A Parallel Algorithm for EDF-Schedulability Analysis of Multi-modal Real-Time Systems

Modern real-time embedded systems often require the capability of switching between operating modes to adapt in dynamically changing environments. The development of such real-time multi-modal systems fundamentally relies upon effective schedulability analysis. Recently, researchers have proposed serial schedulability analysis algorithms for multi-modal systems that account for mode changes at both software level (e.g., changing the set of executing tasks) and hardware level (e.g., changing the operating speed of a processor). However, these algorithms have high runtime complexity which limits their practical usage as schedulability analysis in system design-space exploration. In this paper, we design a parallel algorithm as an efficient solution to the problem of determining the schedulability of uniprocessor multi-modal real-time systems scheduled by EDF. By emphasizing a balanced workload distribution and restricting the number of synchronizations, our parallel algorithm achieves a near-perfect speedup observable both theoretically and experimentally. Experimental results show that the runtime of our parallel algorithm is very low even for systems with large number of modes, making it a tractable choice for design-space exploration of real-time multi-modal systems.