Simon Raffeck - Lehrstuhl für Informatik III

Telefon	(0931) 31-86488
Telefax	(0931) 31-86632
E-Mail	simon.raffeck@uni-wuerzburg.de
Raum	A208
Anschrift	Lehrstuhl für Informatik III Am Hubland D-97074 Würzburg

Inhalt: Übersicht | Veröffentlichungen | Lehre | Arbeitsgruppe | Projekte

Forschungsinteressen

Meine Forschungsinteressen umfassen die folgenden Themen:

Time-Sensitive Networking (TSN)
Internet der Dinge (IoT)
Software Defined Networking (SDN)
5G Mobilfunkkommunikation
Kabellose Kommunikationsprotokolle und Energieeffizienz
Leistungsbewertung und Modellierung von Kommunikationssystemen

Neuste Veröffentlichungen

2026[ to top ]

Repeatable Experiments, Inspectable Results: Lessons from Private 5G Campus Networks. Schumann, Lukas Kilian; Raffeck, Simon; Geißler, Stefan; Hoßfeld, Tobias. In KuVS Fachgespräch - Würzburg Workshop on 6G Networks (WueWoWAS’26). 2026.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
Private 5G campus networks provide flexible environments for studying future mobile systems, but the same flexibility makes measurement results difficult to interpret and compare. Configuration choices, software versions, modem behavior, radio placement, and observability limitations can all affect reported QoS and energy metrics. This work synthesizes lessons from our prior and ongoing work on reproducibility-oriented 5G campus-network experimentation, including an automation workflow, energy-aware parameter studies, and a comparative measurement study of modem-specific influences. From this, we argue that trustworthy private network measurements require experiment state reporting, artifact preservation, explicit observability limits, and multi-artifact corroboration. Examples from our work include configuration-dependent UE power, non-linear gain effects, incomplete or implausible channel metrics, and modem-specific throughput, delay, and SNR behavior. We derive methodological requirements for inspectable results and outline open challenges around larger modem pools, RedCap devices, MCS-aware energy modeling, segmentation- and retransmission-aware delay attribution, and future O-RAN split integration.

@inproceedings{info3-inproceedings-2026-5, abstract = {Private 5G campus networks provide flexible environments for studying future mobile systems, but the same flexibility makes measurement results difficult to interpret and compare. Configuration choices, software versions, modem behavior, radio placement, and observability limitations can all affect reported QoS and energy metrics. This work synthesizes lessons from our prior and ongoing work on reproducibility-oriented 5G campus-network experimentation, including an automation workflow, energy-aware parameter studies, and a comparative measurement study of modem-specific influences. From this, we argue that trustworthy private network measurements require experiment state reporting, artifact preservation, explicit observability limits, and multi-artifact corroboration. Examples from our work include configuration-dependent UE power, non-linear gain effects, incomplete or implausible channel metrics, and modem-specific throughput, delay, and SNR behavior. We derive methodological requirements for inspectable results and outline open challenges around larger modem pools, RedCap devices, MCS-aware energy modeling, segmentation- and retransmission-aware delay attribution, and future O-RAN split integration.}, author = {Schumann, Lukas Kilian and Raffeck, Simon and Geißler, Stefan and Hoßfeld, Tobias}, booktitle = {KuVS Fachgespräch - Würzburg Workshop on 6G Networks (WueWoWAS’26)}, keywords = {sustainet-advance}, month = {09}, title = {Repeatable Experiments, Inspectable Results: Lessons from Private 5G Campus Networks}, year = 2026 }

