Synthesizing time-triggered schedules for switched networks with faulty links

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Abstract

Time-triggered (TT) switched networks are a deterministic communication infrastructure used by real-time distributed embedded systems. These networks rely on the notion of globally discretized time (i.e. time slots) and a static TT schedule that prescribes which message is sent through which link at every time slot, such that all messages reach their destination before a global timeout. These schedules are generated offline, assuming a static network with fault-free links, and entrusting all error-handling functions to the end user. Assuming the network is static is an over-optimistic view, and indeed links tend to fail in practice. We study synthesis of TT schedules on a network in which links fail over time and we assume the switches run a very simple error-recovery protocol once they detect a crashed link. We address the problem of finding a pk; qresistant schedule; namely, one that, assuming the switches run a fixed error-recovery protocol, guarantees that the number of messages that arrive at their destination by the timeout is at least no matter what sequence of at most k links fail. Thus, we maintain the simplicity of the switches while giving a guarantee on the number of messages that meet the timeout. We show how a pk; q-resistant schedule can be obtained using a CEGAR-like approach: find a schedule, decide whether it is pk; q-resistant, and if it is not, use the witnessing fault sequence to generate a constraint that is added to the program. The newly added constraint disallows the schedule to be regenerated in a future iteration while also eliminating several other schedules that are not pk; q-resistant. We illustrate the applicability of our approach using an SMT-based implementation.

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APA

Avni, G., Guha, S., & Rodriguez-Navas, G. (2016). Synthesizing time-triggered schedules for switched networks with faulty links. In Proceedings of the 13th International Conference on Embedded Software, EMSOFT 2016. Association for Computing Machinery, Inc. https://doi.org/10.1145/2968478.2968499

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