Probabilistic analysis for mixed criticality systems using fixed priority preemptive scheduling
Dorin Maxim, Robert Ian Davis, Liliana Cucu‐Grosjean, Arvind Easwaran · 2017
This paper introduces probabilistic analysis for fixed priority preemptive scheduling of mixed criticality systems on a uniprocessor using the Adaptive Mixed Criticality (AMC) and Static Mixed Criticality (SMC) schemes. We compare this analysis to existing deterministic methods, highlighting the performance gains that can be obtained by utilising more detailed information about worst-case execution time estimates described in terms of probability distributions. Besides improvements in schedulability, we also demonstrate significant gains in terms of the budgets that can be allocated to LO-criticality tasks.