Conference proceeding
Real-Time Scheduling for 802.1Qbv Time-Sensitive Networking (TSN): A Systematic Review and Experimental Study
2024 IEEE 30th Real-Time and Embedded Technology and Applications Symposium (RTAS), pp.108-121
05/13/2024
DOI: 10.1109/RTAS61025.2024.00017
Abstract
Time-Sensitive Networking (TSN) has been recognized as one of the key enabling technologies for Industry 4.0 and has been deployed in many mission- and safety-critical applications e.g., automotive and aerospace systems. Given the stringent real-time requirements of these applications, the Time-Aware Shaper (TAS) draws special attention among TSN's many traffic shapers due to its ability to achieve deterministic timing guarantees. Many scheduling methods for TAS shapers have been recently developed that claim to improve system schedulability. However, these scheduling methods have yet to be thoroughly evaluated, especially through experimental comparisons, to provide a systematical understanding of their performance in diverse application scenarios. In this paper, we fill this gap by presenting a systematic review and experimental study on existing TAS-based scheduling methods for TSN. We first categorize the system models employed in these works along with the specific problems they aim to solve, and outline the fundamental considerations in the designs of TAS-based scheduling methods. We then perform an extensive evaluation on 17 representative solutions using both high-fidelity simulations and a real-life TSN testbed, and compare their performance under both synthetic scenarios and real-life industrial use cases. Through these studies, we identify the limitations of individual scheduling methods and highlight several important findings. We expect this work will provide foundational knowledge and performance benchmarks needed for future studies on real-time TSN scheduling.
Details
- Title: Subtitle
- Real-Time Scheduling for 802.1Qbv Time-Sensitive Networking (TSN): A Systematic Review and Experimental Study
- Creators
- Chuanyu Xue - University of ConnecticutTianyu Zhang - University of ConnecticutYuanbin Zhou - Singapore University of Technology and DesignMark Nixon - EmersonAndrew Loveless - Johnson Space CenterSong Han - University of Connecticut
- Resource Type
- Conference proceeding
- Publication Details
- 2024 IEEE 30th Real-Time and Embedded Technology and Applications Symposium (RTAS), pp.108-121
- Publisher
- IEEE; LOS ALAMITOS
- DOI
- 10.1109/RTAS61025.2024.00017
- ISSN
- 1545-3421
- eISSN
- 2642-7346
- Grant note
- 80NSSC19K1076 / NASA STRI Resilient Extraterrestrial Habitats Institute (10.13039/100000104) CNS-1932480,CNS-2008463,CCF-2028875,CNS-1925706 / National Science Foundation (10.13039/100000001)
- Language
- English
- Date published
- 05/13/2024
- Academic Unit
- Computer Science
- Record Identifier
- 9984696584802771
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