Data-Age Analysis and Optimisation for Cause-Effect Chains in Automotive Control Systems

Johannes Schlatow, Mischa Mostl, Sebastian Tobuschat, Tasuku Ishigooka, Rolf Ernst
2018 2018 IEEE 13th International Symposium on Industrial Embedded Systems (SIES)  
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
more » ... asks. 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.
doi:10.1109/sies.2018.8442077 dblp:conf/sies/SchlatowMTIE18 fatcat:4d7tnph755g4ld5cajlp6l54qa