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    Yang Xiangrui, Yan Jinli, Chen Bo, Peng Jintao, Li Junshuai, Quan Wei, Sun Zhigang. FlexTSN: A Flexible TSN Switch Implementation Model[J]. Journal of Computer Research and Development, 2021, 58(1): 153-163. DOI: 10.7544/issn1000-1239.2021.20190784
    Citation: Yang Xiangrui, Yan Jinli, Chen Bo, Peng Jintao, Li Junshuai, Quan Wei, Sun Zhigang. FlexTSN: A Flexible TSN Switch Implementation Model[J]. Journal of Computer Research and Development, 2021, 58(1): 153-163. DOI: 10.7544/issn1000-1239.2021.20190784

    FlexTSN: A Flexible TSN Switch Implementation Model

    • TSN (time-sensitive networking) has gained increasing attention from both industry and academia because of its ability to enable deterministic switching and best effort switching in the same network. Compared with traditional Ethernet, TSN provides quite different mechanisms ranging from time synchronization, gate control mechanism, to time-aware scheduling. This enables the Ethernet to provide the packet forwarding service with deterministic delay. Currently, IEEE 802.1 TSN Group is working on over 17 standards and drafts about TSN. And academic researchers also put much effort into proposing novel mechanisms from frame preemption to flow scheduling. However, there are rare, if exist, general models that enable rapid prototyping of TSN system. And we find this is quite important for rapid design and validation of key technologies in TSN. In this paper, FlexTSN, a flexible TSN switch model with loose-coupling modular design for TSN evaluation, is proposed. The TSN switch pipeline is decoupled into general processing modules and time-aware modules for supporting the rapid building of TSN switches. Moreover, FlexTSN provides a light-weight high-reliable network management mechanism by extending the PTP synchronization protocol for fine-grained centralized network monitoring and configuration. Furthermore, a simplified CQF (cyclical queuing and forwarding) model is adapted based on the FlexTSN prototype. The evaluation result shows that FlexTSN can provide clear abstractions for re-design and rapid evaluation of novel mechanisms in TSN.
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