An improved credit-based shaper for TSN

Zeya Li; Yang Liu; Longqing Gong; Danni Xu; Jinfeng Tang

doi:10.1117/12.3031997

8 June 2024 An improved credit-based shaper for TSN

Zeya Li, Yang Liu, Longqing Gong, Danni Xu, Jinfeng Tang

Proceedings Volume 13171, Third International Conference on Algorithms, Microchips, and Network Applications (AMNA 2024); 131711B (2024) https://doi.org/10.1117/12.3031997
Event: 3rd International Conference on Algorithms, Microchips and Network Applications (AMNA 2024), 2024, Jinan, China

Abstract

In response to the growing demands of real-time application scenarios, TSN has emerged as a crucial solution. However, the implementation of a credit-based shaper to ensure low-priority traffic transmission may unintentionally result in burst traffic generation. This could lead to storage overflow and potential data loss, posing a significant challenge to the efficient operation of TSN networks. To address this issue, we propose the ICBS algorithm, an enhancement of the original CBS mechanism, which preserves the fundamental principles of preventing low-priority starvation while mitigating the risk of burst traffic generation. The ICBS algorithm demonstrates enhanced fine-grained operation of data frames by refining the credit calculation method, effectively minimizing the occurrence of bursts in AVB traffic. Furthermore, we have devised an ICBS adaptation evaluation algorithm to assess the rationality of pre-scheduling results for AVB, ensuring optimal resource allocation. The simulation results demonstrate that the proposed ICBS algorithm effectively achieves its objective of low-priority traffic transmission with extra worst-case delay cost, making it a highly suitable substitute for existing TSN shaper solutions. The ICBS algorithm not only enhances the efficiency and reliability of TSN networks but also paves the way for future advancements in real-time application scenarios.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zeya Li, Yang Liu, Longqing Gong, Danni Xu, and Jinfeng Tang "An improved credit-based shaper for TSN", Proc. SPIE 13171, Third International Conference on Algorithms, Microchips, and Network Applications (AMNA 2024), 131711B (8 June 2024); https://doi.org/10.1117/12.3031997

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Data transmission

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Analytical research

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Detection and tracking algorithms

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