Schedulability analysis of Time-Sensitive Networks with scheduled traffic and preemption support
2020 (English)In: Journal of Parallel and Distributed Computing, ISSN 0743-7315, E-ISSN 1096-0848, Vol. 144, p. 153-171Article in journal (Refereed) Published
Abstract [en]
The Time-Sensitive Networking (TSN) set of standards introduces in IEEE 802.1 switches and end stations novel features to meet the requirements of a broad spectrum of applications that are characterized by time-sensitive and mission-critical traffic flows. In particular, the IEEE802.1Qbv-2015 amendment introduces enhancements that provide temporal isolation for scheduled traffic, i.e., a traffic class that requires transmission based on a known timescale, while the IEEE802.1Qbu-2016 introduces preemption as a mechanism to allow time-critical messages to interrupt ongoing non time-critical transmissions. Both amendments, that are now enrolled in the IEEE802.1Q-2018 standard, are very important for industrial networks, where scheduled traffic and low-latency real-time flows have to coexist, on the same network, with best-effort transmissions. In this context, this work presents a response time analysis of TSN networks that encompasses the enhancements for scheduled traffic and preemption, in various combinations. The paper presents the proposed analysis and a performance comparison between the response times calculated by the analysis and the response times obtained through OMNeT++ simulations in three different scenarios. © 2020 Elsevier Inc.
Place, publisher, year, edition, pages
Academic Press Inc. , 2020. Vol. 144, p. 153-171
Keywords [en]
Response time analysis, Schedulability analysis, Scheduled traffic, Simulation, Time-sensitive networking, IEEE Standards, Industrial networks, Mission critical, Performance comparison, Response-time analysis, Scheduled traffics, Temporal isolation, Time-critical messages, Time switches
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:mdh:diva-49117DOI: 10.1016/j.jpdc.2020.06.001ISI: 000546677400012Scopus ID: 2-s2.0-85086393651OAI: oai:DiVA.org:mdh-49117DiVA, id: diva2:1447303
2020-06-252020-06-252020-09-21Bibliographically approved