Data-Age Analysis and Optimisation for Cause-Effect Chains in Automotive Control Systems
Automotive control systems typically have latency requirements for certain cause-effect chains. When implementing and integrating these systems, these latency requirements must be guaranteed e.g. by applying a worst-case analysis that takes all indeterminism and limited predictability of the timing behaviour into account. In this paper, we address the latency analysis for multi-rate distributed cause-effect chains considering staticpriority preemptive scheduling of offset-synchronised periodic tasks. We particularly focus on data age as one representative of the two most common latency semantics. Our main contribution is an Mixed Integer Linear Program-based optimisation to select design parameters (priorities, task-to-processor mapping, offsets) that minimise the data age. In our experimental evaluation, we apply our method to two real-world automotive use cases.
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