Computer Science

Computer Science ›› 2023, Vol. 50 ›› Issue (7): 286-292.doi: 10.11896/jsjkx.220500178

• Computer Network • Previous Articles     Next Articles

Multi-objective Online Hybrid Traffic Scheduling Algorithm in Time-sensitive Networks

WANG Jiaxing1, YANG Sijin2, ZHUANG Lei2, SONG Yu2, YANG Xinyu1   

  1. 1 School of Cyber Science and Engineering,Zhengzhou University,Zhengzhou 450002,China
    2 School of Computer and Artificial Intelligence,Zhengzhou University,Zhengzhou 450001,China
  • Received:2022-05-18 Revised:2022-11-15 Online:2023-07-15 Published:2023-07-05
  • About author:WANG Jiaxing,born in 1998,postgra-duate,is a member of China Computer Federation.His main research interests include time-sensitive networking and next generation internet.ZHUANG Lei,born in 1963,Ph.D supervisor,is a member of China Compu-ter Federation.Her main research in-terests include future network architecture,time sensitive networking,and network virtualization.
  • Supported by:
    State Grid Corporation of China Science and Technology Project(5700-202024176A-0-0-00).

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Abstract: The time-sensitive network(TSN) based on the Ethernet protocol meets various requirements such as real-time transmission and interconnection of industrial networks through different types of streams.However,when time-triggered(TT) streams,audio/video bridging(AVB) streams,and best-effort(BE) streams are transmitting in the network,it is unavoidable that the same stream competes for queues and different streams interfere with each other.Aiming at the problem that multiple traffic scheduling in TSN affects the end-to-end delay determinism,this paper proposes an improved particle swarm optimization(PSO) for online mixed-traffic analysis.The algorithm dynamically calculates paths for mixed traffic based on network conditions,and accelerates searches to meet the time limits of online computation by reducing redundant searches and constraining particle velocities to avoid particles falling into local optimizations.What’s more,the algorithm sets corresponding fitness functions for different types of traffic to reduce mutual interference between mixed traffic and queuing delay.Simulation results show that proposed algorithm can effectively improve the success rate of mixed traffic transmission in TSN network,and has stable performance and good computing efficiency.

Key words: Time-sensitive network, traffic scheduling, Particle swarm optimization, Mixed traffic

CLC Number: 

  • TP393
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