Performance Evaluation of Gang Scheduling in Distributed Real-Time Systems with Possible Software Faults

Distributed real-time systems play an increasingly vital role in our daily life. The most important aspect of such systems is the scheduling algorithm, which must guarantee that every job in the system will meet its deadline. In this paper we evaluate by simulation the performance of strategies for the scheduling of parallel jobs (gangs) in a homogeneous distributed real-time system with possible software faults. We provide an alternative version for each scheduling policy, which allows imprecise computations, and we propose a performance metric applicable to our problem. Our simulation results show that the alternative versions of the algorithms exhibit promising performance.