc{info3-demo-2017-1, abstract = {The continuous growth of Internet content, applications and services has led to ever more demanding requirements in the networks. To meet this, there have been significant developments in the migration of applications and services towards the cloud. The cloud not only provides applications, but also offers dynamic adaptability, scalability, and optimization with respect to the location of the application by migrating storage and application containers. In particular, cloud services can typically be placed and orchestrated at a variety of locations in the cloud. This demonstration shows a dynamic placement of a cloud service with video streaming and real-time control commands for a remote-controlled drone. We control a drone with the help of a cloud service which, in addition to the control commands, also returns a camera image to the operator. The requirements of this cloud application are groundbreaking. The camera requires high data rates from the drone to the cloud and from the cloud to the operator, so that the image can be transmitted in acceptable quality. For the control of the drone, a short delay must also be given in the direction of the drone so that the control can be carried out in real time.}, address = {Best Demo Award, Lisbon, Portugal}, author = {Wamser, Florian and Loh, Frank and Bruschi, Roberto and Lago, Paolo and Seufert, Michael and Tran-Gia, Phuoc}, booktitle = {15th IFIP/IEEE International Symposium on Integrated Network Management (IM)}, keywords = {can}, month = {05}, title = {Dynamic Cloud Service Placement for Live Video Streaming with a Remote-Controlled Drone}, year = 2017 }

%0 Generic %1 info3-demo-2017-1 %A Wamser, Florian %A Loh, Frank %A Bruschi, Roberto %A Lago, Paolo %A Seufert, Michael %A Tran-Gia, Phuoc %B 15th IFIP/IEEE International Symposium on Integrated Network Management (IM) %C Best Demo Award, Lisbon, Portugal %D 2017 %T Dynamic Cloud Service Placement for Live Video Streaming with a Remote-Controlled Drone %X The continuous growth of Internet content, applications and services has led to ever more demanding requirements in the networks. To meet this, there have been significant developments in the migration of applications and services towards the cloud. The cloud not only provides applications, but also offers dynamic adaptability, scalability, and optimization with respect to the location of the application by migrating storage and application containers. In particular, cloud services can typically be placed and orchestrated at a variety of locations in the cloud. This demonstration shows a dynamic placement of a cloud service with video streaming and real-time control commands for a remote-controlled drone. We control a drone with the help of a cloud service which, in addition to the control commands, also returns a camera image to the operator. The requirements of this cloud application are groundbreaking. The camera requires high data rates from the drone to the cloud and from the cloud to the operator, so that the image can be transmitted in acceptable quality. For the control of the drone, a short delay must also be given in the direction of the drone so that the control can be carried out in real time.
WiFi Offloading and Socially Aware Prefetching on Augmented Home Routers. Petropoulos, George; Lareida, Andri; Soursos, Sergios; Seufert, Michael; Burger, Valentin; Stiller, Burkhard. Clearwater Beach, FL, USA, 2015, October.
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@misc{info3-software-2015-25, address = {Clearwater Beach, FL, USA}, author = {Petropoulos, George and Lareida, Andri and Soursos, Sergios and Seufert, Michael and Burger, Valentin and Stiller, Burkhard}, booktitle = {40th Annual IEEE Conference on Local Computer Networks (LCN), Best Demo Award}, keywords = {sys:hidden:software}, month = 10, title = {WiFi Offloading and Socially Aware Prefetching on Augmented Home Routers}, year = 2015 }

%0 Generic %1 info3-software-2015-25 %A Petropoulos, George %A Lareida, Andri %A Soursos, Sergios %A Seufert, Michael %A Burger, Valentin %A Stiller, Burkhard %B 40th Annual IEEE Conference on Local Computer Networks (LCN), Best Demo Award %C Clearwater Beach, FL, USA %D 2015 %T WiFi Offloading and Socially Aware Prefetching on Augmented Home Routers
On the Monitoring of YouTube QoE in Cellular Networks from End-devices. Seufert, Michael; Wamser, Florian; Casas, Pedro; Irmer, Ralf; Tran-Gia, Phuoc; Schatz, Raimund. Paris, France, 2015, September.
- [ BibTeX ]
- [ EndNote ]
@misc{info3-software-2015-24, address = {Paris, France}, author = {Seufert, Michael and Wamser, Florian and Casas, Pedro and Irmer, Ralf and Tran-Gia, Phuoc and Schatz, Raimund}, booktitle = {Students Workshop (S3)}, keywords = {can}, month = {09}, title = {On the Monitoring of YouTube QoE in Cellular Networks from End-devices}, year = 2015 }

%0 Generic %1 info3-software-2015-24 %A Seufert, Michael %A Wamser, Florian %A Casas, Pedro %A Irmer, Ralf %A Tran-Gia, Phuoc %A Schatz, Raimund %B Students Workshop (S3) %C Paris, France %D 2015 %T On the Monitoring of YouTube QoE in Cellular Networks from End-devices
YoMoApp - Performance Monitoring of Mobile Networks. Wamser, Florian; Seufert, Michael; Tran-Gia, Phuoc; Irmer, Ralf; Casas, Pedro; Schatz, Raimund. Paris, France, 2015, June.
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- [ EndNote ]
@misc{info3-software-2015-23, address = {Paris, France}, author = {Wamser, Florian and Seufert, Michael and Tran-Gia, Phuoc and Irmer, Ralf and Casas, Pedro and Schatz, Raimund}, booktitle = {European Conference on Networks and Communications}, keywords = {can}, month = {06}, title = {YoMoApp - Performance Monitoring of Mobile Networks}, year = 2015 }

%0 Generic %1 info3-software-2015-23 %A Wamser, Florian %A Seufert, Michael %A Tran-Gia, Phuoc %A Irmer, Ralf %A Casas, Pedro %A Schatz, Raimund %B European Conference on Networks and Communications %C Paris, France %D 2015 %T YoMoApp - Performance Monitoring of Mobile Networks
Demonstrating the Benefit of Joint Application and Network Control Within a Wireless Access Network. Wamser, Florian; Hock, David; Seufert, Michael; Zinner, Thomas; Tran-Gia, Phuoc. Turin, Italy, 2013, April.
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- [ Download ]
@misc{info3-software-2013-16, address = {Turin, Italy}, author = {Wamser, Florian and Hock, David and Seufert, Michael and Zinner, Thomas and Tran-Gia, Phuoc}, booktitle = {2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)}, keywords = {sys:hidden:software}, month = {04}, title = {Demonstrating the Benefit of Joint Application and Network Control Within a Wireless Access Network}, year = 2013 }

%0 Generic %1 info3-software-2013-16 %A Wamser, Florian %A Hock, David %A Seufert, Michael %A Zinner, Thomas %A Tran-Gia, Phuoc %B 2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) %C Turin, Italy %D 2013 %T Demonstrating the Benefit of Joint Application and Network Control Within a Wireless Access Network
OC²E²AN: Optimized Control Center for Experience Enhancements in Access Networks. Hock, David; Wamser, Florian; Seufert, Michael; Pries, Rastin; Tran-Gia, Phuoc. Stuttgart, Germany, 2013, March.
- [ BibTeX ]
- [ EndNote ]
@misc{info3-software-2013-17, address = {Stuttgart, Germany}, author = {Hock, David and Wamser, Florian and Seufert, Michael and Pries, Rastin and Tran-Gia, Phuoc}, keywords = {sys:hidden:software}, month = {03}, title = {OC²E²AN: Optimized Control Center for Experience Enhancements in Access Networks}, year = 2013 }

%0 Generic %1 info3-software-2013-17 %A Hock, David %A Wamser, Florian %A Seufert, Michael %A Pries, Rastin %A Tran-Gia, Phuoc %C Stuttgart, Germany %D 2013 %T OC²E²AN: Optimized Control Center for Experience Enhancements in Access Networks
Performance Optimization in Access Networks Using a Combined Control Strategy. Wamser, Florian; Hock, David; Seufert, Michael; Pries, Rastin; Tran-Gia, Phuoc. Würzburg, Germany, 2012, July.
- [ BibTeX ]
- [ EndNote ]
@misc{info3-software-2012-11, address = {Würzburg, Germany}, author = {Wamser, Florian and Hock, David and Seufert, Michael and Pries, Rastin and Tran-Gia, Phuoc}, keywords = {sys:hidden:software}, month = {07}, title = {Performance Optimization in Access Networks Using a Combined Control Strategy}, year = 2012 }

%0 Generic %1 info3-software-2012-11 %A Wamser, Florian %A Hock, David %A Seufert, Michael %A Pries, Rastin %A Tran-Gia, Phuoc %C Würzburg, Germany %D 2012 %T Performance Optimization in Access Networks Using a Combined Control Strategy

Poster

How Good is your Mobile (Web) Surfing? SpeedIndex Inference from Encrypted Traffic. Wassermann, Sarah; Casas, Pedro; Seufert, Michael; Wehner, Nikolas; Schüler, Joshua; Hoßfeld, Tobias. New York City, NY, USA, 2020, August.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
We address the problem ofWeb QoE monitoring, in particular Speed Index (SI), from the Internet Service Provider (ISP) perspective, relying on in-network, passive measurements. Given the wide adoption of end-to-end encryption, we resort to machine-learning models to infer the SI of individual web-page loading sessions, using as input only packet-level data. Our study targets the analysis of SI in mobile devices, including smartphones and tablets. To the best of our knowledge, this is the first paper addressing the inference of SI from encrypted network traffic in mobile devices.

