Performance Analysis of Switch Buffer Management Policy for Mixed-Critical Traffic in Time-Sensitive Networks

Ling Zheng (), Yingge Feng, Weiqiang Wang and Qianxi Men
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Ling Zheng: School of Communication and Information Engineering, Xi’an University of Posts and Telecommunications, Xi’an 710121, China
Yingge Feng: School of Communication and Information Engineering, Xi’an University of Posts and Telecommunications, Xi’an 710121, China
Weiqiang Wang: School of Communication and Information Engineering, Xi’an University of Posts and Telecommunications, Xi’an 710121, China
Qianxi Men: School of Communication and Information Engineering, Xi’an University of Posts and Telecommunications, Xi’an 710121, China

Mathematics, 2025, vol. 13, issue 21, 1-23

Abstract: Time-sensitive networking (TSN), a cutting-edge technology enabling efficient real-time communication and control, provides strong support for traditional Ethernet in terms of real-time performance, reliability, and deterministic transmission. In TSN systems, although time-triggered (TT) flows enjoy deterministic delay guarantees, audio video bridging (AVB) and best effort (BE) traffic still share link bandwidth through statistical multiplexing, a process that remains nondeterministic. This competition in shared memory switches adversely affects data transmission performance. In this paper, a priority queue threshold control policy is proposed and analyzed for mixed-critical traffic in time-sensitive networks. The core of this policy is to set independent queues for different types of traffic in the shared memory queuing system. To prevent low-priority traffic from monopolizing the shared buffer, its entry into the queue is blocked when buffer usage exceeds a preset threshold. A two-dimensional Markov chain is introduced to accurately construct the system’s queuing model. Through detailed analysis of the queuing model, the truncated chain method is used to decompose the two-dimensional state space into solvable one-dimensional sub-problems, and the approximate solution of the system’s steady-state distribution is derived. Based on this, the blocking probability, average queue length, and average queuing delay of different priority queues are accurately calculated. Finally, according to the optimization goal of the overall blocking probability of the system, the optimal threshold value is determined to achieve better system performance. Numerical results show that this strategy can effectively allocate the shared buffer space in multi-priority traffic scenarios. Compared with the conventional schemes, the queue blocking probability is reduced by approximately 40% to 60%.

Keywords: time-sensitive network; queuing model; two-dimensional Markov chain; buffer management (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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