Dynamic stream partitioning for time-triggered traffic in Time-Sensitive Networking

Time-Sensitive Networking (TSN) is a promising network technology that can ensure bounded latency and jitter for industrial real-time scenarios. It establishes the IEEE 802.1 Qbv standard to precisely control the periodic transmission time of the time-triggered (TT) traffic. However, it is still a c...

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Vydáno v:Computer networks (Amsterdam, Netherlands : 1999) Ročník 248; s. 110492
Hlavní autoři: Chen, Zhuoxing, Lu, Yiqin, Wang, Haihan, Qin, Jiancheng, Wang, Meng, Pan, Weiqiang
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 01.06.2024
Témata:
Deterministic communications
Scheduling
Stream partitioning
Time-Sensitive Networking
Time-triggered traffic
Deterministic communications
Time-triggered traffic
Scheduling
Time-Sensitive Networking
Stream partitioning
ISSN:1389-1286, 1872-7069
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Shrnutí:Time-Sensitive Networking (TSN) is a promising network technology that can ensure bounded latency and jitter for industrial real-time scenarios. It establishes the IEEE 802.1 Qbv standard to precisely control the periodic transmission time of the time-triggered (TT) traffic. However, it is still a challenge to efficiently schedule the TT traffic in large-scale networks with high transmission performance. In this paper, we propose a novel method called dynamic stream partitioning (DSP) to solve this problem. It satisfies the IEEE 802.1 Qbv standard and can significantly reduce the scheduling time by reducing the number of constraints. Based on the DSP method, we analyze the impact of stream partitioning on the transmission performance of the TT traffic, and propose an indicator called Normalized Degradation of Performance (NDOP) to quantify it dynamically. Furthermore, we design a partitioning-aware dynamic routing (PADR) to expand the scheduling space. Integrated with NDOP and PADR, we propose a joint routing and dynamic stream partitioning (JR/DSP) algorithm. Extensive simulation experiments verify that the proposed JR/DSP algorithm has higher scalability, transmission performance, and schedulability compared to the static stream partitioning algorithms. •The increase in network scale typically results in a significant increase in scheduling time for time-triggered traffic.•Dynamic partitioning and scheduling the time-triggered traffic can significantly reduce its scheduling time.•An analyzed stream partitioning process can improve the transmission performance of time-triggered traffic.•In Time-Sensitive Networking, the routing strategy based on the dynamic stream partitioning method can effectively expand the scheduling space.
ISSN:1389-1286
1872-7069
DOI:10.1016/j.comnet.2024.110492