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Data Flow Control for Network Load Balancing in IEEE Time-Sensitive Networks for Automation
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  • Thomas Weichlein ,
  • Shujun Zhang ,
  • Pengzhi Li ,
  • Xu Zhang
Thomas Weichlein
University of Gloucestershire

Corresponding Author:[email protected]

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Shujun Zhang
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Pengzhi Li
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IEEE time-sensitive networks (TSN) offer redundant paths for automation networks that are essential preconditions for network load balancing (NLB) or distribution. They also provide several traffic shapers and schedulers with different impacts on the data flow control. The selection of the right traffic shaper or scheduler for an automation network is challenging. Their influence depends on various network parameters such as network extension, network cycles, application cycles, and the amount of data per traffic class and network cycle. In this study, the data flow control for network load balancing in an automation TSN using different traffic shapers and schedulers was investigated. The effects of the network parameters on the shapers and schedulers were derived and imported into the data flow control model of the automation network. The sample networks were simulated, and performance comparisons were performed. The results show that enhancements for scheduled traffic (EST), strict priority queuing (SPQ), and the combination of SPQ with frame preemption are better scheduler selections in connection with larger networks, fast network cycles, and fast application cycles. The cyclic queuing and forwarding (CQF) shaper and asynchronous traffic shaper (ATS) are only alternatives for data load control in small networks or in conjunction with slow applications.
2023Published in IEEE Access volume 11 on pages 14044-14060. 10.1109/ACCESS.2023.3243286