- Access Networks

Research Area

Research Area: Access Networks

We deal within the CAN group with the research field of "Access Networks".

Access networks represent a very focused area in the research field of communication networks. In access networks, there are important communication paradigms that are subject of research in the CAN group. We examine the performance of communication processes and principles with means of modeling and performance analysis.

Study on Wifi Offloading

WiFi offloading is a current trend to cope with the demands of mobile users and the load on cellular networks. It allows providers to handle the traffic in well-dimensioned fixed networks and thereby save costs. In addition, end users can benefit from higher throughput and avoid exceeding their data plan.

We develop simulative and analytic models to investigate the potential of WiFi offloading to mitigate load of cellular networks. We evaluate its impact on QoE and energy efficiency for video streaming applications.

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.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
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.
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.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
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.
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.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
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.
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.
- [ BibTeX ]
- [ EndNote ]
@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
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.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
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.
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.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
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.
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.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
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.

Application Aware Networking

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.

Using analytic and simulative approaches, we conduct analysis methods for network operators to quantify the performance gains of resource allocation algorithms that implement the application-aware concept.

Publications

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.
- [ BibTeX ]
- [ EndNote ]
@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
Machine Learning Based Study of QoE Metrics in Twitch. tv Live Streaming. Loh, Frank; Hildebrand, Kathrin; Wamser, Florian; Geißler, Stefan; Hoßfeld, Tobias. In IEEE/IFIP Network Operations and Management Symposium (NOMS). 2023.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
Video streaming generates most network traffic in today’s Internet. For that reason, video on demand streaming is researched heavily in recent years, and many traffic monitoring mechanisms, flow and stream models, and models to predict the user perceived quality are well established. However, the quickly growing live streaming sector is not considered in these Quality of Experience models and not even the relation between network traffic and playback quality has been studied so far, forming a gap in literature. For that reason, we investigate Twitch.tv streaming as one of the largest live streaming platforms based on a large dataset and investigate the possibility to predict live streaming quality based on uplink request information. We apply approaches that are well studied for on demand streaming to predict quality changes, playback quality, and video interruption events as the most important metrics impairing user perceived quality. In this context, we answer whether these models are suitable for live streaming, if small changes are sufficient for satisfactory prediction results, or if fundamental changes and new models are required.

@inproceedings{info3-inproceedings-2023-17, abstract = {Video streaming generates most network traffic in today’s Internet. For that reason, video on demand streaming is researched heavily in recent years, and many traffic monitoring mechanisms, flow and stream models, and models to predict the user perceived quality are well established. However, the quickly growing live streaming sector is not considered in these Quality of Experience models and not even the relation between network traffic and playback quality has been studied so far, forming a gap in literature. For that reason, we investigate Twitch.tv streaming as one of the largest live streaming platforms based on a large dataset and investigate the possibility to predict live streaming quality based on uplink request information. We apply approaches that are well studied for on demand streaming to predict quality changes, playback quality, and video interruption events as the most important metrics impairing user perceived quality. In this context, we answer whether these models are suitable for live streaming, if small changes are sufficient for satisfactory prediction results, or if fundamental changes and new models are required.}, author = {Loh, Frank and Hildebrand, Kathrin and Wamser, Florian and Geißler, Stefan and Hoßfeld, Tobias}, booktitle = {IEEE/IFIP Network Operations and Management Symposium (NOMS)}, keywords = {sys:hidden:inproceedings}, month = {05}, title = {Machine Learning Based Study of QoE Metrics in Twitch. tv Live Streaming}, year = 2023 }

