4.5 Article

Energy-Aware Nonpreemptive Scheduling of Mixed-Criticality Real-Time Task Systems

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCAD.2021.3120326

关键词

Task analysis; Job shop scheduling; Dynamic scheduling; Processor scheduling; Heuristic algorithms; Vehicle dynamics; Minimization; Dynamic priority; energy management; mixed-criticality (MC); nonpreemptive; real-time scheduling

资金

  1. Youth Innovation Fund Projects of Xiamen City [3502Z20206012]

向作者/读者索取更多资源

Energy-aware real-time scheduling for mixed-criticality systems has gained attention. This study focuses on nonpreemptive dynamic priority scheduling, proposing an algorithm that consumes 25.72% less energy compared to existing ones. Extensive simulations validate the algorithm's performance.
Energy-aware real-time scheduling for mixed-criticality (MC) systems with different criticality levels has drawn many researchers' attentions. However, most of the studies focus on the preemptive MC task model and few studies consider the nonpreemptive MC task model, in which all jobs cannot be preempted until completion. In this article, we address the energy minimization problem for MC systems with nonpreemptive dynamic priority scheduling. First, we develop schedulability test of nonpreemptive earliest deadline first (NP-EDF) in single processor MC systems. Second, we extend the results to nonpreemptive earliest deadline first with virtual deadline (NP-EDFVD), which is the first attempt for nonpreemptive dynamic priority scheduling in single processor MC systems. Third, the energy-aware nonpreemptive scheduling algorithm (EANPS) based on NP-EDFVD is proposed to solve the energy minimization problem for MC systems with nonpreemptive dynamic priority scheduling. Finally, an industrial use-case and extensive simulations are used to validate the performance of the proposed algorithm, and the experimental results show that the EANPS algorithm consumes average 25.72% less energy than that of NP-EDFVD.

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