@misc{SchweissguthParzyjeglaDanielisetal., author = {Schweissguth, Eike and Parzyjegla, Helge and Danielis, Peter and M{\"u}hl, Gero and Timmermann, Dirk and Mehner, Stefan and Hohlfeld, Oliver and Hellmanns, David and Falk, Jonathan}, title = {TSN Scheduler Benchmarking}, series = {2023 IEEE 19th International Conference on Factory Communication Systems (WFCS)}, journal = {2023 IEEE 19th International Conference on Factory Communication Systems (WFCS)}, publisher = {IEEE}, isbn = {978-1-6654-6432-1}, issn = {2835-8414}, doi = {10.1109/WFCS57264.2023.10144227}, abstract = {Time-Sensitive Networking (TSN) disrupts realtime communication technology by making IEEE Ethernet realtime-capable. For time-triggered, hard realtime traffic, TSN provides standardized mechanisms to reserve communication paths as well as individual transmission time slots for data frames. By leveraging these means in a precomputed network schedule, TSN allows for bounded end-to-end delays and minimal jitter. Not being part of the IEEE standard, corresponding scheduling algorithms are an active field of research. Unfortunately, due to differing model assumptions, evaluation setups, and key metrics, a fair comparison of schedulers is impossible so far. In this paper, we present a systematic and reproducible approach to benchmark TSN schedulers. First, we provide a scheduler taxonomy that enables to cluster schedulers by their characteristics. Second, we analyze interactions of input parameters and scheduler results to derive a benchmarking parcour for quantitative comparisons. Finally, we use the approach to benchmark existing schedulers and show subtle interaction effects. This way, our approach enables—for the first time-comparability between schedulers, fueled by the public availability of our benchmarking scenarios.}, language = {en} }