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Journal of Computer Networks and Communications
Volume 2016 (2016), Article ID 5196092, 12 pages
Research Article

Bounds on Worst-Case Deadline Failure Probabilities in Controller Area Networks

Electronics & Control Group, Teesside University, Middlesbrough TS1 3BA, UK

Received 6 November 2015; Revised 2 March 2016; Accepted 28 March 2016

Academic Editor: Tin-Yu Wu

Copyright © 2016 Michael Short. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Industrial communication networks like the Controller Area Network (CAN) are often required to operate reliably in harsh environments which expose the communication network to random errors. Probabilistic schedulability analysis can employ rich stochastic error models to capture random error behaviors, but this is most often at the expense of increased analysis complexity. In this paper, an efficient method (of time complexity ) to bound the message deadline failure probabilities for an industrial CAN network consisting of periodic/sporadic message transmissions is proposed. The paper develops bounds for Deadline Minus Jitter Monotonic (DMJM) and Earliest Deadline First (EDF) message scheduling techniques. Both random errors and random bursts of errors can be included in the model. Stochastic simulations and a case study considering DMJM and EDF scheduling of an automotive benchmark message set provide validation of the technique and highlight its application.