Research Article
A Service Protection Mechanism of Deterministic Networking Based on Segment Routing
@INPROCEEDINGS{10.1007/978-3-031-23141-4_7, author={Tianchi Li and Yueping Cai}, title={A Service Protection Mechanism of Deterministic Networking Based on Segment Routing}, proceedings={Game Theory for Networks. 11th International EAI Conference, GameNets 2022, Virtual Event, July 7--8, 2022, Proceedings}, proceedings_a={GAMENETS}, year={2023}, month={1}, keywords={Deterministic Networking Service protection Segment routing Routing algorithm}, doi={10.1007/978-3-031-23141-4_7} }- Tianchi Li
Yueping Cai
Year: 2023
A Service Protection Mechanism of Deterministic Networking Based on Segment Routing
GAMENETS
Springer
DOI: 10.1007/978-3-031-23141-4_7
Abstract
Deterministic Networking (DetNet) provides guaranteed packet transport services of ultra-low packet loss and bounded delay for the critical traffic in real-time applications such as the industrial control and the power grid. DetNet guarantees reliable packet transmissions by forwarding replicated packets on redundant paths in parallel. This service protection mechanism of DetNet is Packet Replication Elimination and Ordering Functions (PREOF). However, how to obtain the redundant paths and implement the packet replication and elimination functions of the PREOF remains to be a great challenge. This paper proposes an improved PREOF mechanism based on Segment Routing (SR-PREOF). It designs an edge-disjoint path-pair routing algorithm based on the improved Link Pruning method (LP-EDJPP). The proposed SR-PREOF implements the scheme with the SR technology. Network simulation results show that the proposed SR-PREOF effectively improves the packet reception rate and reduces the end-to-end worst-case latency bound while achieving the comparable path reliability performance compared with the traditional PREOF. The packet reception rate of the SR-PREOF increases by 5.6% and the end-to-end worst-case latency bound decreases by 10.89% compared to the PREOF when the offered load is 0.7.
