Abstract

As multi-core processors continue to scale, more and more multiple distributed applications with precedence-constrained tasks simultaneously and widely exist in multi-functional embedded systems. Scheduling multiple DAGs-based applications on heterogeneous multi-core processors faces conflicting high-performance and real-time requirements. This study presents a multiple DAGs-based applications scheduling optimization with respect to high performance and timing constraint. We first present the fairness and the whole priority scheduling algorithms from high performance and timing constraint perspectives, respectively. Thereafter, we mix these two algorithms to present the partial priority scheduling algorithm to meet the deadlines of more high-priority applications and reduce the overall makespan of the system. The partial priority scheduling is implemented by preferentially scheduling the partial tasks of high-priority applications, and then fairly scheduling their remaining tasks with all the tasks of low-priority applications. Both example and experimental evaluation demonstrate the significant optimization of the partial priority scheduling algorithm.

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