Massive Scaling Techniques for Fully Virtualized 5G Mobile Core Networks in the Context of the Internet of Things (5CALE)

Partner	EMnify GmbH
Funded period	February 2019 - January 2022
Researcher	Dr. Florian Wamser Stefan Geißler
Funding Organization	Bayerisches Staatsministerium für Wirtschaft, Landesentwicklung und Energie Strategie BAYERN DIGITAL, Förderlinie Digitalisierung, Förderschwerpunkt "Informations- und Kommunikationstechnik"

Project Description

Massive machine-type communications (mMTC) in the Internet of Things area requires new load balancing, congestion control, scaling, and network survivability techniques for 5G mobile networks. This project addresses the modeling, investigation, and pre-commercial implementation of appropriate mechanisms for managing an immense number of globally distributed network subscribers with a large number of connected network operators based on a distributed, fully virtualized, and cloud-based 5G infrastructure. Project partner of the Chair is the EMnify GmbH. The EMnify GmbH is a commercial provider of a worldwide mobile network in the Internet of Things.

Today, the potential created by the software-based, virtualized network infrastructure is being exploited only by cloud giants like Amazon, Google, and Facebook. An important technical innovation of this project is the examination of the transferability and subsequent application of these approaches to the mobile sector in the context of the Internet of Things. This first requires an exact understanding of the system, which should be gained by characterizing and modeling novel traffic flows in IoT networks. In addition to this scientifically relevant characterization of device traffic, the development of simulation models, which can handle the massive number of devices resulting from the IoT context, is one of the most important scientific innovations for this project. From a technical point of view, the approaches developed for scalability, overload control and network survivability should be mentioned as an important innovation feature.

Work objectives

Methods for functional and stochastic scalability of a fully virtualized, cloud-based based 5G mobile core network.
Overload control and network survivability in the context of the Internet of Things.
Improve the efficiency and efficiency of the overall system.
Pre-commercial implementation (proof of concept).

Challenges

Modeling of new types and patterns of traffic for realistic load description and modeling virtualized core network functions in the cloud.
Evaluation methodologies and design of a simulation to study functional and sustainable stochastic scalability.
Definition of relevant technical and economic metrics and performance evaluation of the common methods such as scaling, overload control and network survivability.
Assessment of the overall performance of the system according to various economic and technical criteria.

The cooperation between the University of Würzburg with its expertise in the fields of traffic modeling and simulation and EMnify GmbH with its expertise in software-based core networks and IoT offers numerous advantages. On the one hand, theoretical and abstract models can be formed, evaluated and validated through the exchange of realistic traffic and cloud data. On the other hand, from the insights gained in this way, practice-relevant mechanisms for scalability, overload control and survivability can be developed and evaluated with regard to their performance in a real system.

Overview of the work packages of the project 5CALE
Overview of and connection between the work packages of the 5CALE project.

Find more information here.

Related Publications

Identification of Signaling Patterns in Mobile IoT Signaling Traffic. Vomhoff, Viktoria; Geißler, Stefan; Hoßfeld, Tobias. In WueWoWAS 22 - KuVS Fachgespräch - Würzburg Workshop on Next-Generation Communication Networks. 2022.
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@inproceedings{info3-inproceedings-2022-8, author = {Vomhoff, Viktoria and Geißler, Stefan and Hoßfeld, Tobias}, booktitle = {WueWoWAS 22 - KuVS Fachgespräch - Würzburg Workshop on Next-Generation Communication Networks}, keywords = {can}, month = {07}, title = {Identification of Signaling Patterns in Mobile IoT Signaling Traffic}, year = 2022 }