%0 Conference Paper %1 info3-inproceedings-2026-5 %A Schumann, Lukas Kilian %A Raffeck, Simon %A Geißler, Stefan %A Hoßfeld, Tobias %B KuVS Fachgespräch - Würzburg Workshop on 6G Networks (WueWoWAS’26) %D 2026 %T Repeatable Experiments, Inspectable Results: Lessons from Private 5G Campus Networks %X Private 5G campus networks provide flexible environments for studying future mobile systems, but the same flexibility makes measurement results difficult to interpret and compare. Configuration choices, software versions, modem behavior, radio placement, and observability limitations can all affect reported QoS and energy metrics. This work synthesizes lessons from our prior and ongoing work on reproducibility-oriented 5G campus-network experimentation, including an automation workflow, energy-aware parameter studies, and a comparative measurement study of modem-specific influences. From this, we argue that trustworthy private network measurements require experiment state reporting, artifact preservation, explicit observability limits, and multi-artifact corroboration. Examples from our work include configuration-dependent UE power, non-linear gain effects, incomplete or implausible channel metrics, and modem-specific throughput, delay, and SNR behavior. We derive methodological requirements for inspectable results and outline open challenges around larger modem pools, RedCap devices, MCS-aware energy modeling, segmentation- and retransmission-aware delay attribution, and future O-RAN split integration.
More is Always Better? Investigating QoS and Energy Efficiency in 5G Campus Networks. Schumann, Lukas Kilian; Raffeck, Simon; Geißler, Stefan; Hoßfeld, Tobias. In 2026 IEEE 12th International Conference on Network Softwarization (NetSoft). 2026.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
As 5G pushes mobile networking toward flexible, softwarized radio access networks, energy efficiency emerges as a first-class performance metric. However, the relationship between 5G NR configuration parameters, power draw, and performance have yet to be systematically explored. To this end, this work introduces a custom automation framework to conduct a large-scale parameter study and investigate the key interactions between Quality of Service (QoS), power consumption, and individual 5G NR configuration parameters. The evaluation conducted in a 5G campus testbed utilizing OAI and srsRAN applies a factorial design to a large set of parameters. In total over 7000 individual experiments are conducted, the results of which are made publicly available, in addition to the framework. The data reveals that 5G NR energy efficiency is highly dependent on the specific use case, as configuration settings can lead to contradictory results based on traffic load and performance targets.

@inproceedings{info3-inproceedings-2026-4, abstract = {As 5G pushes mobile networking toward flexible, softwarized radio access networks, energy efficiency emerges as a first-class performance metric. However, the relationship between 5G NR configuration parameters, power draw, and performance have yet to be systematically explored. To this end, this work introduces a custom automation framework to conduct a large-scale parameter study and investigate the key interactions between Quality of Service (QoS), power consumption, and individual 5G NR configuration parameters. The evaluation conducted in a 5G campus testbed utilizing OAI and srsRAN applies a factorial design to a large set of parameters. In total over 7000 individual experiments are conducted, the results of which are made publicly available, in addition to the framework. The data reveals that 5G NR energy efficiency is highly dependent on the specific use case, as configuration settings can lead to contradictory results based on traffic load and performance targets.}, author = {Schumann, Lukas Kilian and Raffeck, Simon and Geißler, Stefan and Hoßfeld, Tobias}, booktitle = {2026 IEEE 12th International Conference on Network Softwarization (NetSoft)}, keywords = {sustainet-advance}, title = {More is Always Better? Investigating QoS and Energy Efficiency in 5G Campus Networks}, year = 2026 }

