Abstract
To support reliable and low-latency communication, Time-Sensitive Networking introduced protocols and interfaces for resource allocation in Ethernet. However, the implementation of these allocation algorithms has not yet been covered by the standards. Our work focuses on deadline-guaranteeing resource allocation for networks with static and dynamic traffic. To achieve this, we combine offline network optimization heuristics with online admission control and, thus, allow for new flow registrations while the network is running. We demonstrate our solution on Credit-Based Shaper networks by using the delay analysis framework Network Calculus. We compare our approach with an intuitive and a brute-force algorithm, where we can achieve significant improvements, both, in terms of quality and runtime. Thereby, our results show that we can guarantee maximum end-to-end delays and also increase the flexibility of the network while requiring only minimal user input.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
We defined the flows according to the traffic profiles 1, 2, 3, and 4 as defined in Table 1, with 86 flows per profile and a bandwidth of \(1\,{\text {Gbit}}/{\text {s}}\).
- 2.
References
IEEE standard for local and metropolitan area networks-bridges and bridged networks—amendment 31: stream reservation protocol (SRP) enhancements and performance improvements. IEEE Std 802.1Qcc-2018 (Amendment to IEEE Std 802.1Q-2018) (2018). https://doi.org/10.1109/IEEESTD.2018.8514112
P802.1Qdd—resource allocation protocol (2019). https://1.ieee802.org/TSN/802-1qdd/
Akiba, T., Sano, S., Yanase, T., Ohta, T., Koyama, M.: Optuna: a next-generation hyperparameter optimization framework. In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2019)
Arestova, A., Hielscher, K.S.J., German, R.: Design of a hybrid genetic algorithm for time-sensitive networking. In: Hermanns, H. (ed.) Measurement, Modelling and Evaluation of Computing Systems, pp. 99–117. Springer International Publishing, Cham (2020)
Chuang, C.C., Yu, T.H., Lin, C.W., Pang, A.C., Hsieh, T.J.: Online stream-aware routing for TSN-based industrial control systems. In: 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), vol. 1, pp. 254–261 (2020). https://doi.org/10.1109/ETFA46521.2020.9211969
Craciunas, S.S., Oliver, R.S., Chmelík, M., Steiner, W.: Scheduling real-time communication in IEEE 802.1Qbv time sensitive networks. In: Proceedings of the International Conference on Real-Time Networks and Systems, pp. 183–192. ACM Press (2016). https://doi.org/10.1145/2997465.2997470
Fortin, F.A., De Rainville, F.M., Gardner, M.A., Parizeau, M., Gagné, C.: DEAP: evolutionary algorithms made easy. J. Machine Learn. Res. 13, 2171–2175 (2012)
Francés, F., Fraboul, C., Grieu, J.: Using Network Calculus to optimize the AFDX network, p. 9 (2006)
Fraser, A., Burnell, D.: Computer Models in Genetics. McGraw-Hill, New York (1970)
Gavriluţ, V., Pop, P.: Traffic-type Assignment for TSN-based Mixed-criticality cyber-physical systems. ACM Trans. Cyber-Phys. Syst. 4(2), 1–27 (2020). https://doi.org/10.1145/3371708, https://dl.acm.org/doi/10.1145/3371708
Grigorjew, A., Metzger, F., Hoßfeld, T., Specht, J., Götz, F.J., Chen, F., Schmitt, J.: Bounded latency with bridge-local stream reservation and strict priority queuing. In: 11th International Conference on Network of the Future, pp. 55–63 (2020). https://doi.org/10.1109/NoF50125.2020.9249224
Grigorjew, A., Seufert, M., Wehner, N., Hofmann, J., Hoßfeld, T.: Ml-assisted latency assignments in time-sensitive networking. In: IFIP/IEEE International Symposium on Integrated Network Management (IM), pp. 116–124 (2021)
Guck, J.W., Van Bemten, A., Kellerer, W.: Detserv: network models for real-time QOS provisioning in SDN-based industrial environments. IEEE Trans. Netw. Serv. Manage. 14(4), 1003–1017 (2017). https://doi.org/10.1109/TNSM.2017.2755769. Dec
Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings of ICNN’95—International Conference on Neural Networks, vol. 4, pp. 1942–1948 (1995). https://doi.org/10.1109/ICNN.1995.488968
Le Boudec, J.Y., Thiran, P.: Network calculus: a theory of deterministic queuing systems for the Internet. Springer, Berlin, Heidelberg (2001). https://doi.org/10.1007/3-540-45318-0
Li, E., He, F., Zhao, L., Zhou, X.: A SDN-based traffic bandwidth allocation method for time sensitive networking in Avionics. In: 2019 IEEE/AIAA 38th Digital Avionics Systems Conference (DASC), pp. 1–7 (2019). https://doi.org/10.1109/DASC43569.2019.9081700
Maile, L., Hielscher, K.S., German, R.: Network calculus results for TSN: an introduction. In: 2020 Information Communication Technologies Conference (ICTC), pp. 131–140. IEEE, Nanjing, China (2020). https://doi.org/10.1109/ICTC49638.2020.9123308
Maile, L., Hielscher, K.S.J., German, R.: Delay-guaranteeing admission control for time-sensitive networking using the credit-based shaper. IEEE Open J. Commun. Soc. 3, 1834–1852 (2022). https://doi.org/10.1109/OJCOMS.2022.3212939
Maile, L., Voitlein, D., Grigorjew, A., Hielscher, K.S., German, R.: On the validity of credit-based shaper delay guarantees in decentralized reservation protocols. In: Proceedings of the 31st International Conference on Real-Time Networks and Systems. RTNS 2023, Association for Computing Machinery, New York, NY, USA (2023). https://doi.org/10.1145/3575757.3593644,, forthcoming
Niemann, K.H.: PROFINET Design Guideline Version 1.53. Tech. Rep. 8.062, PROFIBUS Nutzerorganisation e.V., Karlsruhe, Germany (2022)
Soni, A., Scharbarg, J.L., Ermont, J.: Efficient configuration of a QoS-aware AFDX network with deficit round robin. In: 2020 IEEE 18th International Conference on Industrial Informatics (INDIN). vol. 1, pp. 251–258 (2020). https://doi.org/10.1109/INDIN45582.2020.9442115, iSSN: 2378-363X
Yen, J.Y.: Finding the K shortest loopless paths in a network. Manage. Sci. 17(11), 712–716 (1971)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Maile, L., Hielscher, KS., German, R. (2024). Combining Static and Dynamic Traffic with Delay Guarantees in Time-Sensitive Networking. In: Kalyvianaki, E., Paolieri, M. (eds) Performance Evaluation Methodologies and Tools. VALUETOOLS 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 539. Springer, Cham. https://doi.org/10.1007/978-3-031-48885-6_8
Download citation
DOI: https://doi.org/10.1007/978-3-031-48885-6_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-48884-9
Online ISBN: 978-3-031-48885-6
eBook Packages: Computer ScienceComputer Science (R0)