Schedulability Analysis in Time-Sensitive Networking: A Systematic Literature Review

TL;DR

This paper systematically reviews 123 research papers over 15 years on schedulability analysis in Time-Sensitive Networking, categorizing methods, comparing their strengths, and highlighting future challenges for ensuring real-time guarantees.

Contribution

It provides a comprehensive overview and classification of schedulability analysis techniques in TSN, clarifies evaluation scenarios, and identifies open challenges for future research.

Findings

Categorized schedulability analysis methods and their strengths and weaknesses.

Identified key network scenarios and traffic classes in evaluations.

Highlighted future challenges and directions in TSN schedulability analysis.

Abstract

Time-Sensitive Networking (TSN) is a set of standards that provide low-latency, high-reliability guarantees for the transmission of traffic in networks, and it is becoming an accepted solution for complex time-critical systems such as those in industrial automation and the automotive. In time-critical systems, it is essential to verify the timing predictability of the system, and the application of scheduling mechanisms in TSN can also bring about changes in system timing. Therefore, schedulability analysis techniques can be used to verify that the system is scheduled according to the scheduling mechanism and meets the timing requirements. In this paper, we provide a clear overview of the state-of-the-art works on the topic of schedulability analysis in TSN in an attempt to clarify the purpose of schedulability analysis, categorize the methods of schedulability analysis and compare their respective strengths and weaknesses, point out the scheduling mechanisms under analyzing and the corresponding traffic classes, clarify the network scenarios constructed during the evaluation and list the challenges and directions still needing to be worked on in schedulability analysis in TSN. To this end, we conducted a systematic literature review and finally identified 123 relevant research papers published in major conferences and journals in the past 15 years. Based on a comprehensive review of the relevant literature, we have identified several key findings and emphasized the future challenges in schedulability analysis for TSN.