@misc{info3-poster-2020-1, abstract = {We address the problem ofWeb QoE monitoring, in particular Speed Index (SI), from the Internet Service Provider (ISP) perspective, relying on in-network, passive measurements. Given the wide adoption of end-to-end encryption, we resort to machine-learning models to infer the SI of individual web-page loading sessions, using as input only packet-level data. Our study targets the analysis of SI in mobile devices, including smartphones and tablets. To the best of our knowledge, this is the first paper addressing the inference of SI from encrypted network traffic in mobile devices.}, address = {New York City, NY, USA}, author = {Wassermann, Sarah and Casas, Pedro and Seufert, Michael and Wehner, Nikolas and Schüler, Joshua and Hoßfeld, Tobias}, booktitle = {ACM Special Interest Group on Data Communication Conference (SIGCOMM)}, keywords = {ucn}, month = {08}, title = {How Good is your Mobile (Web) Surfing? SpeedIndex Inference from Encrypted Traffic}, year = 2020 }

%0 Generic %1 info3-poster-2020-1 %A Wassermann, Sarah %A Casas, Pedro %A Seufert, Michael %A Wehner, Nikolas %A Schüler, Joshua %A Hoßfeld, Tobias %B ACM Special Interest Group on Data Communication Conference (SIGCOMM) %C New York City, NY, USA %D 2020 %T How Good is your Mobile (Web) Surfing? SpeedIndex Inference from Encrypted Traffic %X We address the problem ofWeb QoE monitoring, in particular Speed Index (SI), from the Internet Service Provider (ISP) perspective, relying on in-network, passive measurements. Given the wide adoption of end-to-end encryption, we resort to machine-learning models to infer the SI of individual web-page loading sessions, using as input only packet-level data. Our study targets the analysis of SI in mobile devices, including smartphones and tablets. To the best of our knowledge, this is the first paper addressing the inference of SI from encrypted network traffic in mobile devices.
Studying the Impact of the Content Selection Method on the Video QoE on Mobile Devices. Wehner, Nikolas; Mertinat, Nils; Seufert, Michael; Hoßfeld, Tobias. Athlone, Ireland, 2020, May.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
When conducting video QoE studies, participants are usually asked to rate the QoE of prepared test videos. However, participants are given no choice to select content, which they like or in which they are interested. This may cause annoyance or frustration when conducting the QoE study, which eventually might affect the QoE results of the study. The consequent question is whether the content liking has a direct impact on the submitted ratings by the participants and whether the freedom of choosing the video content in QoE studies results in better ratings. To investigate this research question, MCA, an existing framework for crowdsourced video testing, is extended and used in a pilot field study. MCA runs on mobile devices and allows users to watch the tested conditions of a QoE study within video content of their interest. The results of a QoE study with individual and dynamic content selection are compared to a QoE study with pre-selected contents. Moreover, this work includes a comparison to a previous QoE study for validation. As the previous study was conducted on desktop PCs, the MCA study further allows to identify differences in the stalling perception between studies on desktop PCs and mobile devices.

@misc{info3-poster-2020-2, abstract = {When conducting video QoE studies, participants are usually asked to rate the QoE of prepared test videos. However, participants are given no choice to select content, which they like or in which they are interested. This may cause annoyance or frustration when conducting the QoE study, which eventually might affect the QoE results of the study. The consequent question is whether the content liking has a direct impact on the submitted ratings by the participants and whether the freedom of choosing the video content in QoE studies results in better ratings. To investigate this research question, MCA, an existing framework for crowdsourced video testing, is extended and used in a pilot field study. MCA runs on mobile devices and allows users to watch the tested conditions of a QoE study within video content of their interest. The results of a QoE study with individual and dynamic content selection are compared to a QoE study with pre-selected contents. Moreover, this work includes a comparison to a previous QoE study for validation. As the previous study was conducted on desktop PCs, the MCA study further allows to identify differences in the stalling perception between studies on desktop PCs and mobile devices.}, address = {Athlone, Ireland}, author = {Wehner, Nikolas and Mertinat, Nils and Seufert, Michael and Hoßfeld, Tobias}, booktitle = {12th International Conference on Quality of Multimedia Experience (QoMEX)}, keywords = {ucn}, month = {05}, title = {Studying the Impact of the Content Selection Method on the Video QoE on Mobile Devices}, year = 2020 }

%0 Generic %1 info3-poster-2020-2 %A Wehner, Nikolas %A Mertinat, Nils %A Seufert, Michael %A Hoßfeld, Tobias %B 12th International Conference on Quality of Multimedia Experience (QoMEX) %C Athlone, Ireland %D 2020 %T Studying the Impact of the Content Selection Method on the Video QoE on Mobile Devices %X When conducting video QoE studies, participants are usually asked to rate the QoE of prepared test videos. However, participants are given no choice to select content, which they like or in which they are interested. This may cause annoyance or frustration when conducting the QoE study, which eventually might affect the QoE results of the study. The consequent question is whether the content liking has a direct impact on the submitted ratings by the participants and whether the freedom of choosing the video content in QoE studies results in better ratings. To investigate this research question, MCA, an existing framework for crowdsourced video testing, is extended and used in a pilot field study. MCA runs on mobile devices and allows users to watch the tested conditions of a QoE study within video content of their interest. The results of a QoE study with individual and dynamic content selection are compared to a QoE study with pre-selected contents. Moreover, this work includes a comparison to a previous QoE study for validation. As the previous study was conducted on desktop PCs, the MCA study further allows to identify differences in the stalling perception between studies on desktop PCs and mobile devices.
ViCrypt: Real-time, Fine-grained Prediction of Video Quality from Encrypted Streaming Traffic. Wassermann, Sarah; Seufert, Michael; Casas, Pedro; Li, Gang; Kuang, Li. Amsterdam, The Netherlands, 2019, October.
- [ BibTeX ]
- [ EndNote ]
@misc{info3-poster-2019-2, address = {Amsterdam, The Netherlands}, author = {Wassermann, Sarah and Seufert, Michael and Casas, Pedro and Li, Gang and Kuang, Li}, booktitle = {19th ACM Internet Measurement Conference (IMC)}, keywords = {ucn}, month = 10, title = {ViCrypt: Real-time, Fine-grained Prediction of Video Quality from Encrypted Streaming Traffic}, year = 2019 }

%0 Generic %1 info3-poster-2019-2 %A Wassermann, Sarah %A Seufert, Michael %A Casas, Pedro %A Li, Gang %A Kuang, Li %B 19th ACM Internet Measurement Conference (IMC) %C Amsterdam, The Netherlands %D 2019 %T ViCrypt: Real-time, Fine-grained Prediction of Video Quality from Encrypted Streaming Traffic
Beauty is in the Eye of the Smartphone Holder - A Data Driven Analysis of YouTube Mobile QoE. Wehner, Nikolas; Wassermann, Sarah; Casas, Pedro; Seufert, Michael; Wamser, Florian. Rome, Italy, 2018, September.
- [ BibTeX ]
- [ EndNote ]
@misc{info3-poster-2018-3, address = {Rome, Italy}, author = {Wehner, Nikolas and Wassermann, Sarah and Casas, Pedro and Seufert, Michael and Wamser, Florian}, booktitle = {14th International Conference on Network and Service Management (CNSM)}, keywords = {sys:hidden:poster}, month = {09}, title = {Beauty is in the Eye of the Smartphone Holder - A Data Driven Analysis of YouTube Mobile QoE}, year = 2018 }

%0 Generic %1 info3-poster-2018-3 %A Wehner, Nikolas %A Wassermann, Sarah %A Casas, Pedro %A Seufert, Michael %A Wamser, Florian %B 14th International Conference on Network and Service Management (CNSM) %C Rome, Italy %D 2018 %T Beauty is in the Eye of the Smartphone Holder - A Data Driven Analysis of YouTube Mobile QoE
What’s Up? Ein Frühwarnsystem für Kinder und Jugendliche mit Depression basierend auf der Analyse ihrer WhatsApp-Kommunikation. Eine Pilotstudie. Lüttke, Stefan; Schwind, Anika; Seufert, Michael; Wolf, Markus; Meurers, Detmar; Balle, Stefanie. Landau, Germany, 2018.
- [ BibTeX ]
- [ EndNote ]
@misc{info3-poster-2018-2, address = {Landau, Germany}, author = {Lüttke, Stefan and Schwind, Anika and Seufert, Michael and Wolf, Markus and Meurers, Detmar and Balle, Stefanie}, booktitle = {36th Symposium of the Section of Clinical Psychology and Psychotherapy of the German Society for Psychology}, keywords = {sys:hidden:poster}, title = {What’s Up? Ein Frühwarnsystem für Kinder und Jugendliche mit Depression basierend auf der Analyse ihrer WhatsApp-Kommunikation. Eine Pilotstudie.}, year = 2018 }

%0 Generic %1 info3-poster-2018-2 %A Lüttke, Stefan %A Schwind, Anika %A Seufert, Michael %A Wolf, Markus %A Meurers, Detmar %A Balle, Stefanie %B 36th Symposium of the Section of Clinical Psychology and Psychotherapy of the German Society for Psychology %C Landau, Germany %D 2018 %T What’s Up? Ein Frühwarnsystem für Kinder und Jugendliche mit Depression basierend auf der Analyse ihrer WhatsApp-Kommunikation. Eine Pilotstudie.
YouTube QoE Monitoring with YoMoApp: a Mobile App for Crowdsourced YouTube QoE Analysis. Seufert, Michael; Wehner, Nikolas; Wamser, Florian; Casas, Pedro. London, UK, 2017, November.
- [ BibTeX ]
- [ EndNote ]
@misc{info3-poster-2017-1, address = {London, UK}, author = {Seufert, Michael and Wehner, Nikolas and Wamser, Florian and Casas, Pedro}, booktitle = {ACM Internet Measurement Conference (IMC)}, keywords = {can}, month = 11, title = {YouTube QoE Monitoring with YoMoApp: a Mobile App for Crowdsourced YouTube QoE Analysis}, year = 2017 }

%0 Generic %1 info3-poster-2017-1 %A Seufert, Michael %A Wehner, Nikolas %A Wamser, Florian %A Casas, Pedro %B ACM Internet Measurement Conference (IMC) %C London, UK %D 2017 %T YouTube QoE Monitoring with YoMoApp: a Mobile App for Crowdsourced YouTube QoE Analysis
Impact of Intermediate Layer on Quality of Experience of HTTP Adaptive Streaming. Seufert, Michael; Hoßfeld, Tobias; Sieber, Christian. Barcelona, Spain, 2015, November.
- [ BibTeX ]
- [ EndNote ]
@misc{info3-poster-2015-40, address = {Barcelona, Spain}, author = {Seufert, Michael and Hoßfeld, Tobias and Sieber, Christian}, booktitle = {11th International Conference on Network and Service Management (CNSM)}, keywords = {can}, month = 11, title = {Impact of Intermediate Layer on Quality of Experience of HTTP Adaptive Streaming.}, year = 2015 }