%0 Conference Paper %1 info3-inproceedings-2022-8 %A Vomhoff, Viktoria %A Geißler, Stefan %A Hoßfeld, Tobias %B WueWoWAS 22 - KuVS Fachgespräch - Würzburg Workshop on Next-Generation Communication Networks %D 2022 %T Identification of Signaling Patterns in Mobile IoT Signaling Traffic
Characterizing Mobile Signaling Anomalies in the Internet-of-Things. Vomhoff, Viktoria; Geißler, Stefan; Loh, Frank; Bauer, Wolfgang; Hoßfeld, Tobias. In 2nd IFIP/IEEE International workshop on Fully-Flexible Internet Architectures and Protocols for the Next-Generation Tactile Internet (FlexNGIA). 2022.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
The development and adoption speed of new Internet of Things (IoT) devices and applications is constantly increasing. In particular in mobile networks, however, constant connectivity for all newly developed, globally spread, and occasionally geographically mobile devices is challenging. While the main business of current network operators is in particular, not to roam these new device generation between different networks, whereas new so-called Mobile Virtual Network Operators (MVNOs) arise with exactly this business case. They use already available Radio Access Networks and deploy SIM cards that are able to establish data connection everywhere on the basis of international roaming agreements. However, because of the complex interconnection of different systems, additional challenges arise. Outages in one network component might impact the whole system. In this work, we study these signaling anomalies called incidents based on a dataset received from a global MVNO. The goal of this work is to determine traffic characteristics during these incidents towards a better understanding of signaling traffic in IoT networks. Thus, this work can be seen as a fundamental basis to help operators in a characterization, and in particular prediction and avoidance of signaling incidents.

@inproceedings{info3-inproceedings-2022-4, abstract = {The development and adoption speed of new Internet of Things (IoT) devices and applications is constantly increasing. In particular in mobile networks, however, constant connectivity for all newly developed, globally spread, and occasionally geographically mobile devices is challenging. While the main business of current network operators is in particular, not to roam these new device generation between different networks, whereas new so-called Mobile Virtual Network Operators (MVNOs) arise with exactly this business case. They use already available Radio Access Networks and deploy SIM cards that are able to establish data connection everywhere on the basis of international roaming agreements. However, because of the complex interconnection of different systems, additional challenges arise. Outages in one network component might impact the whole system. In this work, we study these signaling anomalies called incidents based on a dataset received from a global MVNO. The goal of this work is to determine traffic characteristics during these incidents towards a better understanding of signaling traffic in IoT networks. Thus, this work can be seen as a fundamental basis to help operators in a characterization, and in particular prediction and avoidance of signaling incidents.}, author = {Vomhoff, Viktoria and Geißler, Stefan and Loh, Frank and Bauer, Wolfgang and Hoßfeld, Tobias}, booktitle = {2nd IFIP/IEEE International workshop on Fully-Flexible Internet Architectures and Protocols for the Next-Generation Tactile Internet (FlexNGIA)}, keywords = {can}, month = {04}, title = {Characterizing Mobile Signaling Anomalies in the Internet-of-Things}, year = 2022 }

%0 Conference Paper %1 info3-inproceedings-2022-4 %A Vomhoff, Viktoria %A Geißler, Stefan %A Loh, Frank %A Bauer, Wolfgang %A Hoßfeld, Tobias %B 2nd IFIP/IEEE International workshop on Fully-Flexible Internet Architectures and Protocols for the Next-Generation Tactile Internet (FlexNGIA) %D 2022 %T Characterizing Mobile Signaling Anomalies in the Internet-of-Things %X The development and adoption speed of new Internet of Things (IoT) devices and applications is constantly increasing. In particular in mobile networks, however, constant connectivity for all newly developed, globally spread, and occasionally geographically mobile devices is challenging. While the main business of current network operators is in particular, not to roam these new device generation between different networks, whereas new so-called Mobile Virtual Network Operators (MVNOs) arise with exactly this business case. They use already available Radio Access Networks and deploy SIM cards that are able to establish data connection everywhere on the basis of international roaming agreements. However, because of the complex interconnection of different systems, additional challenges arise. Outages in one network component might impact the whole system. In this work, we study these signaling anomalies called incidents based on a dataset received from a global MVNO. The goal of this work is to determine traffic characteristics during these incidents towards a better understanding of signaling traffic in IoT networks. Thus, this work can be seen as a fundamental basis to help operators in a characterization, and in particular prediction and avoidance of signaling incidents.
Performance Evaluation of Next-Generation Data Plane Architectures and their Components. Technical Report (PhD dissertation), . Geißler, Stefan. PhD dissertation. University of Würzburg, 2022, April.
- [ Abstract ]
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In this doctoral thesis we cover the performance evaluation of next generation data plane architectures, comprised of complex software as well as programmable hardware components that allow fine granular configuration. In the scope of the thesis we propose mechanisms to monitor the performance of singular components and model key performance indicators of software based packet processing solutions. We present novel approaches towards network abstraction that allow the integration of heterogeneous data plane technologies into a singular network while maintaining total transparency between control and data plane. Finally, we investigate a full, complex system consisting of multiple software-based solutions and perform a detailed performance analysis. We employ simulative approaches to investigate overload control mechanisms that allow efficient operation under adversary conditions. The contributions of this work build the foundation for future research in the areas of network softwarization and network function virtualization.

