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Design of a Hybrid Genetic Algorithm for Time-Sensitive Networking

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Measurement, Modelling and Evaluation of Computing Systems (MMB 2020)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 12040))

Abstract

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.

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Notes

  1. 1.

    \( e_k \) for end-system and \( s_k \) for switch.

  2. 2.

    We assume that route 1 provides the least traffic load without giving a concrete example network.

  3. 3.

    The delay introduced between subsequent devices on a flow path is described as the static network delay from Sect. 3.2.

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Authors and Affiliations

  1. Department of Computer Science 7, Computer Networks and Communication Systems, University of Erlangen-Nürnberg, Martensstraße 3, 91058, Erlangen, Germany

    Anna Arestova, Kai-Steffen Jens Hielscher & Reinhard German

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  1. Anna Arestova
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  2. Kai-Steffen Jens Hielscher
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  3. Reinhard German
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Correspondence to Anna Arestova .

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  1. Saarland University, Saarbrücken, Germany

    Holger Hermanns

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Arestova, A., Hielscher, KS.J., German, R. (2020). Design of a Hybrid Genetic Algorithm for Time-Sensitive Networking. In: Hermanns, H. (eds) Measurement, Modelling and Evaluation of Computing Systems. MMB 2020. Lecture Notes in Computer Science(), vol 12040. Springer, Cham. https://doi.org/10.1007/978-3-030-43024-5_7

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  • DOI: https://doi.org/10.1007/978-3-030-43024-5_7

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