%0 Conference Paper %1 info3-inproceedings-2026-4 %A Schumann, Lukas Kilian %A Raffeck, Simon %A Geißler, Stefan %A Hoßfeld, Tobias %B 2026 IEEE 12th International Conference on Network Softwarization (NetSoft) %D 2026 %T More is Always Better? Investigating QoS and Energy Efficiency in 5G Campus Networks %X As 5G pushes mobile networking toward flexible, softwarized radio access networks, energy efficiency emerges as a first-class performance metric. However, the relationship between 5G NR configuration parameters, power draw, and performance have yet to be systematically explored. To this end, this work introduces a custom automation framework to conduct a large-scale parameter study and investigate the key interactions between Quality of Service (QoS), power consumption, and individual 5G NR configuration parameters. The evaluation conducted in a 5G campus testbed utilizing OAI and srsRAN applies a factorial design to a large set of parameters. In total over 7000 individual experiments are conducted, the results of which are made publicly available, in addition to the framework. The data reveals that 5G NR energy efficiency is highly dependent on the specific use case, as configuration settings can lead to contradictory results based on traffic load and performance targets.
Reproducibility of Experiments in Networking. Wehner, Nikolas; Grigorjew, Alexej; Raffeck, Simon; Goedicke, Michael; Hoßfeld, Tobias. In IEEE Access. 2026.
- [ Abstract ]
- [ BibTeX ]
- [ EndNote ]
Reproducibility is a cornerstone of good scientific practice, enabling validation of experimental results and fostering progress by building upon prior work. The importance of reproducibility in networking research has gained traction in recent years. Notably, the Dagstuhl beginner’s guide to reproducible experimental networking research has provided valuable best practices for documentation, data handling, and experiment design. However, the identification of specific networking components and aspects that prevent experiment reproducibility has not been investigated yet. This work addresses this gap by systematically identifying such components, constructing a taxonomy based on the findings, and proposing guidelines to increase experiment reproducibility. For this purpose, we discuss and analyze several networking use cases: 5G measurement experiments, Internet measurements, AI/ML-based networking experiments, and subjective QoE studies. Through targeted experiments and a review of existing studies, we identify some key sources of variability and discuss strategies to reduce variability and thus increase reproducibility. Our analysis highlights the importance of clearly defining research questions and expected outcomes as they form the foundation for assessing reproducibility. Additionally, our findings show the need for documenting potential sources of randomness, e.g., platform-specific effects introduced by operating systems, prior to experimental design. Minimizing unnecessary variability, e.g., by abstracting or replacing such components, further enhances reproducibility. While not all variability can be controlled due to the inherent complexity of networked systems, the proposed guidelines offer practical steps toward more reproducible networking experiments.

@article{info3-article-2026-2, abstract = {Reproducibility is a cornerstone of good scientific practice, enabling validation of experimental results and fostering progress by building upon prior work. The importance of reproducibility in networking research has gained traction in recent years. Notably, the Dagstuhl beginner’s guide to reproducible experimental networking research has provided valuable best practices for documentation, data handling, and experiment design. However, the identification of specific networking components and aspects that prevent experiment reproducibility has not been investigated yet. This work addresses this gap by systematically identifying such components, constructing a taxonomy based on the findings, and proposing guidelines to increase experiment reproducibility. For this purpose, we discuss and analyze several networking use cases: 5G measurement experiments, Internet measurements, AI/ML-based networking experiments, and subjective QoE studies. Through targeted experiments and a review of existing studies, we identify some key sources of variability and discuss strategies to reduce variability and thus increase reproducibility. Our analysis highlights the importance of clearly defining research questions and expected outcomes as they form the foundation for assessing reproducibility. Additionally, our findings show the need for documenting potential sources of randomness, e.g., platform-specific effects introduced by operating systems, prior to experimental design. Minimizing unnecessary variability, e.g., by abstracting or replacing such components, further enhances reproducibility. While not all variability can be controlled due to the inherent complexity of networked systems, the proposed guidelines offer practical steps toward more reproducible networking experiments.}, author = {Wehner, Nikolas and Grigorjew, Alexej and Raffeck, Simon and Goedicke, Michael and Hoßfeld, Tobias}, journal = {IEEE Access}, keywords = {sys:hidden:article}, title = {Reproducibility of Experiments in Networking}, year = 2026 }