%0 Generic %1 info3-poster-2015-40 %A Seufert, Michael %A Hoßfeld, Tobias %A Sieber, Christian %B 11th International Conference on Network and Service Management (CNSM) %C Barcelona, Spain %D 2015 %T Impact of Intermediate Layer on Quality of Experience of HTTP Adaptive Streaming.
On the Monitoring of YouTube QoE in Cellular Networks from End-devices. Seufert, Michael; Wamser, Florian; Casas, Pedro; Irmer, Ralf; Tran-Gia, Phuoc; Schatz, Raimund. Paris, France, 2015, September.
- [ BibTeX ]
- [ EndNote ]
@misc{info3-poster-2015-39, address = {Paris, France}, author = {Seufert, Michael and Wamser, Florian and Casas, Pedro and Irmer, Ralf and Tran-Gia, Phuoc and Schatz, Raimund}, booktitle = {Wireless of the Students, by the Students, and for the Students Workshop (S3)}, keywords = {can}, month = {09}, title = {On the Monitoring of YouTube QoE in Cellular Networks from End-devices}, year = 2015 }

%0 Generic %1 info3-poster-2015-39 %A Seufert, Michael %A Wamser, Florian %A Casas, Pedro %A Irmer, Ralf %A Tran-Gia, Phuoc %A Schatz, Raimund %B Wireless of the Students, by the Students, and for the Students Workshop (S3) %C Paris, France %D 2015 %T On the Monitoring of YouTube QoE in Cellular Networks from End-devices
Understanding YouTube QoE in Cellular Networks with YoMoApp - a QoE Monitoring Tool for YouTube Mobile. Wamser, Florian; Seufert, Michael; Casas, Pedro; Irmer, Ralf; Tran-Gia, Phuoc; Schatz, Raimund. 2015, September.
- [ BibTeX ]
- [ EndNote ]
@misc{info3-poster-2015-38, author = {Wamser, Florian and Seufert, Michael and Casas, Pedro and Irmer, Ralf and Tran-Gia, Phuoc and Schatz, Raimund}, booktitle = {21st Annual International Conference on Mobile Computing and Networking (MobiCom)}, keywords = {can}, month = {09}, title = {Understanding YouTube QoE in Cellular Networks with YoMoApp - a QoE Monitoring Tool for YouTube Mobile}, year = 2015 }

%0 Generic %1 info3-poster-2015-38 %A Wamser, Florian %A Seufert, Michael %A Casas, Pedro %A Irmer, Ralf %A Tran-Gia, Phuoc %A Schatz, Raimund %B 21st Annual International Conference on Mobile Computing and Networking (MobiCom) %D 2015 %T Understanding YouTube QoE in Cellular Networks with YoMoApp - a QoE Monitoring Tool for YouTube Mobile
HORST - Home Router Sharing based on Trust. Seufert, Michael; Burger, Valentin; Hoßfeld, Tobias. Zurich, Switzerland, 2013, October.
- [ BibTeX ]
- [ EndNote ]
@misc{info3-poster-2013-35, address = {Zurich, Switzerland}, author = {Seufert, Michael and Burger, Valentin and Hoßfeld, Tobias}, booktitle = {Workshop on Social-aware Economic Traffic Management for Overlay and Cloud Applications (SETM 2013)}, keywords = {can}, month = 10, title = {HORST - Home Router Sharing based on Trust}, year = 2013 }

%0 Generic %1 info3-poster-2013-35 %A Seufert, Michael %A Burger, Valentin %A Hoßfeld, Tobias %B Workshop on Social-aware Economic Traffic Management for Overlay and Cloud Applications (SETM 2013) %C Zurich, Switzerland %D 2013 %T HORST - Home Router Sharing based on Trust
Application and Quality of Experience Aware Resource Management in Wireless Access Networks. Wamser, Florian; Hock, David; Seufert, Michael; Pries, Rastin; Tran-Gia, Phuoc. Würzburg, Germany, 2012, March.
- [ BibTeX ]
- [ EndNote ]
@misc{info3-poster-2012-34, address = {Würzburg, Germany}, author = {Wamser, Florian and Hock, David and Seufert, Michael and Pries, Rastin and Tran-Gia, Phuoc}, booktitle = {EuroNF Summer School Modeling and Analysis of Novel Mechanisms in Future Internet Applications}, keywords = {sys:hidden:poster}, month = {03}, title = {Application and Quality of Experience Aware Resource Management in Wireless Access Networks}, year = 2012 }

%0 Generic %1 info3-poster-2012-34 %A Wamser, Florian %A Hock, David %A Seufert, Michael %A Pries, Rastin %A Tran-Gia, Phuoc %B EuroNF Summer School Modeling and Analysis of Novel Mechanisms in Future Internet Applications %C Würzburg, Germany %D 2012 %T Application and Quality of Experience Aware Resource Management in Wireless Access Networks

Technical Reports

White Paper on Crowdsourced Network and QoE Measurements – Definitions, Use Cases and Challenges. Technical Report (10.25972/OPUS-20232), . Hoßfeld, Tobias; Wunderer, Stefan; Beyer, André; Hall, Andrew; Schwind, Anika; Gassner, Christian; Guillemin, Fabrice; Wamser, Florian; Wascinski, Krzysztof; Hirth, Matthias; Seufert, Michael; Casas, Pedro; Tran-Gia, Phuoc; Robitza, Werner; Wascinski, Wojciech; Ben Houidi, Zied. Würzburg, 2020.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
- [ Download ]
The goal of the white paper at hand is as follows. The definitions of the terms build a framework for discussions around the hype topic ‘crowdsourcing’. This serves as a basis for differentiation and a consistent view from different perspectives on crowdsourced network measurements, with the goal to provide a commonly accepted definition in the community. The focus is on the context of mobile and fixed network operators, but also on measurements of different layers (network, application, user layer). In addition, the white paper shows the value of crowdsourcing for selected use cases, e.g., to improve QoE or regulatory issues. Finally, the major challenges and issues for researchers and practitioners are highlighted. This white paper is the outcome of the Würzburg seminar on “Crowdsourced Network and QoE Measurements” which took place from 25-26 September 2019 in Würzburg, Germany. International experts were invited from industry and academia. They are well known in their communities, having different backgrounds in crowdsourcing, mobile networks, network measurements, network performance, Quality of Service (QoS), and Quality of Experience (QoE). The discussions in the seminar focused on how crowdsourcing will support vendors, operators, and regulators to determine the Quality of Experience in new 5G networks that enable various new applications and network architectures. As a result of the discussions, the need for a white paper manifested, with the goal of providing a scientific discussion of the terms “crowdsourced network measurements” and “crowdsourced QoE measurements”, describing relevant use cases for such crowdsourced data, and its underlying challenges. During the seminar, those main topics were identified, intensively discussed in break-out groups, and brought back into the plenum several times. The outcome of the seminar is this white paper at hand which is – to our knowledge – the first one covering the topic of crowdsourced network and QoE measurements.

@techreport{info3-misc-2020-1, abstract = {The goal of the white paper at hand is as follows. The definitions of the terms build a framework for discussions around the hype topic ‘crowdsourcing’. This serves as a basis for differentiation and a consistent view from different perspectives on crowdsourced network measurements, with the goal to provide a commonly accepted definition in the community. The focus is on the context of mobile and fixed network operators, but also on measurements of different layers (network, application, user layer). In addition, the white paper shows the value of crowdsourcing for selected use cases, e.g., to improve QoE or regulatory issues. Finally, the major challenges and issues for researchers and practitioners are highlighted. This white paper is the outcome of the Würzburg seminar on “Crowdsourced Network and QoE Measurements” which took place from 25-26 September 2019 in Würzburg, Germany. International experts were invited from industry and academia. They are well known in their communities, having different backgrounds in crowdsourcing, mobile networks, network measurements, network performance, Quality of Service (QoS), and Quality of Experience (QoE). The discussions in the seminar focused on how crowdsourcing will support vendors, operators, and regulators to determine the Quality of Experience in new 5G networks that enable various new applications and network architectures. As a result of the discussions, the need for a white paper manifested, with the goal of providing a scientific discussion of the terms “crowdsourced network measurements” and “crowdsourced QoE measurements”, describing relevant use cases for such crowdsourced data, and its underlying challenges. During the seminar, those main topics were identified, intensively discussed in break-out groups, and brought back into the plenum several times. The outcome of the seminar is this white paper at hand which is – to our knowledge – the first one covering the topic of crowdsourced network and QoE measurements.}, author = {Hoßfeld, Tobias and Wunderer, Stefan and Beyer, André and Hall, Andrew and Schwind, Anika and Gassner, Christian and Guillemin, Fabrice and Wamser, Florian and Wascinski, Krzysztof and Hirth, Matthias and Seufert, Michael and Casas, Pedro and Tran-Gia, Phuoc and Robitza, Werner and Wascinski, Wojciech and Ben Houidi, Zied}, institution = {Würzburg}, keywords = {ua-net}, month = {03}, number = {10.25972/OPUS-20232}, title = {White Paper on Crowdsourced Network and QoE Measurements – Definitions, Use Cases and Challenges}, year = 2020 }

