Resource-Optimal Fault-Tolerant Scheduler Design for Task Graphs Using Supervisory Control

Real-time control applications are highly parallelizable and can be used to effectively harness the capacity of a given computing platform when appropriately scheduled. Given a multicore platform for executing a set of parallelizable applications, it is necessary to ensure proper functioning of the system even in the presence of transient processor faults. However, most existing scheduling approaches for parallel applications have been heuristic schemes which are often based only on the satisfaction of a set of sufficiency conditions and cannot take into consideration of all necessary schedulability requirements. Consequently, such schemes lead to suboptimal usage of resources resulting in higher design costs. Formal model-based safe design methodologies such as supervisory control are often desirable in the design of correct-by-construction fault-tolerant schedulers. This article proposes a supervisory control-based fault-tolerant scheduler synthesis scheme for real-time tasks modeled as precedence-constrained task graphs, executing on multicores. Further, we devise search strategies to obtain schedules that 1) maximize fault-tolerance and 2) minimize peak-power (MPP) dissipation. Conducted experiments using real-world benchmarks reveal the efficacy of our scheme.