Electronics Optics & Control, Volume. 32, Issue 2, 54(2025)

Airborne TSN End-to-End Worst-Case Delay Analysis Model Based on Network Calculation

CHEN Chen1...2, ZHENG Zhiming2, ZHANG Xiaobei1 and ZHANG Qi1 |Show fewer author(s)
Author Affiliations
  • 1School of Communication and Information Engineering, Shanghai University, Shanghai 200000, China
  • 2Shanghai Aircraft Design and Research Institute, Shanghai 201000, China
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    The Frame Replication and Elimination for Reliability (FRER) redundancy mechanism in Time Sensitive Network (TSN) improves the reliability of the network through the replication and elimination functions of data packets. Data packets are copied onto the redundant paths through replication function, and then the paths are merged and the elimination function removes duplicates. This redundancy scheme affects the timing behavior of the TSN, resulting in increased end-to-end uncertainty. To this end, by combing the Time Aware Shaper (TAS) algorithm, the delay problem caused by the FRER mechanism is reduced by setting different gating parameters, and a worst-case delay calculation model based on Network Calculus (NC) is provided for airborne TSN, and the upper bound of end-to-end delay in multi-service data transmission is quantitatively analyzed to evaluate whether the airborne network under TSN meets the communication requirements. Finally, the network topology of certain aircraft is simulated by OMNET, which verifies the applicability of TSN technology in civil aircraft avionics network and the availability of this model for end-to-end worst delay analysis of airborne TSN communication system, and provides a basis for network resource optimization.

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    CHEN Chen, ZHENG Zhiming, ZHANG Xiaobei, ZHANG Qi. Airborne TSN End-to-End Worst-Case Delay Analysis Model Based on Network Calculation[J]. Electronics Optics & Control, 2025, 32(2): 54

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    Paper Information

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    Received: Dec. 18, 2023

    Accepted: Feb. 20, 2025

    Published Online: Feb. 20, 2025

    The Author Email:

    DOI:10.3969/j.issn.1671-637x.2025.02.009

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