%0 Report %1 info3-misc-2020-1 %A Hoßfeld, Tobias %A Wunderer, Stefan %A Beyer, André %A Hall, Andrew %A Schwind, Anika %A Gassner, Christian %A Guillemin, Fabrice %A Wamser, Florian %A Wascinski, Krzysztof %A Hirth, Matthias %A Seufert, Michael %A Casas, Pedro %A Tran-Gia, Phuoc %A Robitza, Werner %A Wascinski, Wojciech %A Ben Houidi, Zied %D 2020 %N 10.25972/OPUS-20232 %T White Paper on Crowdsourced Network and QoE Measurements – Definitions, Use Cases and Challenges %X The goal of the white paper at hand is as follows. The definitions of the terms build a framework for discussions around the hype topic ‘crowdsourcing’. This serves as a basis for differentiation and a consistent view from different perspectives on crowdsourced network measurements, with the goal to provide a commonly accepted definition in the community. The focus is on the context of mobile and fixed network operators, but also on measurements of different layers (network, application, user layer). In addition, the white paper shows the value of crowdsourcing for selected use cases, e.g., to improve QoE or regulatory issues. Finally, the major challenges and issues for researchers and practitioners are highlighted. This white paper is the outcome of the Würzburg seminar on “Crowdsourced Network and QoE Measurements” which took place from 25-26 September 2019 in Würzburg, Germany. International experts were invited from industry and academia. They are well known in their communities, having different backgrounds in crowdsourcing, mobile networks, network measurements, network performance, Quality of Service (QoS), and Quality of Experience (QoE). The discussions in the seminar focused on how crowdsourcing will support vendors, operators, and regulators to determine the Quality of Experience in new 5G networks that enable various new applications and network architectures. As a result of the discussions, the need for a white paper manifested, with the goal of providing a scientific discussion of the terms “crowdsourced network measurements” and “crowdsourced QoE measurements”, describing relevant use cases for such crowdsourced data, and its underlying challenges. During the seminar, those main topics were identified, intensively discussed in break-out groups, and brought back into the plenum several times. The outcome of the seminar is this white paper at hand which is – to our knowledge – the first one covering the topic of crowdsourced network and QoE measurements.
A Survey of Cloud Services and Potential Applications of Social Awareness. Technical Report (496), . Seufert, Michael; Hoßfeld, Tobias; Sperb Machado, Guilherme; Bocek, Thomas; Biancani, Matteo; Cruschelli, Paolo; Lapacz, Roman; Darzanos, George; Papafili, Ioanna; Wajda, Krzysztof. University of Wuerzburg, 2015.
- [ BibTeX ]
- [ EndNote ]
@techreport{info3-techreport-2015-3, author = {Seufert, Michael and Hoßfeld, Tobias and Sperb Machado, Guilherme and Bocek, Thomas and Biancani, Matteo and Cruschelli, Paolo and Lapacz, Roman and Darzanos, George and Papafili, Ioanna and Wajda, Krzysztof}, institution = {University of Wuerzburg}, keywords = {can}, month = 11, number = 496, title = {A Survey of Cloud Services and Potential Applications of Social Awareness}, year = 2015 }

%0 Report %1 info3-techreport-2015-3 %A Seufert, Michael %A Hoßfeld, Tobias %A Sperb Machado, Guilherme %A Bocek, Thomas %A Biancani, Matteo %A Cruschelli, Paolo %A Lapacz, Roman %A Darzanos, George %A Papafili, Ioanna %A Wajda, Krzysztof %D 2015 %N 496 %T A Survey of Cloud Services and Potential Applications of Social Awareness
Best Practices and Recommendations for Crowdsourced QoE - Lessons learned from the Qualinet Task Force Crowdsourcing. Technical Report (Whitepaper), . Hoßfeld, Tobias; Hirth, Matthias; Redi, Judith; Mazza, Filippo; Korshunov, Pavel; Naderi, Babak; Seufert, Michael; Gardlo, Bruno; Egger, Sebastian; Keimel, Christian. COST Action IC1003 European Network on Quality of Experience in Multimedia Systems and Services (QUALINET), 2014.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
- [ Download ]
Crowdsourcing is a popular approach that outsources tasks via the Internet to a large number of users. Commercial crowdsourcing platforms provide a global pool of users employed for performing short and simple online tasks. For quality assessment of multimedia services and applications, crowdsourcing enables new possibilities by moving the subjective test into the crowd resulting in larger diversity of the test subjects, faster turnover of test campaigns, and reduced costs due to low reimbursement costs of the participants. Further, crowdsourcing allows easily addressing additional features like real-life environments. Crowdsourced quality assessment however is not a straight-forward implementation of existing subjective testing methodologies in an Internet-based environment. Additional challenges and differences to lab studies occur, in conceptual, technical, and motivational areas. For example, the test contents need to be transmitted to the user over the Internet; test users may have low resolution screens influencing the user experience; also users may not understand the test or do not execute the test carefully resulting in unreliable data. This white paper summarizes the recommendations and best practices for crowdsourced quality assessment of multimedia applications from the Qualinet Task Force on 'Crowdsourcing'. The European Network on Quality of Experience in Multimedia Systems and Services Qualinet (COST Action IC 1003, see www.qualinet.eu) established this task force in 2012. Since then it has grown to more then 30 members. The recommendation paper resulted from the experience in designing, implementing, and conducting crowdsourcing experiments as well as the analysis of the crowdsourced user ratings and context data. For understanding the impact of the crowdsourcing environment on QoE assessment and to derive a methodology and setup for crowdsourced QoE assessment, data from traditional lab experiments were compared with results from crowdsourcing experiments. Within the crowdsourcing task force, several different application domains and scientific questions were considered, among others: - video and image quality in general, - QoE for HTTP streaming and HTTP adaptive streaming, - selfie portrait images perception in a recruitment context, - privacy in HDR images and video, - compression of HDR images, - evaluation of 3D video, - image recognizability and aesthetic appeal, - multidimensional modeling of web QoE, - QoE factors of cloud storage services, - enabling eye tracking experiments using web technologies. From a crowdsourcing perspective, the following mechanisms and approaches were investigated which are relevant to understand for crowdsourced quality assessment. - Motivation and incentives, e.g., extrinsic motivation scale - Influence of payments - Impact of task design - Impact of crowdsourcing platforms selection - Reliability methods and screening mechanisms, monitoring result quality - Development of crowdsourcing frameworks and platforms As an outcome of the task force, scientific papers on best practices and crowdsourcing for QoE assessment in general were published. - Challenges in Crowd-based Video Quality Assessment, - Crowdsourcing in QoE Evaluation and best practices for QoE crowdtesting, - Survey of web-based crowdsourcing frameworks for subjective quality assessment. The scope of this white paper is to share practical issues and best practices in crowdsourcing experiments, to summarize the major lessons learned and to give key recommendations from the Qualinet task force. Thereby, the authors especially focus on aspects which are highly important in practice, but often not explained or discussed in scientific research papers for various reasons. Due to the large number of contributors, the document will not reflect the opinion of each individual person at all points. Nevertheless, each section of this white paper briefly formulates an important lesson learned.

@techreport{info3-article-2014-128, abstract = {Crowdsourcing is a popular approach that outsources tasks via the Internet to a large number of users. Commercial crowdsourcing platforms provide a global pool of users employed for performing short and simple online tasks. For quality assessment of multimedia services and applications, crowdsourcing enables new possibilities by moving the subjective test into the crowd resulting in larger diversity of the test subjects, faster turnover of test campaigns, and reduced costs due to low reimbursement costs of the participants. Further, crowdsourcing allows easily addressing additional features like real-life environments. Crowdsourced quality assessment however is not a straight-forward implementation of existing subjective testing methodologies in an Internet-based environment. Additional challenges and differences to lab studies occur, in conceptual, technical, and motivational areas. For example, the test contents need to be transmitted to the user over the Internet; test users may have low resolution screens influencing the user experience; also users may not understand the test or do not execute the test carefully resulting in unreliable data. This white paper summarizes the recommendations and best practices for crowdsourced quality assessment of multimedia applications from the Qualinet Task Force on 'Crowdsourcing'. The European Network on Quality of Experience in Multimedia Systems and Services Qualinet (COST Action IC 1003, see www.qualinet.eu) established this task force in 2012. Since then it has grown to more then 30 members. The recommendation paper resulted from the experience in designing, implementing, and conducting crowdsourcing experiments as well as the analysis of the crowdsourced user ratings and context data. For understanding the impact of the crowdsourcing environment on QoE assessment and to derive a methodology and setup for crowdsourced QoE assessment, data from traditional lab experiments were compared with results from crowdsourcing experiments. Within the crowdsourcing task force, several different application domains and scientific questions were considered, among others: - video and image quality in general, - QoE for HTTP streaming and HTTP adaptive streaming, - selfie portrait images perception in a recruitment context, - privacy in HDR images and video, - compression of HDR images, - evaluation of 3D video, - image recognizability and aesthetic appeal, - multidimensional modeling of web QoE, - QoE factors of cloud storage services, - enabling eye tracking experiments using web technologies. From a crowdsourcing perspective, the following mechanisms and approaches were investigated which are relevant to understand for crowdsourced quality assessment. - Motivation and incentives, e.g., extrinsic motivation scale - Influence of payments - Impact of task design - Impact of crowdsourcing platforms selection - Reliability methods and screening mechanisms, monitoring result quality - Development of crowdsourcing frameworks and platforms As an outcome of the task force, scientific papers on best practices and crowdsourcing for QoE assessment in general were published. - Challenges in Crowd-based Video Quality Assessment, - Crowdsourcing in QoE Evaluation and best practices for QoE crowdtesting, - Survey of web-based crowdsourcing frameworks for subjective quality assessment. The scope of this white paper is to share practical issues and best practices in crowdsourcing experiments, to summarize the major lessons learned and to give key recommendations from the Qualinet task force. Thereby, the authors especially focus on aspects which are highly important in practice, but often not explained or discussed in scientific research papers for various reasons. Due to the large number of contributors, the document will not reflect the opinion of each individual person at all points. Nevertheless, each section of this white paper briefly formulates an important lesson learned.}, author = {Hoßfeld, Tobias and Hirth, Matthias and Redi, Judith and Mazza, Filippo and Korshunov, Pavel and Naderi, Babak and Seufert, Michael and Gardlo, Bruno and Egger, Sebastian and Keimel, Christian}, institution = {COST Action IC1003 European Network on Quality of Experience in Multimedia Systems and Services (QUALINET)}, keywords = {sys:hidden:techreport}, month = 10, number = {Whitepaper}, title = {Best Practices and Recommendations for Crowdsourced QoE - Lessons learned from the Qualinet Task Force Crowdsourcing}, year = 2014 }