@phdthesis{info3-dissertation-2022-1, abstract = {In this doctoral thesis we cover the performance evaluation of next generation data plane architectures, comprised of complex software as well as programmable hardware components that allow fine granular configuration. In the scope of the thesis we propose mechanisms to monitor the performance of singular components and model key performance indicators of software based packet processing solutions. We present novel approaches towards network abstraction that allow the integration of heterogeneous data plane technologies into a singular network while maintaining total transparency between control and data plane. Finally, we investigate a full, complex system consisting of multiple software-based solutions and perform a detailed performance analysis. We employ simulative approaches to investigate overload control mechanisms that allow efficient operation under adversary conditions. The contributions of this work build the foundation for future research in the areas of network softwarization and network function virtualization.}, author = {Geißler, Stefan}, keywords = {can}, month = {04}, school = {University of Würzburg}, title = {Performance Evaluation of Next-Generation Data Plane Architectures and their Components}, year = 2022 }

%0 Thesis %1 info3-dissertation-2022-1 %A Geißler, Stefan %D 2022 %T Performance Evaluation of Next-Generation Data Plane Architectures and their Components %X In this doctoral thesis we cover the performance evaluation of next generation data plane architectures, comprised of complex software as well as programmable hardware components that allow fine granular configuration. In the scope of the thesis we propose mechanisms to monitor the performance of singular components and model key performance indicators of software based packet processing solutions. We present novel approaches towards network abstraction that allow the integration of heterogeneous data plane technologies into a singular network while maintaining total transparency between control and data plane. Finally, we investigate a full, complex system consisting of multiple software-based solutions and perform a detailed performance analysis. We employ simulative approaches to investigate overload control mechanisms that allow efficient operation under adversary conditions. The contributions of this work build the foundation for future research in the areas of network softwarization and network function virtualization.
Data Usage in IoT: A Characterization of GTP Tunnels in M2M Mobile Networks. Raffeck, Simon; Geißler, Stefan; Krolikowski, Michael; Gebert, Steffen; Hoßfeld, Tobias. In 2nd IFIP/IEEE International workshop on Fully-Flexible Internet Architectures and Protocols for the Next-Generation Tactile Internet (FlexNGIA). 2022.
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IoT and M2M devices have seen a significant growth in usage and deployment over the last years. Gaining insight into device and data usage behavior exhibited by the participants of mobile networks is elementary for MNO and MVNO to scale their networks and provide a reliable service. This work aims to make use of its first of a kind dataset, spanning multiple countries and MNO, to provide a detailed characterization of GTP tunnels and devices. To this end, general statistics are used to describe the observed data traffic focusing on the distribution of the tunnel duration and volume as well as periodic device behavior. An approximate metric is introduced to analyze the periodicity and synchronicity of IoT devices. Lastly, we publish the data investigated in this work and provide a large scale dataset on the data usage behavior of IoT devices to interested researchers.

@inproceedings{info3-inproceedings-2022-5, abstract = {IoT and M2M devices have seen a significant growth in usage and deployment over the last years. Gaining insight into device and data usage behavior exhibited by the participants of mobile networks is elementary for MNO and MVNO to scale their networks and provide a reliable service. This work aims to make use of its first of a kind dataset, spanning multiple countries and MNO, to provide a detailed characterization of GTP tunnels and devices. To this end, general statistics are used to describe the observed data traffic focusing on the distribution of the tunnel duration and volume as well as periodic device behavior. An approximate metric is introduced to analyze the periodicity and synchronicity of IoT devices. Lastly, we publish the data investigated in this work and provide a large scale dataset on the data usage behavior of IoT devices to interested researchers.}, author = {Raffeck, Simon and Geißler, Stefan and Krolikowski, Michael and Gebert, Steffen and Hoßfeld, Tobias}, booktitle = {2nd IFIP/IEEE International workshop on Fully-Flexible Internet Architectures and Protocols for the Next-Generation Tactile Internet (FlexNGIA)}, keywords = {can}, month = {04}, title = {Data Usage in IoT: A Characterization of GTP Tunnels in M2M Mobile Networks}, year = 2022 }

