Criticality-Aware Partitioning for Multicore Mixed-Criticality Systems

Abstract

The scheduling for mixed-criticality (MC) systems, where multiple activities have different certification requirements and thus different criticality on a shared hardware platform, has recently become an important research focus. In this work, considering that multicore processors have emerged as the de-facto platform for modern embedded systems, we propose a novel and efficient criticality-aware task partitioning algorithm (CA-TPA) for a set of periodic MC tasks running on multicore systems. We employ the state-of-the art EDF-VD scheduler on each core. Our work is based on the observation that the utilizations of MC tasks at different criticality levels can have quite large variations, hence when a task is allocated, its utilization contribution on different processors may vary by large margins and this can significantly affect the schedulability of tasks. During partitioning, CA-TPA sorts the tasks according to their utilization contributions on individual processors. Several heuristics are investigated to balance the workload on processors with the objective of improving the schedulability of tasks under CA-TPA. The simulation results show that our proposed CA-TPA scheme is effective, giving much higher schedulability ratios when compared to the classical partitioning schemes.