Simon Raffeck M. Sc.

2022

1.
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
2.
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.
3.
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.
4.
Raffeck, S., Geißler, S., Krolikowski, M., Gebert, S., Hoßfeld, T.: Data Usage in IoT: A Characterization of GTP Tunnels in M2M Mobile Networks. 2nd IFIP/IEEE International workshop on Fully-Flexible Internet Architectures and Protocols for the Next-Generation Tactile Internet (FlexNGIA) (2022).
[ Abstract ] [ BibTeX ] [ EndNote ]
 
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 = {myown 5cale sys:hidden:inproceedings can}, month = 4, 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.

2018

1.
Nguyen-Ngoc, A., Raffeck, S., Lange, S., Geissler, S., Zinner, T., Tran-Gia, P.: Benchmarking the ONOS Controller with OFCProbe. 7th International Conference on Communications and Electronics (ICCE). , Hue, Vietnam (2018).
[ Abstract ] [ BibTeX ] [ EndNote ]
 
The increased popularity of Software Defined Networking (SDN) drives the development and research of all involved components. In particular, state-of-the-art SDN controllers are a central part of the resulting network architecture and have a large impact on the performance of the entire network. Hence, it is necessary to quantify various performance indicators of the SDN controller in order to assess its feasibility in the context of different network characteristics such as topology and network size w.r.t. the number of nodes and links. To this end, we extend the open-source controller benchmarking tool OFCProbe with several novel modules that are capable of recording relevant performance metrics and demonstrate their use in the context of benchmarking the ONOS controller. Furthermore, we investigate the impact of different types of topology characteristics on the performance of the controller. In this work, we focus on several performance indicators for SDN controllers. First, the time that the ONOS controller needs to discover the network topology and update its internal representation of the topology. Second, we investigate the duration of the installation of flow rules that are used for reactive path provisioning. Finally, we measure the response time of the controller when dealing with asynchronous messages.
@inproceedings{info3-inproceedings-2018-15, abstract = {The increased popularity of Software Defined Networking (SDN) drives the development and research of all involved components. In particular, state-of-the-art SDN controllers are a central part of the resulting network architecture and have a large impact on the performance of the entire network. Hence, it is necessary to quantify various performance indicators of the SDN controller in order to assess its feasibility in the context of different network characteristics such as topology and network size w.r.t. the number of nodes and links. To this end, we extend the open-source controller benchmarking tool OFCProbe with several novel modules that are capable of recording relevant performance metrics and demonstrate their use in the context of benchmarking the ONOS controller. Furthermore, we investigate the impact of different types of topology characteristics on the performance of the controller. In this work, we focus on several performance indicators for SDN controllers. First, the time that the ONOS controller needs to discover the network topology and update its internal representation of the topology. Second, we investigate the duration of the installation of flow rules that are used for reactive path provisioning. Finally, we measure the response time of the controller when dealing with asynchronous messages.}, address = {Hue, Vietnam}, author = {Nguyen-Ngoc, Anh and Raffeck, Simon and Lange, Stanislav and Geissler, Stefan and Zinner, Thomas and Tran-Gia, Phuoc}, booktitle = {7th International Conference on Communications and Electronics (ICCE)}, keywords = {myown sendate-planets 5g-net sys:hidden:inproceedings ngn}, month = 7, title = {Benchmarking the ONOS Controller with OFCProbe}, year = 2018 }
%0 Conference Paper %1 info3-inproceedings-2018-15 %A Nguyen-Ngoc, Anh %A Raffeck, Simon %A Lange, Stanislav %A Geissler, Stefan %A Zinner, Thomas %A Tran-Gia, Phuoc %B 7th International Conference on Communications and Electronics (ICCE) %C Hue, Vietnam %D 2018 %T Benchmarking the ONOS Controller with OFCProbe %X The increased popularity of Software Defined Networking (SDN) drives the development and research of all involved components. In particular, state-of-the-art SDN controllers are a central part of the resulting network architecture and have a large impact on the performance of the entire network. Hence, it is necessary to quantify various performance indicators of the SDN controller in order to assess its feasibility in the context of different network characteristics such as topology and network size w.r.t. the number of nodes and links. To this end, we extend the open-source controller benchmarking tool OFCProbe with several novel modules that are capable of recording relevant performance metrics and demonstrate their use in the context of benchmarking the ONOS controller. Furthermore, we investigate the impact of different types of topology characteristics on the performance of the controller. In this work, we focus on several performance indicators for SDN controllers. First, the time that the ONOS controller needs to discover the network topology and update its internal representation of the topology. Second, we investigate the duration of the installation of flow rules that are used for reactive path provisioning. Finally, we measure the response time of the controller when dealing with asynchronous messages.