Dynamic Partitioning Based Scheduling of Real-Time Tasks in Multicore Processors

Abstract

Existing real-time multicore schedulers use either global or partitioned scheduling technique to schedule real-time tasks. Partitioned scheduling is a static approach in which, a task is mapped to a per-processor ready queue prior to scheduling it and it cannot migrate. Partitioned scheduling makes ineffective use of the available processing power and incurs high overhead when real-time tasks are dynamic in nature. Global scheduling is a dynamic scheduling approach, where the processors share a single ready-queue to execute the highest priority tasks. Global scheduling allows task migration which results in high scheduling overhead. In this paper, we present a dynamic partitioning based scheduling of real-time tasks, called DP scheduling. In DP scheduling, jobs of tasks are assigned to cores when they are released and remain in the same core till they finish execution. The partitioning in DP scheduling is done based on the slack time and priority of jobs. If a job cannot be allocated to any core, then it is split, and executed on more than one core. DP scheduling technique attempts to retain good features of both global and partitioned scheduling without compromising on resource utilization, and at the same time, also tries to minimize the scheduling overhead. We have tested DP scheduling technique with EDF scheduling policy at each core, and we term this scheduling algorithm as DP-EDF. The performance of DP-EDF scheduling algorithm has been evaluated using simulation study and its implementation in LITMUS-RT on a 64-bit intel processor with eight logical cores. Both simulation and experimental results show that DP-EDF scheduling algorithm has better performance in terms of resource utilization, and comparable or better performance in terms of scheduling overhead in comparison to contemporary scheduling algorithms.