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Dynamic scheduling of tasks for multi-core real-time systems based on optimum energy and throughput

机译:基于最佳能量和吞吐量的多核实时系统的任务动态调度

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One of the critical design issues in real-time systems is energy consumption, especially in battery-operated systems. Generally higher processor voltage generates higher throughput of the system while decreasing voltage can perform energy minimisation. Instead of lowering processor voltage, this paper presents an optimum energy efficient real-time scheduling to adjust voltage dynamically to achieve optimum throughput. Earlier research works have considered random new tasks, which have been divided into jobs using pfair scheduling to fit into idle times of different cores of the system. In this paper we consider each job has different power levels and execution time at each power level can be found using normalised execution time. Based on the power levels and their corresponding execution time, we find different combinations of energy signature of the system and derive the optimum state of the system using a weighted average of the energy of the system and corresponding throughput. We verify the proposed model using generated task sets and the results show that the model performs excellently in all the cases and significantly reduced the total energy consumption of the system with respect to some popular and relatively new scheduling schemes.
机译:实时系统中的关键设计问题之一是能耗,尤其是在电池供电的系统中。通常,较高的处理器电压会产生较高的系统吞吐量,而降低电压可以使能量最小化。代替降低处理器电压,本文提出了一种最佳的节能实时调度,以动态调整电压以实现最佳吞吐量。早期的研究工作考虑了随机的新任务,这些任务已使用公平调度(ffair schedule)划分为工作,以适应系统不同核心的空闲时间。在本文中,我们认为每个作业具有不同的功率级别,并且可以使用归一化的执行时间找到每个功率级别的执行时间。基于功率水平及其相应的执行时间,我们找到系统能量特征的不同组合,并使用系统能量和相应吞吐量的加权平均值得出系统的最佳状态。我们使用生成的任务集验证了提出的模型,结果表明该模型在所有情况下均具有出色的性能,并且相对于一些流行且相对较新的调度方案而言,显着降低了系统的总能耗。

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