An efficient schedulability analysis for optimizing systems with adaptive mixed-criticality scheduling

In the design optimization of real-time systems, the schedulability analysis is used to define the feasibility region within which tasks meet their deadlines, so that optimization algorithms can find the best solution within the region. However, the current analysis techniques for systems with adaptive mixed-criticality (AMC) scheduling are based on response time calculation, which are too complex for optimization purposes. In this paper, we provide a simpler schedulability test based on request bound functions, which allows an efficient definition of the feasibility region for AMC. We prove that the new analysis is safe with bounded pessimism. Experimental results show that our analysis provides much better scalability for optimization procedures, with only small loss of performance (less than 7% in weighted schedulability, and no more than 4% in optimization objectives).