Enhancing Low-Latency and High-Reliability Data Forwarding for In-Vehicle Time-Sensitive Networks
To satisfy the low delay, low jitter, and high success rate requirements for in-vehicle networks, IEEE 802.1 Task Group proposed Time-Sensitive Networking (TSN), which has aroused increasing attention in managing time-critical services in networks. This paper resolves the following issue: <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">how to minimize the worst-case response time (WCRT) of frame forwarding in TSN under no-wait scenarios to guarantee low-latency transmission, stability, and high success rate for in-vehicle TSN networks?</i> Currently, some work resolves this problem by leveraging integer linear programming, and others apply heuristic methods to avoid the time complexity problem, but the success rate is affected since they are prone to get trapped in local optima. To reach a balance between time-complexity and success rate, a scheme named Frame Dynamic Priority Scheduling Mechanism (FDPSM) is proposed, where the frame dynamic priority levels are set up and frames are scheduled accordingly. The target is to maximize the success rate and minimize the WCRT for in-vehicle networks. We evaluate the proposed mechanism from aspects such as traffic forwarding time, size of windows, number of hops, and the network load, together with success rate and the simulation results demonstrate the advantages of the FDPSM for in-vehicle TSN networks.
Authors
- Wanqing Guan (ORCID: https://orcid.org/0000-0002-5205-7936)
- Victor C. M. Leung (ORCID: https://orcid.org/0000-0003-3529-2640)
- Haitong Sun (ORCID: https://orcid.org/0000-0002-6629-0376)
- Hui Ma (ORCID: https://orcid.org/0000-0002-2851-0091)
- Haijun Zhang (ORCID: https://orcid.org/0000-0002-0236-6482)
- Xiangnan Liu (ORCID: https://orcid.org/0000-0002-0094-8948)
Institutions
- Shenzhen University (CN)
- KTH Royal Institute of Technology (SE)
Publication Details
- Journal
- IEEE Transactions on Vehicular Technology
- Published
- 2025-03-18
- DOI
- https://doi.org/10.1109/tvt.2025.3552531
- Citations
- 2
- Primary Topic
- Context-Aware Activity Recognition Systems
- Type
- article
- Field-Weighted Citation Impact
- 2.55