Conference proceeding
Work-in-Progress: An Open-Source Evaluation Framework for Time-Sensitive Networking Scheduling Research
Proceedings - Real-Time Systems Symposium, pp.628-631
12/02/2025
DOI: 10.1109/RTSS66672.2025.00064
Abstract
Reproducing and extending research on TimeSensitive Networking (TSN) scheduling has become increasingly challenging, as most published methods lack open-source implementations. The few available implementations are often scattered across different programming languages and formats, forcing researchers to reimplement algorithms from scratch-a time-consuming and error-prone process that hinders fair comparison of methods and slows research progress. In this work, we present TSNKit, an open-source toolkit designed to address these challenges through: (i) standardized implementations of a broad set of representative scheduling algorithms with unified interfaces for integrating new methods; (ii) an end-to-end pipeline covering test case generation, scheduling, and simulation-based validation; and (iii) comprehensive benchmarking modules for reproducible performance evaluation. TSNKit enables researchers to reproduce published results, extend existing methods, and perform fair comparisons across algorithms. Our ongoing work extends TSNKit to support multiple traffic shapers beyond Time-Aware Shaping (TAS), improve benchmark efficiency through enhanced scheduling heuristics, and incorporate hardware-in-the-loop capabilities for seamless real-world deployment.
Details
- Title: Subtitle
- Work-in-Progress: An Open-Source Evaluation Framework for Time-Sensitive Networking Scheduling Research
- Creators
- Chuanyu Xue - University of ConnecticutElaine Hu - Chestnut Hill CollegeTianyu Zhang - University of IowaSong Han - University of Connecticut
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings - Real-Time Systems Symposium, pp.628-631
- DOI
- 10.1109/RTSS66672.2025.00064
- eISSN
- 2576-3172
- Publisher
- IEEE
- Language
- English
- Date published
- 12/02/2025
- Academic Unit
- Computer Science
- Record Identifier
- 9985116070802771
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