LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Joint Algorithm of Message Fragmentation and No-Wait Scheduling for Time-Sensitive Networks

Photo by jontyson from unsplash

Time-sensitive networks (TSNs) support not only traditional best-effort communications but also deterministic communications, which send each packet at a deterministic time so that the data transmissions of networked control systems… Click to show full abstract

Time-sensitive networks (TSNs) support not only traditional best-effort communications but also deterministic communications, which send each packet at a deterministic time so that the data transmissions of networked control systems can be precisely scheduled to guarantee hard real-time constraints. No-wait scheduling is suitable for such TSNs and generates the schedules of deterministic communications with the minimal network resources so that all of the remaining resources can be used to improve the throughput of best-effort communications. However, due to inappropriate message fragmentation, the realtime performance of no-wait scheduling algorithms is reduced. Therefore, in this paper, joint algorithms of message fragmentation and no-wait scheduling are proposed. First, a specification for the joint problem based on optimization modulo theories is proposed so that off-the-shelf solvers can be used to find optimal solutions. Second, to improve the scalability of our algorithm, the worst-case delay of messages is analyzed, and then, based on the analysis, a heuristic algorithm is proposed to construct low-delay schedules. Finally, we conduct extensive test cases to evaluate our proposed algorithms. The evaluation results indicate that, compared to existing algorithms, the proposed joint algorithm improves schedulability by up to 50%.

Keywords: time; message fragmentation; wait scheduling; time sensitive

Journal Title: IEEE/CAA Journal of Automatica Sinica
Year Published: 2021

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.