%0 Report %1 info3-article-2014-128 %A Hoßfeld, Tobias %A Hirth, Matthias %A Redi, Judith %A Mazza, Filippo %A Korshunov, Pavel %A Naderi, Babak %A Seufert, Michael %A Gardlo, Bruno %A Egger, Sebastian %A Keimel, Christian %D 2014 %N Whitepaper %T Best Practices and Recommendations for Crowdsourced QoE - Lessons learned from the Qualinet Task Force Crowdsourcing %X Crowdsourcing is a popular approach that outsources tasks via the Internet to a large number of users. Commercial crowdsourcing platforms provide a global pool of users employed for performing short and simple online tasks. For quality assessment of multimedia services and applications, crowdsourcing enables new possibilities by moving the subjective test into the crowd resulting in larger diversity of the test subjects, faster turnover of test campaigns, and reduced costs due to low reimbursement costs of the participants. Further, crowdsourcing allows easily addressing additional features like real-life environments. Crowdsourced quality assessment however is not a straight-forward implementation of existing subjective testing methodologies in an Internet-based environment. Additional challenges and differences to lab studies occur, in conceptual, technical, and motivational areas. For example, the test contents need to be transmitted to the user over the Internet; test users may have low resolution screens influencing the user experience; also users may not understand the test or do not execute the test carefully resulting in unreliable data. This white paper summarizes the recommendations and best practices for crowdsourced quality assessment of multimedia applications from the Qualinet Task Force on 'Crowdsourcing'. The European Network on Quality of Experience in Multimedia Systems and Services Qualinet (COST Action IC 1003, see www.qualinet.eu) established this task force in 2012. Since then it has grown to more then 30 members. The recommendation paper resulted from the experience in designing, implementing, and conducting crowdsourcing experiments as well as the analysis of the crowdsourced user ratings and context data. For understanding the impact of the crowdsourcing environment on QoE assessment and to derive a methodology and setup for crowdsourced QoE assessment, data from traditional lab experiments were compared with results from crowdsourcing experiments. Within the crowdsourcing task force, several different application domains and scientific questions were considered, among others: - video and image quality in general, - QoE for HTTP streaming and HTTP adaptive streaming, - selfie portrait images perception in a recruitment context, - privacy in HDR images and video, - compression of HDR images, - evaluation of 3D video, - image recognizability and aesthetic appeal, - multidimensional modeling of web QoE, - QoE factors of cloud storage services, - enabling eye tracking experiments using web technologies. From a crowdsourcing perspective, the following mechanisms and approaches were investigated which are relevant to understand for crowdsourced quality assessment. - Motivation and incentives, e.g., extrinsic motivation scale - Influence of payments - Impact of task design - Impact of crowdsourcing platforms selection - Reliability methods and screening mechanisms, monitoring result quality - Development of crowdsourcing frameworks and platforms As an outcome of the task force, scientific papers on best practices and crowdsourcing for QoE assessment in general were published. - Challenges in Crowd-based Video Quality Assessment, - Crowdsourcing in QoE Evaluation and best practices for QoE crowdtesting, - Survey of web-based crowdsourcing frameworks for subjective quality assessment. The scope of this white paper is to share practical issues and best practices in crowdsourcing experiments, to summarize the major lessons learned and to give key recommendations from the Qualinet task force. Thereby, the authors especially focus on aspects which are highly important in practice, but often not explained or discussed in scientific research papers for various reasons. Due to the large number of contributors, the document will not reflect the opinion of each individual person at all points. Nevertheless, each section of this white paper briefly formulates an important lesson learned.
Crowdsourced Subjective User Study Results on QoE Influence Factors of HTTP Adaptive Streaming. Technical Report (491), . Hoßfeld, Tobias; Seufert, Michael; Sieber, Christian; Zinner, Thomas. University of Wuerzburg, 2014.
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- [ Download ]
@techreport{info3-techreport-2014-265, author = {Hoßfeld, Tobias and Seufert, Michael and Sieber, Christian and Zinner, Thomas}, institution = {University of Wuerzburg}, keywords = {sys:hidden:techreport}, month = {07}, number = 491, title = {Crowdsourced Subjective User Study Results on QoE Influence Factors of HTTP Adaptive Streaming}, year = 2014 }

%0 Report %1 info3-techreport-2014-265 %A Hoßfeld, Tobias %A Seufert, Michael %A Sieber, Christian %A Zinner, Thomas %D 2014 %N 491 %T Crowdsourced Subjective User Study Results on QoE Influence Factors of HTTP Adaptive Streaming
A Survey on Quality of Experience of HTTP Adaptive Streaming. Technical Report (490), . Seufert, Michael; Egger, Sebastian; Slanina, Martin; Zinner, Thomas; Hoßfeld, Tobias; Tran-Gia, Phuoc. University of Wuerzburg, 2014.
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- [ EndNote ]
- [ Download ]
@techreport{info3-techreport-2014-264, author = {Seufert, Michael and Egger, Sebastian and Slanina, Martin and Zinner, Thomas and Hoßfeld, Tobias and Tran-Gia, Phuoc}, institution = {University of Wuerzburg}, keywords = {sys:hidden:techreport}, month = {04}, number = 490, title = {A Survey on Quality of Experience of HTTP Adaptive Streaming}, year = 2014 }

%0 Report %1 info3-techreport-2014-264 %A Seufert, Michael %A Egger, Sebastian %A Slanina, Martin %A Zinner, Thomas %A Hoßfeld, Tobias %A Tran-Gia, Phuoc %D 2014 %N 490 %T A Survey on Quality of Experience of HTTP Adaptive Streaming
Service Quality Definition and Measurement. Technical Report (1.0.4), . Wennesheimer, Michael; Robinson, Dave; De Vriendt, Johan; De Vleeschauwer, Danny; Bahr, Charles; Heise, Karl; Argyropoulos, Savvas; Feiten, Bernhard; Bilgic, Murat; Raiha, Tommi; Egger, Sebastian; Seufert, Michael; Slanina, Martin; Kottkamp, Meik; Gsödl, Harald; Ibl, Harald; García Pérez, Raquel. Next Generation Mobile Networks Alliance (NGMN), 2013.
- [ BibTeX ]
- [ EndNote ]
@techreport{info3-techreport-2013-266, author = {Wennesheimer, Michael and Robinson, Dave and De Vriendt, Johan and De Vleeschauwer, Danny and Bahr, Charles and Heise, Karl and Argyropoulos, Savvas and Feiten, Bernhard and Bilgic, Murat and Raiha, Tommi and Egger, Sebastian and Seufert, Michael and Slanina, Martin and Kottkamp, Meik and Gsödl, Harald and Ibl, Harald and García Pérez, Raquel}, institution = {Next Generation Mobile Networks Alliance (NGMN)}, keywords = {sys:hidden:techreport}, month = {08}, number = {1.0.4}, title = {Service Quality Definition and Measurement}, year = 2013 }

%0 Report %1 info3-techreport-2013-266 %A Wennesheimer, Michael %A Robinson, Dave %A De Vriendt, Johan %A De Vleeschauwer, Danny %A Bahr, Charles %A Heise, Karl %A Argyropoulos, Savvas %A Feiten, Bernhard %A Bilgic, Murat %A Raiha, Tommi %A Egger, Sebastian %A Seufert, Michael %A Slanina, Martin %A Kottkamp, Meik %A Gsödl, Harald %A Ibl, Harald %A García Pérez, Raquel %D 2013 %N 1.0.4 %T Service Quality Definition and Measurement
Transport Protocol Influences on YouTube QoE. Technical Report (482), . Hoßfeld, Tobias; Zinner, Thomas; Schatz, Raimund; Seufert, Michael; Tran-Gia, Phuoc. University of Wuerzburg, 2011.
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- [ EndNote ]
- [ Download ]
@techreport{info3-techreport-2011-258, author = {Hoßfeld, Tobias and Zinner, Thomas and Schatz, Raimund and Seufert, Michael and Tran-Gia, Phuoc}, institution = {University of Wuerzburg}, keywords = {sys:hidden:techreport}, month = {07}, number = 482, title = {Transport Protocol Influences on YouTube QoE}, year = 2011 }

%0 Report %1 info3-techreport-2011-258 %A Hoßfeld, Tobias %A Zinner, Thomas %A Schatz, Raimund %A Seufert, Michael %A Tran-Gia, Phuoc %D 2011 %N 482 %T Transport Protocol Influences on YouTube QoE

Tutorials

HTTP Adaptive Video Streaming and Quality of Experience. Seufert, Michael. Santander, Spain, 2015, September.
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- [ EndNote ]
@misc{info3-tutorial-2015-19, address = {Santander, Spain}, author = {Seufert, Michael}, booktitle = {7th EAI International Conference on Mobile Networks and Management (MONAMI)}, keywords = {sys:hidden:tutorial}, month = {09}, title = {HTTP Adaptive Video Streaming and Quality of Experience}, year = 2015 }

%0 Generic %1 info3-tutorial-2015-19 %A Seufert, Michael %B 7th EAI International Conference on Mobile Networks and Management (MONAMI) %C Santander, Spain %D 2015 %T HTTP Adaptive Video Streaming and Quality of Experience

Talks

Different Points of View: Impact of 3D Point Cloud Reduction on QoE of Rendered Images. Seufert, Michael. 12th International Conference on Quality of Multimedia Experience (QoMEX), Athlone, Ireland (virtual), 2020, May 27.
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@presentation{info3-presentation-2020-2, address = {12th International Conference on Quality of Multimedia Experience (QoMEX), Athlone, Ireland (virtual)}, author = {Seufert, Michael}, keywords = {ucn}, month = {05}, title = {Different Points of View: Impact of 3D Point Cloud Reduction on QoE of Rendered Images}, year = 2020 }

%0 Generic %1 info3-presentation-2020-2 %A Seufert, Michael %C 12th International Conference on Quality of Multimedia Experience (QoMEX), Athlone, Ireland (virtual) %D 2020 %T Different Points of View: Impact of 3D Point Cloud Reduction on QoE of Rendered Images
Quality of Experience and Access Network Traffic Management of HTTP Adaptive Video Streaming. Seufert, Michael. International Conference on Networked Systems (NetSys), KuVS Dissertation Award 2018, Munich, Germany, 2019, March 20.
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@presentation{info3-presentation-2019-2, address = {International Conference on Networked Systems (NetSys), KuVS Dissertation Award 2018, Munich, Germany}, author = {Seufert, Michael}, keywords = {sys:hidden:presentation}, month = {03}, title = {Quality of Experience and Access Network Traffic Management of HTTP Adaptive Video Streaming}, year = 2019 }

%0 Generic %1 info3-presentation-2019-2 %A Seufert, Michael %C International Conference on Networked Systems (NetSys), KuVS Dissertation Award 2018, Munich, Germany %D 2019 %T Quality of Experience and Access Network Traffic Management of HTTP Adaptive Video Streaming
QUICker or not? - an Empirical Analysis of QUIC vs TCP for Video Streaming QoE Provisioning. Seufert, Michael. 3rd International Workshop on Quality of Experience Management (QoE-Management), Paris, France, 2019, February 18.
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@presentation{info3-presentation-2019-1, address = {3rd International Workshop on Quality of Experience Management (QoE-Management), Paris, France}, author = {Seufert, Michael}, keywords = {sys:hidden:presentation}, month = {02}, title = {QUICker or not? - an Empirical Analysis of QUIC vs TCP for Video Streaming QoE Provisioning}, year = 2019 }

