Dr. Stefan Geißler

2022

1.
Vomhoff, V., Geißler, S., Hoßfeld, T.: Identification of Signaling Patterns in Mobile IoT Signaling Traffic. 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 = {myown 5cale sys:hidden:inproceedings can}, month = 7, 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
2.
Raffeck, S., Geißler, S., Hoßfeld, T.: DBM: Decentralized Burst Mitigation for Self-Organizing LoRa Deployments. KuVS Fachgespräch - Würzburg Workshop on Modeling, Analysis and Simulation of Next-Generation Communication Networks 2022 (2022).
[ BibTeX ] [ EndNote ]
 
@inproceedings{info3-inproceedings-2022-7, author = {Raffeck, Simon and Geißler, Stefan and Hoßfeld, Tobias}, booktitle = {KuVS Fachgespräch - Würzburg Workshop on Modeling, Analysis and Simulation of Next-Generation Communication Networks 2022}, keywords = {myown sys:hidden:inproceedings can}, month = 7, title = {DBM: Decentralized Burst Mitigation for Self-Organizing LoRa Deployments}, year = 2022 }
%0 Conference Paper %1 info3-inproceedings-2022-7 %A Raffeck, Simon %A Geißler, Stefan %A Hoßfeld, Tobias %B KuVS Fachgespräch - Würzburg Workshop on Modeling, Analysis and Simulation of Next-Generation Communication Networks 2022 %D 2022 %T DBM: Decentralized Burst Mitigation for Self-Organizing LoRa Deployments
3.
Hoßfeld, T., Raffeck, S., Loh, F., Geißler, S.: Analytical Model for the Energy Efficiency in Low Power IoT Deployments. 1st International Workshop on Network Energy Efficiency in the Softwarization Era (2022).
[ Abstract ] [ BibTeX ] [ EndNote ]
 
The recent rise of the Internet of Things (IoT) has given way to numerous challenges and research questions. One of the most critical issues in the area of low powered devices is the question of energy efficiency. Here, technologies like LoRa or Zigbee emerged, promising low power consumption while maintaining adequate performance. However, even when using these tailor made technologies, several configuration aspects need to be taken into account to provide high performance, energy efficient operation. To this end, we propose a generic model to compute the energy efficiency of wireless sensors under the assumption of perfect CSMA/CA channel access. We present numerical results for a typical LoRa device and highlight extensions towards other channel access mechanisms. Finally, we apply Kleinrock's power metric to obtain ideal system configurations for varying load parameters.
@inproceedings{info3-inproceedings-2022-6, abstract = {The recent rise of the Internet of Things (IoT) has given way to numerous challenges and research questions. One of the most critical issues in the area of low powered devices is the question of energy efficiency. Here, technologies like LoRa or Zigbee emerged, promising low power consumption while maintaining adequate performance. However, even when using these tailor made technologies, several configuration aspects need to be taken into account to provide high performance, energy efficient operation. To this end, we propose a generic model to compute the energy efficiency of wireless sensors under the assumption of perfect CSMA/CA channel access. We present numerical results for a typical LoRa device and highlight extensions towards other channel access mechanisms. Finally, we apply Kleinrock's power metric to obtain ideal system configurations for varying load parameters.}, author = {Hoßfeld, Tobias and Raffeck, Simon and Loh, Frank and Geißler, Stefan}, booktitle = {1st International Workshop on Network Energy Efficiency in the Softwarization Era}, keywords = {myown sys:hidden:inproceedings can}, month = 6, title = {Analytical Model for the Energy Efficiency in Low Power IoT Deployments}, year = 2022 }
%0 Conference Paper %1 info3-inproceedings-2022-6 %A Hoßfeld, Tobias %A Raffeck, Simon %A Loh, Frank %A Geißler, Stefan %B 1st International Workshop on Network Energy Efficiency in the Softwarization Era %D 2022 %T Analytical Model for the Energy Efficiency in Low Power IoT Deployments %X The recent rise of the Internet of Things (IoT) has given way to numerous challenges and research questions. One of the most critical issues in the area of low powered devices is the question of energy efficiency. Here, technologies like LoRa or Zigbee emerged, promising low power consumption while maintaining adequate performance. However, even when using these tailor made technologies, several configuration aspects need to be taken into account to provide high performance, energy efficient operation. To this end, we propose a generic model to compute the energy efficiency of wireless sensors under the assumption of perfect CSMA/CA channel access. We present numerical results for a typical LoRa device and highlight extensions towards other channel access mechanisms. Finally, we apply Kleinrock's power metric to obtain ideal system configurations for varying load parameters.
4.
Geißler, S.: Performance Evaluation of Next-Generation Data Plane Architectures and their Components, (2022).
[ Abstract ] [ BibTeX ] [ EndNote ]
 
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 = {myown sendate-planets sys:hidden:dissertation 5cale ngn sys:hidden:supervisor:tobias.hoßfeld can}, month = 4, 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.
5.
Raffeck, S., Geißler, S., Krolikowski, M., Gebert, S., Hoßfeld, T.: Anonymized GTP Tunnel Trace in Mobile IoT, (2022).
[ Abstract ] [ BibTeX ] [ EndNote ]
 
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 = {myown 5cale sys:hidden:misc can}, month = 2, 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.