4.7 Article Proceedings Paper

Constraint programming approaches to joint routing and scheduling in time-sensitive networks

期刊

COMPUTERS & INDUSTRIAL ENGINEERING
卷 157, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cie.2021.107317

关键词

Time-sensitive networking; Real-time communication; Time-triggered communication; Isochronous traffic; Integer linear programming; Satisfiability Modulo Theories

资金

  1. European Regional Development Fund under the project AIReasoning [CZ.02.1.01/0.0/0.0/15_003/0000466]

向作者/读者索取更多资源

This paper discusses the problem of joint routing and scheduling in real-time communication networks, proposing two models in Constraint Programming formalism to ensure the deterministic nature of the communication. Experimental results demonstrate that the novel approach presented in this paper significantly increases schedulability and outperforms state-of-the-art methods in terms of performance.
The deterministic behavior of real-time communication networks is achieved by time-triggered periodic schedules for critical data traffic. Calculating such a schedule requires satisfying a lot of constraints, which in practice may be difficult due to the increasing number of data flows in the network. In the current approaches, the routes of flows are usually given or determined separately from the scheduling process. If the routes of flows can be computed jointly with scheduling, more flows could be scheduled since the algorithm chooses among alternative paths. This paper formalizes the problem of joint routing and scheduling of time-triggered periodic communication in Time-Sensitive Networks, guaranteeing the required deterministic nature of the communication, and proposes two models in Constraint Programming formalism. We further apply the Logic-Based Benders Decomposition on the proposed models and give an extensive experimental evaluation of our solutions showing that our novel approach that models waiting of frames in queues along with the Logic-Based Benders Decomposition exhibits the best performance and significantly increases the schedulability over the state-of-the-art methods.

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