%0 Conference Paper %1 info3-inproceedings-2022-5 %A Raffeck, Simon %A Geißler, Stefan %A Krolikowski, Michael %A Gebert, Steffen %A Hoßfeld, Tobias %B 2nd IFIP/IEEE International workshop on Fully-Flexible Internet Architectures and Protocols for the Next-Generation Tactile Internet (FlexNGIA) %D 2022 %T Data Usage in IoT: A Characterization of GTP Tunnels in M2M Mobile Networks %X IoT and M2M devices have seen a significant growth in usage and deployment over the last years. Gaining insight into device and data usage behavior exhibited by the participants of mobile networks is elementary for MNO and MVNO to scale their networks and provide a reliable service. This work aims to make use of its first of a kind dataset, spanning multiple countries and MNO, to provide a detailed characterization of GTP tunnels and devices. To this end, general statistics are used to describe the observed data traffic focusing on the distribution of the tunnel duration and volume as well as periodic device behavior. An approximate metric is introduced to analyze the periodicity and synchronicity of IoT devices. Lastly, we publish the data investigated in this work and provide a large scale dataset on the data usage behavior of IoT devices to interested researchers.
Anonymized GTP Tunnel Trace in Mobile IoT. Raffeck, Simon; Geißler, Stefan; Krolikowski, Michael; Gebert, Steffen; Hoßfeld, Tobias. 2022, February.
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Extensive dataset containing one whole month of create and delete events as well as the total, received, and transmitted volume of devices. We obtained data tunnel related events and volume values over 30 days in October 2021. In total the dataset contains a sample of 500000 unique devices that generate 155 million individual data tunnels.

@misc{info3-misc-2022-1, abstract = {Extensive dataset containing one whole month of create and delete events as well as the total, received, and transmitted volume of devices. We obtained data tunnel related events and volume values over 30 days in October 2021. In total the dataset contains a sample of 500000 unique devices that generate 155 million individual data tunnels.}, author = {Raffeck, Simon and Geißler, Stefan and Krolikowski, Michael and Gebert, Steffen and Hoßfeld, Tobias}, howpublished = {https://zenodo.org/record/6045708}, keywords = {can}, month = {02}, title = {Anonymized GTP Tunnel Trace in Mobile IoT}, year = 2022 }

%0 Generic %1 info3-misc-2022-1 %A Raffeck, Simon %A Geißler, Stefan %A Krolikowski, Michael %A Gebert, Steffen %A Hoßfeld, Tobias %D 2022 %T Anonymized GTP Tunnel Trace in Mobile IoT %X Extensive dataset containing one whole month of create and delete events as well as the total, received, and transmitted volume of devices. We obtained data tunnel related events and volume values over 30 days in October 2021. In total the dataset contains a sample of 500000 unique devices that generate 155 million individual data tunnels.
Signaling Traffic in Internet-of-Things Mobile Networks. Geissler, Stefan; Wamser, Florian; Bauer, Wolfang; Krolikowski, Michael; Gebert, Steffen; Hoßfeld, Tobias. In IFIP/IEEE International Symposium on Integrated Network Management (IM 2021). Bordeaux, France (Virtual Conference), 2021.
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- [ EndNote ]
The Internet of Things (IoT) is expected to play an increasingly important role in next-generation mobile networks. Detailed knowledge of this type of traffic and the associated signaling in those networks is of interest to operators and standardization in order to run these networks successfully. The aim of this study is to characterize IoT signaling traffic for mobile communication networks (i) from a network operator’s point of view, (ii) at device level, and (iii) for the establishment of data connections. General statistics on signaling and device behavior, such as the observed IoT traffic volume and message composition, are given before device classes with statistically different signaling behavior are identified. Finally, by characterizing the aggre- gated signaling traffic, we show that the Markov assumption, widespread in standardization and literature, regarding the aggregated arrival process for data connections does not apply in reality.

