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A genetic algorithm-based tasks scheduling in multicore processors considering energy consumption

机译:考虑能量消耗的多核处理器中的基于基于遗传算法的任务

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摘要

Energy consumption has been always an important issue in multicore processors which are getting more and more popular in embedded systems. In this paper, we propose an energy-aware task scheduling approach taking advantages of heuristic algorithms based on genetic algorithm. The proposed approach includes both static and dynamic scheduling schemes. The task scheduling is modelled as a genetic algorithm problem which is mainly used when the tasks are ready before run-time; i.e., static task scheduling. The tasks which arrive after beginning task execution are dynamically scheduled using a proposed heuristic algorithm in combination with the genetic algorithm. The experimental results show that the proposed algorithm achieves more energy efficiency in both static and dynamic task scheduling for multicore processors as compared with similar energy-aware scheduling methods.
机译:能源消耗始终是多核处理器中的一个重要问题,在嵌入式系统中越来越受欢迎。 本文提出了一种基于遗传算法的启发式算法的能量感知任务调度方法。 该方法包括静态和动态调度方案。 任务调度被建模为一个遗传算法问题,主要用于在运行时间之前完成任务; 即,静态任务调度。 在开始任务执行之后到达的任务是使用所提出的启发式算法动态调度,与遗传算法组合。 实验结果表明,与类似的能量感知调度方法相比,该算法在多核处理器的静态和动态任务调度中实现了更多能效。

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