Delay analysis of TSN based industrial networks with preemptive traffic using network calculus
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Accepted Version
Date
2023-07-24
Authors
Seliem, Mohamed
Zahran, Ahmed
Pesch, Dirk
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published Version
Abstract
Time-Sensitive Networking (TSN) extends traditional Ethernet to support data traffic with ultra-reliability and time-critical requirements for a range of applications in industrial automation, automotive, and aerospace. The TSN standards present guidelines to integrate different types of data traffic over a single converged network. Therefore, it is becoming an enabling technology towards the Industry 4.0 vision of integrating information and operational technologies within future Industrial Internet of Things networks. In this paper, we develop a network calculus based framework to analyse TSN based industrial networks supporting a range of data traffic classes. We apply the framework to study and analyse a well-known industrial use case, Quality Checks After Production (QCAP), with four data traffic types with different requirements in terms of reliability and end-to-end latency. In our evaluation, we validate our framework with a computer simulation model and compare the tightness of the calculated delay bounds to a state-of-the-art approach. We then use our model to analyse the upper bounds on the worst-case delay of the different QCAP traffic types and assess the factors that impact end-to-end delay, e.g. flow offset and critical links. Finally, we compare various credit accumulation rates and their impact on the traffic delay bounds.
Description
Keywords
Time-Sensitive Networking (TSN) , Industrial networks , Network Calculus (NC) , IIoT , Deterministic latency , Quality control
Citation
Seliem, M., Zahran, A. and Pesch, D. (2023) 'Delay analysis of TSN based industrial networks with preemptive traffic using network calculus', 2023 IFIP Networking Conference (IFIP Networking), Barcelona, Spain, 12-15 June, pp. 1-9. doi: 10.23919/IFIPNetworking57963.2023.10186400.