@inproceedings{info3-inproceedings-2021-1, abstract = {The Internet of Things (IoT) is expected to play an increasingly important role in next-generation mobile networks. Detailed knowledge of this type of traffic and the associated signaling in those networks is of interest to operators and standardization in order to run these networks successfully. The aim of this study is to characterize IoT signaling traffic for mobile communication networks (i) from a network operator’s point of view, (ii) at device level, and (iii) for the establishment of data connections. General statistics on signaling and device behavior, such as the observed IoT traffic volume and message composition, are given before device classes with statistically different signaling behavior are identified. Finally, by characterizing the aggre- gated signaling traffic, we show that the Markov assumption, widespread in standardization and literature, regarding the aggregated arrival process for data connections does not apply in reality.}, address = {Bordeaux, France (Virtual Conference)}, author = {Geissler, Stefan and Wamser, Florian and Bauer, Wolfang and Krolikowski, Michael and Gebert, Steffen and Hoßfeld, Tobias}, booktitle = {IFIP/IEEE International Symposium on Integrated Network Management (IM 2021)}, keywords = {can}, month = {05}, title = {Signaling Traffic in Internet-of-Things Mobile Networks}, year = 2021 }

%0 Conference Paper %1 info3-inproceedings-2021-1 %A Geissler, Stefan %A Wamser, Florian %A Bauer, Wolfang %A Krolikowski, Michael %A Gebert, Steffen %A Hoßfeld, Tobias %B IFIP/IEEE International Symposium on Integrated Network Management (IM 2021) %C Bordeaux, France (Virtual Conference) %D 2021 %T Signaling Traffic in Internet-of-Things Mobile Networks %X The Internet of Things (IoT) is expected to play an increasingly important role in next-generation mobile networks. Detailed knowledge of this type of traffic and the associated signaling in those networks is of interest to operators and standardization in order to run these networks successfully. The aim of this study is to characterize IoT signaling traffic for mobile communication networks (i) from a network operator’s point of view, (ii) at device level, and (iii) for the establishment of data connections. General statistics on signaling and device behavior, such as the observed IoT traffic volume and message composition, are given before device classes with statistically different signaling behavior are identified. Finally, by characterizing the aggre- gated signaling traffic, we show that the Markov assumption, widespread in standardization and literature, regarding the aggregated arrival process for data connections does not apply in reality.
Modeling of Traffic Flows in Internet of Things Using Renewal Approximation. Wamser, Florian; Tran-Gia, Phuoc; Geissler, Stefan; Hoßfeld, Tobias. In International Conference on Optimization and Decision Science (ODS2019). 2019.
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This paper proposes a versatile approach to model aggregated traffic flows in the Internet of Things (IoT) using renewal approximation. The modeled traffic originates from a large number of sources or devices consisting of a set of sensors mixed with classical elastic random traffic modeled as Poisson arrival process. The work shows the exact derivation in the simple case for periodic sensors. It shows further results in the mixed case with periodic sensors and a background process. The renewal approximation allows to derive the required number of sensors such that the aggregated traffic can be approximated as Poisson process.

@inproceedings{info3-article-2019-8, abstract = {This paper proposes a versatile approach to model aggregated traffic flows in the Internet of Things (IoT) using renewal approximation. The modeled traffic originates from a large number of sources or devices consisting of a set of sensors mixed with classical elastic random traffic modeled as Poisson arrival process. The work shows the exact derivation in the simple case for periodic sensors. It shows further results in the mixed case with periodic sensors and a background process. The renewal approximation allows to derive the required number of sensors such that the aggregated traffic can be approximated as Poisson process.}, author = {Wamser, Florian and Tran-Gia, Phuoc and Geissler, Stefan and Hoßfeld, Tobias}, booktitle = {International Conference on Optimization and Decision Science (ODS2019)}, keywords = {can}, month = {09}, title = {Modeling of Traffic Flows in Internet of Things Using Renewal Approximation}, year = 2019 }

%0 Conference Paper %1 info3-article-2019-8 %A Wamser, Florian %A Tran-Gia, Phuoc %A Geissler, Stefan %A Hoßfeld, Tobias %B International Conference on Optimization and Decision Science (ODS2019) %D 2019 %T Modeling of Traffic Flows in Internet of Things Using Renewal Approximation %X This paper proposes a versatile approach to model aggregated traffic flows in the Internet of Things (IoT) using renewal approximation. The modeled traffic originates from a large number of sources or devices consisting of a set of sensors mixed with classical elastic random traffic modeled as Poisson arrival process. The work shows the exact derivation in the simple case for periodic sensors. It shows further results in the mixed case with periodic sensors and a background process. The renewal approximation allows to derive the required number of sensors such that the aggregated traffic can be approximated as Poisson process.