%0 Journal Article %1 info3-article-2026-2 %A Wehner, Nikolas %A Grigorjew, Alexej %A Raffeck, Simon %A Goedicke, Michael %A Hoßfeld, Tobias %D 2026 %J IEEE Access %T Reproducibility of Experiments in Networking %X Reproducibility is a cornerstone of good scientific practice, enabling validation of experimental results and fostering progress by building upon prior work. The importance of reproducibility in networking research has gained traction in recent years. Notably, the Dagstuhl beginner’s guide to reproducible experimental networking research has provided valuable best practices for documentation, data handling, and experiment design. However, the identification of specific networking components and aspects that prevent experiment reproducibility has not been investigated yet. This work addresses this gap by systematically identifying such components, constructing a taxonomy based on the findings, and proposing guidelines to increase experiment reproducibility. For this purpose, we discuss and analyze several networking use cases: 5G measurement experiments, Internet measurements, AI/ML-based networking experiments, and subjective QoE studies. Through targeted experiments and a review of existing studies, we identify some key sources of variability and discuss strategies to reduce variability and thus increase reproducibility. Our analysis highlights the importance of clearly defining research questions and expected outcomes as they form the foundation for assessing reproducibility. Additionally, our findings show the need for documenting potential sources of randomness, e.g., platform-specific effects introduced by operating systems, prior to experimental design. Minimizing unnecessary variability, e.g., by abstracting or replacing such components, further enhances reproducibility. While not all variability can be controlled due to the inherent complexity of networked systems, the proposed guidelines offer practical steps toward more reproducible networking experiments.

2025[ to top ]

QoS and QoE Study of the European 5G Mobile Networks for Next Generation of Applications. Loh, Frank; Raithel, Flavian; Raffeck, Simon; Seufert, Anika; Fröhler, Robert; Heller, Claus; Hoßfeld, Tobias. In IEEE Communications Magazine. 2025.
- [ BibTeX ]
- [ EndNote ]
@article{info3-article-2025-4, author = {Loh, Frank and Raithel, Flavian and Raffeck, Simon and Seufert, Anika and Fröhler, Robert and Heller, Claus and Hoßfeld, Tobias}, journal = {IEEE Communications Magazine}, keywords = {5gqmon}, title = {QoS and QoE Study of the European 5G Mobile Networks for Next Generation of Applications}, year = 2025 }

%0 Journal Article %1 info3-article-2025-4 %A Loh, Frank %A Raithel, Flavian %A Raffeck, Simon %A Seufert, Anika %A Fröhler, Robert %A Heller, Claus %A Hoßfeld, Tobias %D 2025 %J IEEE Communications Magazine %T QoS and QoE Study of the European 5G Mobile Networks for Next Generation of Applications

2024[ to top ]

Time-Sensitive Networking over the Air: Combining 5G and TSN. Grigorjew, Alexej; Raffeck, Simon; Geißler, Stefan; Hoßfeld, Tobias. In WueWoWAS’24 KuVS Fachgespraech - Wuerzburg Workshop on Next-Generation Communication Networks. 2024.
- [ BibTeX ]
- [ EndNote ]
@inproceedings{info3-inproceedings-2024-10, author = {Grigorjew, Alexej and Raffeck, Simon and Geißler, Stefan and Hoßfeld, Tobias}, booktitle = {WueWoWAS'24 KuVS Fachgespraech - Wuerzburg Workshop on Next-Generation Communication Networks}, keywords = {kosinu5}, month = 10, title = {Time-Sensitive Networking over the Air: Combining 5G and TSN}, year = 2024 }

%0 Conference Paper %1 info3-inproceedings-2024-10 %A Grigorjew, Alexej %A Raffeck, Simon %A Geißler, Stefan %A Hoßfeld, Tobias %B WueWoWAS'24 KuVS Fachgespraech - Wuerzburg Workshop on Next-Generation Communication Networks %D 2024 %T Time-Sensitive Networking over the Air: Combining 5G and TSN

Eine umfassende Liste aller Publikationen finden Sie hier: Veröffentlichungen

Simon Raffeck M. Sc.

Forschungsinteressen

Neuste Veröffentlichungen

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