Arestova A, Hielscher KS, German R (2020)
Publication Type: Conference contribution
Publication year: 2020
Publisher: Springer
Book Volume: 12040 LNCS
Pages Range: 99-117
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISBN: 9783030430238
DOI: 10.1007/978-3-030-43024-5_7
With Time-Sensitive Networking (TSN), the IEEE 802.1 Task Group is extending the Ethernet standard by time-sensitive capabilities to establish a common ground for real-time communication systems via Ethernet. The Time-Sensitive Networking Task Group introduces a time-triggered transmission approach in IEEE 802.1Qbv to enable a deterministic transmission of time-critical network traffic, which requires scheduling strategies. Genetic algorithms are qualified to solve these scheduling problems in Time-Sensitive Networks. The difficulty is to design the genetic algorithm to find an optimal or a near-optimal solution for different complex problems taking performance and quality of the schedule into account. The complexity of schedules for TSN depends on the decision space of a network designer comprising the possibility to combine a variable number of network participants, a variable number of TSN flows, as well as assuming fixed or flexible routes for the flows. In this paper, we discuss a design approach for a hybrid genetic algorithm including chromosome representation for the routing and scheduling problems in TSN, the choice of genetic operators, and a neighborhood search to find a near-optimal solution. Additionally, we introduce an approach to compress the resulting schedules. Our evaluations show that the proposed hybrid genetic algorithm is able to compete with the well-adapted NEH algorithm in terms of schedule quality, and it outperforms the NEH algorithm regarding the computing time.
APA:
Arestova, A., Hielscher, K.-S., & German, R. (2020). Design of a hybrid genetic algorithm for time-sensitive networking. In Holger Hermanns, Holger Hermanns (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 99-117). Saarbrücken, DE: Springer.
MLA:
Arestova, Anna, Kai-Steffen Hielscher, and Reinhard German. "Design of a hybrid genetic algorithm for time-sensitive networking." Proceedings of the 20th International GI/ITG Conference on Measurement, Modelling and Evaluation of Computing Systems, MMB 2020, Saarbrücken Ed. Holger Hermanns, Holger Hermanns, Springer, 2020. 99-117.
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