A Feedback-Based Adaptive Algorithm for Combined Scheduling with Fault-Tolerance in Real-Time Systems

Abstract. In this paper, we propose a feedback-based combined scheduling algorithm with fault tolerance for applications that have both periodic tasks and aperiodic tasks in real-time uniprocessor systems. Each periodic task is assumed to have a primary copy and a backup copy. By using the rate monotonic scheduling and deferrable server algorithm, we create two servers, one for serving aperiodic tasks and the other for executing backup copies of periodic tasks. The goal is to maximize the schedulability of aperiodic tasks while keeping the recovery rate of periodic tasks close to 100%. Our algorithm uses feedback control technique to balance the CPU allocation between the backup server and the aperiodic server. Our simulation studies show that the algorithm can adapt the parameters of the servers to recover the failed periodic tasks. Keywords: Real-time systems, feedback-based scheduling, deferrable server algorithm, fault-tolerance.