%0 Conference Paper %1 info3-inproceedings-2023-17 %A Loh, Frank %A Hildebrand, Kathrin %A Wamser, Florian %A Geißler, Stefan %A Hoßfeld, Tobias %B IEEE/IFIP Network Operations and Management Symposium (NOMS) %D 2023 %T Machine Learning Based Study of QoE Metrics in Twitch. tv Live Streaming %X Video streaming generates most network traffic in today’s Internet. For that reason, video on demand streaming is researched heavily in recent years, and many traffic monitoring mechanisms, flow and stream models, and models to predict the user perceived quality are well established. However, the quickly growing live streaming sector is not considered in these Quality of Experience models and not even the relation between network traffic and playback quality has been studied so far, forming a gap in literature. For that reason, we investigate Twitch.tv streaming as one of the largest live streaming platforms based on a large dataset and investigate the possibility to predict live streaming quality based on uplink request information. We apply approaches that are well studied for on demand streaming to predict quality changes, playback quality, and video interruption events as the most important metrics impairing user perceived quality. In this context, we answer whether these models are suitable for live streaming, if small changes are sufficient for satisfactory prediction results, or if fundamental changes and new models are required.
On Profiling, Benchmarking and Behavioral Analysis of SDN Architecture Under DDoS Attacks. Huu Thanh, Nguyen; NgocTuan, Nguyen; AnhKhoa, Dang; CongTuan, Le; TrungKien, Nguyen; XuanDung, Nguyen; QuynhThu, Ngo; Wamser, Florian. In Journal of Network and Systems Management. 2023.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
Software-Defined Networking (SDN) has attracted much attention from research and industrial communities recently as it is more agile and flexible compared to conventional networking technology in offering new network functions and services. By separating the network control functions from the forwarding devices and placing them in a centralized, softwarized and programmable SDN controller, new network functions and services can be easily added into the network in an on-demand manner. However, the centralized control paradigm and the flow-based forwarding principle make the SDN architecture more fragile and vulnerable to malicious actions, such as cyber hijacking or DDoS attacks. In this paper, we focus on analyzing and evaluating negative impacts of DDoS attacks on the SDN architecture. By performing stress tests, the performance of such common SDN controllers as POX, Ryu and Floodlight under DDoS attacks is benchmarked, along with their impacts on the SDN switch and OpenFlow channel. We also address some new threats and vulnerabilities introduced by the nature of SDN.

@article{info3-article-2023-1, abstract = {Software-Defined Networking (SDN) has attracted much attention from research and industrial communities recently as it is more agile and flexible compared to conventional networking technology in offering new network functions and services. By separating the network control functions from the forwarding devices and placing them in a centralized, softwarized and programmable SDN controller, new network functions and services can be easily added into the network in an on-demand manner. However, the centralized control paradigm and the flow-based forwarding principle make the SDN architecture more fragile and vulnerable to malicious actions, such as cyber hijacking or DDoS attacks. In this paper, we focus on analyzing and evaluating negative impacts of DDoS attacks on the SDN architecture. By performing stress tests, the performance of such common SDN controllers as POX, Ryu and Floodlight under DDoS attacks is benchmarked, along with their impacts on the SDN switch and OpenFlow channel. We also address some new threats and vulnerabilities introduced by the nature of SDN.}, author = {Huu Thanh, Nguyen and NgocTuan, Nguyen and AnhKhoa, Dang and CongTuan, Le and TrungKien, Nguyen and XuanDung, Nguyen and QuynhThu, Ngo and Wamser, Florian}, journal = {Journal of Network and Systems Management}, keywords = {sys:hidden:article}, month = {03}, title = {On Profiling, Benchmarking and Behavioral Analysis of SDN Architecture Under DDoS Attacks}, year = 2023 }

%0 Journal Article %1 info3-article-2023-1 %A Huu Thanh, Nguyen %A NgocTuan, Nguyen %A AnhKhoa, Dang %A CongTuan, Le %A TrungKien, Nguyen %A XuanDung, Nguyen %A QuynhThu, Ngo %A Wamser, Florian %D 2023 %J Journal of Network and Systems Management %T On Profiling, Benchmarking and Behavioral Analysis of SDN Architecture Under DDoS Attacks %X Software-Defined Networking (SDN) has attracted much attention from research and industrial communities recently as it is more agile and flexible compared to conventional networking technology in offering new network functions and services. By separating the network control functions from the forwarding devices and placing them in a centralized, softwarized and programmable SDN controller, new network functions and services can be easily added into the network in an on-demand manner. However, the centralized control paradigm and the flow-based forwarding principle make the SDN architecture more fragile and vulnerable to malicious actions, such as cyber hijacking or DDoS attacks. In this paper, we focus on analyzing and evaluating negative impacts of DDoS attacks on the SDN architecture. By performing stress tests, the performance of such common SDN controllers as POX, Ryu and Floodlight under DDoS attacks is benchmarked, along with their impacts on the SDN switch and OpenFlow channel. We also address some new threats and vulnerabilities introduced by the nature of SDN.

Student Works

Previous Works

AquareYoum: Application and Quality of Experience-Aware Resource Management for YouTube (KiVS Communication Software Award 2011)
Summary | Screencast | Publications | Contact

Application and Network Control Within a Wireless Access Network
(IEEE Infocom 2013)
Summary | Screencas & Poster | Publications | Contact

Research Area

Research Area: Access Networks

Study on Wifi Offloading

Application Aware Networking

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