Workload-Aware Harmonic Partitioned Scheduling of Periodic Real-Time Tasks with Constrained Deadlines

Abstract

Multiprocessor platforms have been widely applied in safety-critical domains to accommodate the increasing computation requirement of modern real-time applications. In this paper, we present a workload-aware harmonic partitioned multiprocessor scheduling scheme for periodic real-time tasks with constrained deadlines under the fixed-priority preemptive scheduling policy. In particular, two grouping metrics effectively integrating both harmonicity and workload characteristic are designed to guide our task partition. With those metrics, our scheme can greatly improve system utilization by taking advantage of the combination of harmonic relationship exploration and workload awareness. Experiments show that our proposed scheme significantly outperforms existing approaches in terms of schedulability.