As CAN (Controller Area Network) is increasingly used in safety-critical applications, there is a need for accurate predictions of failure probability. In this paper we provide a general probabilistic schedulability analysis technique which is applied specifically to CAN to determine the effect of random network faults on the response times of messages. The resultant probability distribution of response times can be used to provide probabilistic guarantees of real-time be haviour in the presence of faults. The analysis is designed to have as little pessimism as possible but never be optimistic. Through simulations, this is shown to be the case. It is easy to apply and can provide useful evidence for justification of an event-triggered bus in a critical system.
Real-time networks have tight communication latency and minimal jitter requirements. One way to ensure these requirements is the implementation of a static schedule, which defines the transmission points in time of time-triggered frames. Synthesizing such static schedules is known to be an NP-complete problem where the complexity is driven by the large number of constraints imposed by the network. Satisfiabily Modulo Theories (SMT) have been proven powerful tools to synthesize schedules of medium-to-large industrial networks. However, the schedules of new extremely large networks, such as integrated multi-machine factory networks, are defined by an extremely large number of constraints exceeding the capabilities of being synthesized by the tool alone.This paper presents a decomposition approach that will allow us to improve to synthesize schedules with up to two orders of magnitude in terms of the number of constraints that can be handled. We also present an implementation of a dependency tree on top of the decomposition approach to address applicationimposed constraints between frames.
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