%0 Generic %1 info3-presentation-2019-1 %A Seufert, Michael %C 3rd International Workshop on Quality of Experience Management (QoE-Management), Paris, France %D 2019 %T QUICker or not? - an Empirical Analysis of QUIC vs TCP for Video Streaming QoE Provisioning
A Wrapper for Automatic Measurements with YouTube’s Native Android App. Seufert, Michael. Network Traffic Measurement and Analysis Conference (TMA), Vienna, Austria, 2018, June 28.
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@presentation{info3-presentation-2018-3, address = {Network Traffic Measurement and Analysis Conference (TMA), Vienna, Austria}, author = {Seufert, Michael}, keywords = {sys:hidden:presentation}, month = {06}, title = {A Wrapper for Automatic Measurements with YouTube’s Native Android App}, year = 2018 }

%0 Generic %1 info3-presentation-2018-3 %A Seufert, Michael %C Network Traffic Measurement and Analysis Conference (TMA), Vienna, Austria %D 2018 %T A Wrapper for Automatic Measurements with YouTube’s Native Android App
Applicability and Limitations of a Simple WiFi Hotspot Model for Cities. Seufert, Michael. 13th International Conference on Network and Service Management (CNSM). , Tokio, Japan, 2017, November 27.
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@presentation{info3-presentation-2017-11, address = {13th International Conference on Network and Service Management (CNSM). , Tokio, Japan}, author = {Seufert, Michael}, keywords = {sys:hidden:presentation}, month = 11, title = {Applicability and Limitations of a Simple WiFi Hotspot Model for Cities}, year = 2017 }

%0 Generic %1 info3-presentation-2017-11 %A Seufert, Michael %C 13th International Conference on Network and Service Management (CNSM). , Tokio, Japan %D 2017 %T Applicability and Limitations of a Simple WiFi Hotspot Model for Cities
Performance Evaluation of Selective Flow Monitoring in the ONOS Controller. Seufert, Michael. 4th International Workshop on Management of SDN and NFV Systems (ManSDN/NFV). , Tokio, Japan, 2017, November 26.
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- [ EndNote ]
@presentation{info3-presentation-2017-10, address = {4th International Workshop on Management of SDN and NFV Systems (ManSDN/NFV). , Tokio, Japan}, author = {Seufert, Michael}, keywords = {sys:hidden:presentation}, month = 11, title = {Performance Evaluation of Selective Flow Monitoring in the ONOS Controller}, year = 2017 }

%0 Generic %1 info3-presentation-2017-10 %A Seufert, Michael %C 4th International Workshop on Management of SDN and NFV Systems (ManSDN/NFV). , Tokio, Japan %D 2017 %T Performance Evaluation of Selective Flow Monitoring in the ONOS Controller
Performance Evaluation of Mobile Crowdsensing. Seufert, Michael. ITG FA 5.2 Workshop on Smart Cities, Lübeck, Germany, 2017, September 28.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
This talk intends to give an overview on Quality of Experience (QoE) monitoring for mobile video streaming, which is an important part of the QoE traffic management cycle. First, the talk recaps the concept of Quality of Experience of HTTP Adaptive Streaming (HAS), which is the current state-of-the-art video streaming technology. Afterwards, different approaches to QoE monitoring are introduced and discussed. Thereby, the talk provides details how the impact of QoE factors, in particular, the quality adaptation of HAS, can be assessed with crowdsourced subjective studies. Moreover, an example is given how to monitor network- and application-layer QoE factors and subjective feedback of end users with a smartphone video streaming app. Finally, the talk wants to stimulate discussions on open research questions of HAS and beyond.

@presentation{info3-presentation-2017-9, abstract = {This talk intends to give an overview on Quality of Experience (QoE) monitoring for mobile video streaming, which is an important part of the QoE traffic management cycle. First, the talk recaps the concept of Quality of Experience of HTTP Adaptive Streaming (HAS), which is the current state-of-the-art video streaming technology. Afterwards, different approaches to QoE monitoring are introduced and discussed. Thereby, the talk provides details how the impact of QoE factors, in particular, the quality adaptation of HAS, can be assessed with crowdsourced subjective studies. Moreover, an example is given how to monitor network- and application-layer QoE factors and subjective feedback of end users with a smartphone video streaming app. Finally, the talk wants to stimulate discussions on open research questions of HAS and beyond.}, address = {ITG FA 5.2 Workshop on Smart Cities, Lübeck, Germany}, author = {Seufert, Michael}, keywords = {can}, month = {09}, title = {Performance Evaluation of Mobile Crowdsensing}, year = 2017 }

%0 Generic %1 info3-presentation-2017-9 %A Seufert, Michael %C ITG FA 5.2 Workshop on Smart Cities, Lübeck, Germany %D 2017 %T Performance Evaluation of Mobile Crowdsensing %X This talk intends to give an overview on Quality of Experience (QoE) monitoring for mobile video streaming, which is an important part of the QoE traffic management cycle. First, the talk recaps the concept of Quality of Experience of HTTP Adaptive Streaming (HAS), which is the current state-of-the-art video streaming technology. Afterwards, different approaches to QoE monitoring are introduced and discussed. Thereby, the talk provides details how the impact of QoE factors, in particular, the quality adaptation of HAS, can be assessed with crowdsourced subjective studies. Moreover, an example is given how to monitor network- and application-layer QoE factors and subjective feedback of end users with a smartphone video streaming app. Finally, the talk wants to stimulate discussions on open research questions of HAS and beyond.
Concept and Implementation of Video QoE Measurements in a Mobile Broadband Testbed. Seufert, Michael. IEEE/IFIP Workshop on Mobile Network Measurement (MNM’17), Dublin, Ireland, 2017, June 20.
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- [ EndNote ]
@presentation{info3-presentation-2017-5, address = {IEEE/IFIP Workshop on Mobile Network Measurement (MNM’17), Dublin, Ireland}, author = {Seufert, Michael}, keywords = {sys:hidden:presentation}, month = {06}, title = {Concept and Implementation of Video QoE Measurements in a Mobile Broadband Testbed}, year = 2017 }

%0 Generic %1 info3-presentation-2017-5 %A Seufert, Michael %C IEEE/IFIP Workshop on Mobile Network Measurement (MNM’17), Dublin, Ireland %D 2017 %T Concept and Implementation of Video QoE Measurements in a Mobile Broadband Testbed
Research Activities Report for "Crowdsourcing TF" and "Managing Web & Cloud QoE TF". Seufert, Michael. 11th Qualinet General Meeting, Erfurt, Germany, 2017, May 30.
- [ BibTeX ]
- [ EndNote ]
@presentation{info3-presentation-2017-2, address = {11th Qualinet General Meeting, Erfurt, Germany}, author = {Seufert, Michael}, keywords = {can}, month = {05}, title = {Research Activities Report for "Crowdsourcing TF" and "Managing Web & Cloud QoE TF"}, year = 2017 }

%0 Generic %1 info3-presentation-2017-2 %A Seufert, Michael %C 11th Qualinet General Meeting, Erfurt, Germany %D 2017 %T Research Activities Report for "Crowdsourcing TF" and "Managing Web & Cloud QoE TF"
Is QUIC becoming the New TCP? On the Potential Impact of a New Protocol on Networked Multimedia QoE. Seufert, Michael. 11th International Conference on Quality of Multimedia Experience (QoMEX), Berlin, Germany, 2019, June 7.
- [ BibTeX ]
- [ EndNote ]
@presentation{info3-presentation-2019-5, address = {11th International Conference on Quality of Multimedia Experience (QoMEX), Berlin, Germany}, author = {Seufert, Michael}, keywords = {sys:hidden:presentation}, month = {06}, title = {Is QUIC becoming the New TCP? On the Potential Impact of a New Protocol on Networked Multimedia QoE}, year = 2019 }

%0 Generic %1 info3-presentation-2019-5 %A Seufert, Michael %C 11th International Conference on Quality of Multimedia Experience (QoMEX), Berlin, Germany %D 2019 %T Is QUIC becoming the New TCP? On the Potential Impact of a New Protocol on Networked Multimedia QoE
Fundamental Advantages of Considering Quality of Experience Distributions over Mean Opinion Scores. Seufert, Michael. 11th International Conference on Quality of Multimedia Experience (QoMEX), Berlin, Germany, 2019, June 5.
- [ BibTeX ]
- [ EndNote ]
@presentation{info3-presentation-2019-4, address = {11th International Conference on Quality of Multimedia Experience (QoMEX), Berlin, Germany}, author = {Seufert, Michael}, keywords = {sys:hidden:presentation}, month = {06}, title = {Fundamental Advantages of Considering Quality of Experience Distributions over Mean Opinion Scores}, year = 2019 }

%0 Generic %1 info3-presentation-2019-4 %A Seufert, Michael %C 11th International Conference on Quality of Multimedia Experience (QoMEX), Berlin, Germany %D 2019 %T Fundamental Advantages of Considering Quality of Experience Distributions over Mean Opinion Scores
Research Activities Report for "Managing Web & Cloud QoE TF". Seufert, Michael. 13th Qualinet General Meeting, Berlin, Germany, 2019, June 4.
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- [ EndNote ]
@presentation{info3-presentation-2019-3, address = {13th Qualinet General Meeting, Berlin, Germany}, author = {Seufert, Michael}, keywords = {sys:hidden:presentation}, month = {06}, title = {Research Activities Report for "Managing Web & Cloud QoE TF"}, year = 2019 }

%0 Generic %1 info3-presentation-2019-3 %A Seufert, Michael %C 13th Qualinet General Meeting, Berlin, Germany %D 2019 %T Research Activities Report for "Managing Web & Cloud QoE TF"
A Fair Share for All: Novel Adaptation Logic for QoE Fairness of HTTP Adaptive Video Streaming. Seufert, Michael. 14th International Conference on Network and Service Management (CNSM), Best Paper Award, Rome, Italy, 2018, September.
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@presentation{info3-presentation-2018-5, address = {14th International Conference on Network and Service Management (CNSM), Best Paper Award, Rome, Italy}, author = {Seufert, Michael}, keywords = {sys:hidden:presentation}, month = {09}, title = {A Fair Share for All: Novel Adaptation Logic for QoE Fairness of HTTP Adaptive Video Streaming}, year = 2018 }

