Resource-Aware Partitioned Scheduling for Heterogeneous Multicore Real-Time Systems

Heterogeneous multicore processors have become popular computing engines for modern embedded real-time systems recently. However, there is rather limited research on the scheduling of real-time tasks running on heterogeneous multicore systems with shared resources. Note that, different partitionings of tasks upon heterogeneous cores can affect the synchronization overheads of tasks (and thus the system schedulability). Focusing on the partitioned-EDF scheduling and resource access protocol MSRP (Multiprocessor Stack Resource Policy), this paper proposes an effective synchronization aware task partitioning algorithm for heterogeneous multicores (SA-TPA-HM). Several resource-oriented heuristics are exploited to tighten the bound on the synchronization costs of tasks through dynamic task prioritization and to find an appropriate core for each task that can minimize the system utilization increment. The simulation results show that our proposed SA-TPA-HM scheme can achieve higher acceptance ratio (e.g., 60% more), when compared to the existing schemes designed for homogeneous multicores.