Data Flow Control for Network Load Balancing in IEEE Time-Sensitive
Networks for Automation
Abstract
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.