%0 Generic %1 info3-presentation-2018-5 %A Seufert, Michael %C 14th International Conference on Network and Service Management (CNSM), Best Paper Award, Rome, Italy %D 2018 %T A Fair Share for All: Novel Adaptation Logic for QoE Fairness of HTTP Adaptive Video Streaming
Studying the Impact of HAS QoE Factors on the Standardized QoE Model P.1203. Seufert, Michael. 3rd Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE), Vienna, Austria, 2018, July.
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@presentation{info3-presentation-2018-4, address = {3rd Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE), Vienna, Austria}, author = {Seufert, Michael}, keywords = {sys:hidden:presentation}, month = {07}, title = {Studying the Impact of HAS QoE Factors on the Standardized QoE Model P.1203}, year = 2018 }

%0 Generic %1 info3-presentation-2018-4 %A Seufert, Michael %C 3rd Workshop on QoE-based Analysis and Management of Data Communication Networks (Internet-QoE), Vienna, Austria %D 2018 %T Studying the Impact of HAS QoE Factors on the Standardized QoE Model P.1203
Research Activities Report for "Crowdsourcing TF". Seufert, Michael. 12th Qualinet General Meeting, Pula, Italy, 2018, June.
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@presentation{info3-presentation-2018-2, address = {12th Qualinet General Meeting, Pula, Italy}, author = {Seufert, Michael}, keywords = {sys:hidden:presentation}, month = {06}, title = {Research Activities Report for "Crowdsourcing TF"}, year = 2018 }

%0 Generic %1 info3-presentation-2018-2 %A Seufert, Michael %C 12th Qualinet General Meeting, Pula, Italy %D 2018 %T Research Activities Report for "Crowdsourcing TF"
Quality of Experience and Access Network Traffic Management of HTTP Adaptive Video Streaming. Seufert, Michael. IEEE/IFIP Network Operations and Management Symposium (NOMS), Best Dissertation Award, Taipei, Taiwan, 2018, April.
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@presentation{info3-presentation-2018-1, address = {IEEE/IFIP Network Operations and Management Symposium (NOMS), Best Dissertation Award, Taipei, Taiwan}, author = {Seufert, Michael}, keywords = {sys:hidden:presentation}, month = {04}, title = {Quality of Experience and Access Network Traffic Management of HTTP Adaptive Video Streaming}, year = 2018 }

%0 Generic %1 info3-presentation-2018-1 %A Seufert, Michael %C IEEE/IFIP Network Operations and Management Symposium (NOMS), Best Dissertation Award, Taipei, Taiwan %D 2018 %T Quality of Experience and Access Network Traffic Management of HTTP Adaptive Video Streaming
Automated Decision Making Methods for the Multi-objective Optimization Task of Cloud Service Placement. Seufert, Michael. 1st International Workshop on Programmability for Cloud Networks and Applications (PROCON), Würzburg, Germany, 2016, September 12.
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@presentation{info3-presentation-2016-9, address = {1st International Workshop on Programmability for Cloud Networks and Applications (PROCON), Würzburg, Germany}, author = {Seufert, Michael}, keywords = {sys:hidden:presentation}, month = {09}, title = {Automated Decision Making Methods for the Multi-objective Optimization Task of Cloud Service Placement}, year = 2016 }

%0 Generic %1 info3-presentation-2016-9 %A Seufert, Michael %C 1st International Workshop on Programmability for Cloud Networks and Applications (PROCON), Würzburg, Germany %D 2016 %T Automated Decision Making Methods for the Multi-objective Optimization Task of Cloud Service Placement
One Shot Crowdtesting: Approaching the Extremes of Crowdsourced Subjective Quality Testing. Seufert, Michael. 5th ISCA/DEGA Workshop on Perceptual Quality of Systems (PQS), Berlin, Germany, 2016, August 31.
- [ BibTeX ]
- [ EndNote ]
@presentation{info3-presentation-2016-7, address = {5th ISCA/DEGA Workshop on Perceptual Quality of Systems (PQS), Berlin, Germany}, author = {Seufert, Michael}, keywords = {sys:hidden:presentation}, month = {08}, title = {One Shot Crowdtesting: Approaching the Extremes of Crowdsourced Subjective Quality Testing}, year = 2016 }

%0 Generic %1 info3-presentation-2016-7 %A Seufert, Michael %C 5th ISCA/DEGA Workshop on Perceptual Quality of Systems (PQS), Berlin, Germany %D 2016 %T One Shot Crowdtesting: Approaching the Extremes of Crowdsourced Subjective Quality Testing
Application-Layer Monitoring of QoE Parameters for Mobile YouTube Video Streaming in the Field. Seufert, Michael. IEEE 6th International Conference on Communications and Electronics (ICCE), Ha Long, Vietnam, 2016, July 29.
- [ BibTeX ]
- [ EndNote ]
@presentation{info3-presentation-2016-5, address = {IEEE 6th International Conference on Communications and Electronics (ICCE), Ha Long, Vietnam}, author = {Seufert, Michael}, keywords = {sys:hidden:presentation}, month = {07}, title = {Application-Layer Monitoring of QoE Parameters for Mobile YouTube Video Streaming in the Field}, year = 2016 }

%0 Generic %1 info3-presentation-2016-5 %A Seufert, Michael %C IEEE 6th International Conference on Communications and Electronics (ICCE), Ha Long, Vietnam %D 2016 %T Application-Layer Monitoring of QoE Parameters for Mobile YouTube Video Streaming in the Field
Adaptive Videostreaming and QoE. Seufert, Michael. HUST Spring School, Würzburg, Germany, 2016, February 23.
- [ BibTeX ]
- [ EndNote ]
@presentation{info3-presentation-2016-3, address = {HUST Spring School, Würzburg, Germany}, author = {Seufert, Michael}, keywords = {sys:hidden:presentation}, month = {02}, title = {Adaptive Videostreaming and QoE}, year = 2016 }

%0 Generic %1 info3-presentation-2016-3 %A Seufert, Michael %C HUST Spring School, Würzburg, Germany %D 2016 %T Adaptive Videostreaming and QoE
Taming QoE in Cellular Networks: from Subjective Lab Studies to Measurements in the Field. Seufert, Michael. 11th International Conference on Network and Service Management (CNSM), Barcelona, Spain, 2015, November 11.
- [ BibTeX ]
- [ EndNote ]
@presentation{info3-talk-2015-497, address = {11th International Conference on Network and Service Management (CNSM), Barcelona, Spain}, author = {Seufert, Michael}, keywords = {can}, month = 11, title = {Taming QoE in Cellular Networks: from Subjective Lab Studies to Measurements in the Field}, year = 2015 }

%0 Generic %1 info3-talk-2015-497 %A Seufert, Michael %C 11th International Conference on Network and Service Management (CNSM), Barcelona, Spain %D 2015 %T Taming QoE in Cellular Networks: from Subjective Lab Studies to Measurements in the Field
Utilizing Backhaul Capacities to Meet the Mobile Data Challenge. Burger, Valentin; Seufert, Michael; Tran-Gia, Phuoc. Joint ITG 5.2.1/5.2.4 Workshop on Cloud Networking, Tübingen, Germany, 2015, September 24.
- [ BibTeX ]
- [ EndNote ]
@presentation{info3-talk-2015-495, address = {Joint ITG 5.2.1/5.2.4 Workshop on Cloud Networking, Tübingen, Germany}, author = {Burger, Valentin and Seufert, Michael and Tran-Gia, Phuoc}, keywords = {sys:hidden:presentation}, month = {09}, title = {Utilizing Backhaul Capacities to Meet the Mobile Data Challenge}, year = 2015 }

%0 Generic %1 info3-talk-2015-495 %A Burger, Valentin %A Seufert, Michael %A Tran-Gia, Phuoc %C Joint ITG 5.2.1/5.2.4 Workshop on Cloud Networking, Tübingen, Germany %D 2015 %T Utilizing Backhaul Capacities to Meet the Mobile Data Challenge
Analysis of Group-based Communication in WhatsApp. Seufert, Michael. 7th EAI International Conference on Mobile Networks and Management (MONAMI), Santander, Spain, 2015, September 18.
- [ BibTeX ]
- [ EndNote ]
@presentation{info3-talk-2015-494, address = {7th EAI International Conference on Mobile Networks and Management (MONAMI), Santander, Spain}, author = {Seufert, Michael}, keywords = {smartenit}, month = {09}, title = {Analysis of Group-based Communication in WhatsApp}, year = 2015 }

%0 Generic %1 info3-talk-2015-494 %A Seufert, Michael %C 7th EAI International Conference on Mobile Networks and Management (MONAMI), Santander, Spain %D 2015 %T Analysis of Group-based Communication in WhatsApp
YouTube QoE on Mobile Devices: Subjective Analysis of Classical vs. Adaptive Video Streaming. Seufert, Michael. 6th International Workshop on Traffic Analysis and Characterization (TRAC), Dubrovnik, Croatia, 2015, August 25.
- [ BibTeX ]
- [ EndNote ]
@presentation{info3-talk-2015-493, address = {6th International Workshop on Traffic Analysis and Characterization (TRAC), Dubrovnik, Croatia}, author = {Seufert, Michael}, keywords = {can}, month = {08}, title = {YouTube QoE on Mobile Devices: Subjective Analysis of Classical vs. Adaptive Video Streaming}, year = 2015 }

%0 Generic %1 info3-talk-2015-493 %A Seufert, Michael %C 6th International Workshop on Traffic Analysis and Characterization (TRAC), Dubrovnik, Croatia %D 2015 %T YouTube QoE on Mobile Devices: Subjective Analysis of Classical vs. Adaptive Video Streaming
Assessing Effect Sizes of Influence Factors Towards a QoE Model for HTTP Adaptive Streaming. Seufert, Michael. 6th International Workshop on Quality of Multimedia Experience (QoMEX), Singapore, 2014, September 19.
- [ BibTeX ]
- [ EndNote ]
@presentation{info3-talk-2014-488, address = {6th International Workshop on Quality of Multimedia Experience (QoMEX), Singapore}, author = {Seufert, Michael}, keywords = {smartenit}, month = {09}, title = {Assessing Effect Sizes of Influence Factors Towards a QoE Model for HTTP Adaptive Streaming}, year = 2014 }

%0 Generic %1 info3-talk-2014-488 %A Seufert, Michael %C 6th International Workshop on Quality of Multimedia Experience (QoMEX), Singapore %D 2014 %T Assessing Effect Sizes of Influence Factors Towards a QoE Model for HTTP Adaptive Streaming
HTTP Adaptive Streaming. Seufert, Michael. 7th COST Qualinet General Meeting, Berlin, Germany, 2014, March 24.
- [ BibTeX ]
- [ EndNote ]
@presentation{info3-talk-2014-476, address = {7th COST Qualinet General Meeting, Berlin, Germany}, author = {Seufert, Michael}, keywords = {sys:hidden:presentation}, month = {03}, title = {HTTP Adaptive Streaming}, year = 2014 }

%0 Generic %1 info3-talk-2014-476 %A Seufert, Michael %C 7th COST Qualinet General Meeting, Berlin, Germany %D 2014 %T HTTP Adaptive Streaming
Socially-Aware Traffic Management. Seufert, Michael. Workshop Sozioinformatik, Koblenz, Germany, 2013, September 16.
- [ BibTeX ]
- [ EndNote ]
@presentation{info3-talk-2013-486, address = {Workshop Sozioinformatik, Koblenz, Germany}, author = {Seufert, Michael}, keywords = {smartenit}, month = {09}, title = {Socially-Aware Traffic Management}, year = 2013 }

%0 Generic %1 info3-talk-2013-486 %A Seufert, Michael %C Workshop Sozioinformatik, Koblenz, Germany %D 2013 %T Socially-Aware Traffic Management
EdgeNetworkCloudSim: Placement of Service Chains in Edge Clouds Using NetworkCloudSim. Seufert, Michael. 1st IEEE International Workshop on Network Programmability - From the Data Center to the Ground (NetFoG), Bologna, Italy, 2017, July 3.
- [ BibTeX ]
- [ EndNote ]
@presentation{info3-presentation-2017-6, address = {1st IEEE International Workshop on Network Programmability - From the Data Center to the Ground (NetFoG), Bologna, Italy}, author = {Seufert, Michael}, keywords = {sys:hidden:presentation}, month = {07}, title = {EdgeNetworkCloudSim: Placement of Service Chains in Edge Clouds Using NetworkCloudSim}, year = 2017 }

%0 Generic %1 info3-presentation-2017-6 %A Seufert, Michael %C 1st IEEE International Workshop on Network Programmability - From the Data Center to the Ground (NetFoG), Bologna, Italy %D 2017 %T EdgeNetworkCloudSim: Placement of Service Chains in Edge Clouds Using NetworkCloudSim
Unperturbed Video Streaming QoE Under Web Page Related Context Factors. Seufert, Michael. 9th International Conference on Quality of Multimedia Experience (QoMEX), Erfurt, Germany, 2017, June 2.
- [ BibTeX ]
- [ EndNote ]
@presentation{info3-presentation-2017-3, address = {9th International Conference on Quality of Multimedia Experience (QoMEX), Erfurt, Germany}, author = {Seufert, Michael}, keywords = {can}, month = {06}, title = {Unperturbed Video Streaming QoE Under Web Page Related Context Factors}, year = 2017 }

%0 Generic %1 info3-presentation-2017-3 %A Seufert, Michael %C 9th International Conference on Quality of Multimedia Experience (QoMEX), Erfurt, Germany %D 2017 %T Unperturbed Video Streaming QoE Under Web Page Related Context Factors
Unsupervised QoE Field Study for Mobile YouTube Video Streaming with YoMoApp. Seufert, Michael. 9th International Conference on Quality of Multimedia Experience (QoMEX), Erfurt, Germany, 2017, June 2.
- [ BibTeX ]
- [ EndNote ]
@presentation{info3-presentation-2017-4, address = {9th International Conference on Quality of Multimedia Experience (QoMEX), Erfurt, Germany}, author = {Seufert, Michael}, keywords = {can}, month = {06}, title = {Unsupervised QoE Field Study for Mobile YouTube Video Streaming with YoMoApp}, year = 2017 }

%0 Generic %1 info3-presentation-2017-4 %A Seufert, Michael %C 9th International Conference on Quality of Multimedia Experience (QoMEX), Erfurt, Germany %D 2017 %T Unsupervised QoE Field Study for Mobile YouTube Video Streaming with YoMoApp
Evaluating the Impact of WiFi Offloading on Mobile Users of HTTP Adaptive Video Streaming. Seufert, Michael. 5th IEEE International Workshop on Quality of Experience for Multimedia Communications (QoEMC), Washington, DC, USA, 2016, December 8.
- [ BibTeX ]
- [ EndNote ]
@presentation{info3-presentation-2016-10, address = {5th IEEE International Workshop on Quality of Experience for Multimedia Communications (QoEMC), Washington, DC, USA}, author = {Seufert, Michael}, keywords = {can}, month = 12, title = {Evaluating the Impact of WiFi Offloading on Mobile Users of HTTP Adaptive Video Streaming}, year = 2016 }

%0 Generic %1 info3-presentation-2016-10 %A Seufert, Michael %C 5th IEEE International Workshop on Quality of Experience for Multimedia Communications (QoEMC), Washington, DC, USA %D 2016 %T Evaluating the Impact of WiFi Offloading on Mobile Users of HTTP Adaptive Video Streaming
Test Effects in Crowdtesting. Seufert, Michael. Qualinet Crowdsourcing TF Meeting, Berlin, Germany, 2016, September 1.
- [ BibTeX ]
- [ EndNote ]
@presentation{info3-presentation-2016-8, address = {Qualinet Crowdsourcing TF Meeting, Berlin, Germany}, author = {Seufert, Michael}, keywords = {sys:hidden:presentation}, month = {09}, title = {Test Effects in Crowdtesting}, year = 2016 }

%0 Generic %1 info3-presentation-2016-8 %A Seufert, Michael %C Qualinet Crowdsourcing TF Meeting, Berlin, Germany %D 2016 %T Test Effects in Crowdtesting
Research Activities Report for "Crowdsourcing TF" and "Managing Web & Cloud QoE TF". Seufert, Michael. 10th Qualinet General Meeting, Lisbon, Portugal, 2016, June 9.
- [ BibTeX ]
- [ EndNote ]
@presentation{info3-presentation-2016-4, address = {10th Qualinet General Meeting, Lisbon, Portugal}, author = {Seufert, Michael}, keywords = {sys:hidden:presentation}, month = {06}, title = {Research Activities Report for "Crowdsourcing TF" and "Managing Web & Cloud QoE TF"}, year = 2016 }

%0 Generic %1 info3-presentation-2016-4 %A Seufert, Michael %C 10th Qualinet General Meeting, Lisbon, Portugal %D 2016 %T Research Activities Report for "Crowdsourcing TF" and "Managing Web & Cloud QoE TF"
Impact of Test Condition Selection in Adaptive Crowdsourcing Studies on Subjective Quality. Seufert, Michael. 8th International Conference on Quality of Multimedia Experience (QoMEX), Lisbon, Portugal, 2016, June 7.
- [ BibTeX ]
- [ EndNote ]
@presentation{info3-presentation-2016-2, address = {8th International Conference on Quality of Multimedia Experience (QoMEX), Lisbon, Portugal}, author = {Seufert, Michael}, keywords = {sys:hidden:presentation}, month = {06}, title = {Impact of Test Condition Selection in Adaptive Crowdsourcing Studies on Subjective Quality}, year = 2016 }

%0 Generic %1 info3-presentation-2016-2 %A Seufert, Michael %C 8th International Conference on Quality of Multimedia Experience (QoMEX), Lisbon, Portugal %D 2016 %T Impact of Test Condition Selection in Adaptive Crowdsourcing Studies on Subjective Quality
Smart Cities. Seufert, Michael. Datev Trendscout, Nürnberg, Germany, 2015, May 5.
- [ BibTeX ]
- [ EndNote ]
@presentation{info3-talk-2015-491, address = {Datev Trendscout, Nürnberg, Germany}, author = {Seufert, Michael}, keywords = {sys:hidden:presentation}, month = {05}, title = {Smart Cities}, year = 2015 }

%0 Generic %1 info3-talk-2015-491 %A Seufert, Michael %C Datev Trendscout, Nürnberg, Germany %D 2015 %T Smart Cities
Gamification Framework for Personalized Surveys on Relationships in Online Social Networks. Seufert, Michael. 1st International Workshop on Crowdsourcing and Gamification in the Cloud (CGCloud), Dresden, Germany, 2013, December 9.
- [ BibTeX ]
- [ EndNote ]
@presentation{info3-talk-2013-487, address = {1st International Workshop on Crowdsourcing and Gamification in the Cloud (CGCloud), Dresden, Germany}, author = {Seufert, Michael}, keywords = {smartenit}, month = 12, title = {Gamification Framework for Personalized Surveys on Relationships in Online Social Networks}, year = 2013 }

%0 Generic %1 info3-talk-2013-487 %A Seufert, Michael %C 1st International Workshop on Crowdsourcing and Gamification in the Cloud (CGCloud), Dresden, Germany %D 2013 %T Gamification Framework for Personalized Surveys on Relationships in Online Social Networks
To Pool or not to Pool: A Comparison of Temporal Pooling Methods for HTTP Adaptive Video Streaming. Seufert, Michael. 5th International Workshop on Quality of Multimedia Experience (QoMEX), Klagenfurt, Austria, 2013, July 3.
- [ BibTeX ]
- [ EndNote ]
@presentation{info3-talk-2013-485, address = {5th International Workshop on Quality of Multimedia Experience (QoMEX), Klagenfurt, Austria}, author = {Seufert, Michael}, keywords = {sys:hidden:presentation}, month = {07}, title = {To Pool or not to Pool: A Comparison of Temporal Pooling Methods for HTTP Adaptive Video Streaming}, year = 2013 }

%0 Generic %1 info3-talk-2013-485 %A Seufert, Michael %C 5th International Workshop on Quality of Multimedia Experience (QoMEX), Klagenfurt, Austria %D 2013 %T To Pool or not to Pool: A Comparison of Temporal Pooling Methods for HTTP Adaptive Video Streaming

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