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An Efficient Genetic Algorithm for Task Scheduling in Heterogeneous Distributed Computing Systems

机译:异构分布式计算系统中的任务调度有效遗传算法

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Task scheduling plays an important role in the operation of distributed computing systems. Because of its importance, several task scheduling algorithms are proposed in the literature, mainly for homogeneous processors. Few scheduling algorithms are proposed for Heterogeneous Distributed Computing Systems (HeDCSs). In this paper, we present a new approach which uses a customized genetic algorithm to produce high-quality tasks schedules for HeDCSs. The performance of the new algorithm is compared to that of two leading scheduling algorithms for HeDCSs. The comparison, which is based on both randomly generated task graphs and task graphs of certain real-world numerical applications, exhibits the supremacy of the new algorithm over the older ones, in terms of schedule length, speedup and efficiency.
机译:任务调度在分布式计算系统的操作中起着重要作用。由于其重要性,在文献中提出了几项任务调度算法,主要用于均匀处理器。提出了用于异构分布式计算系统(HEDCS)的调度算法。在本文中,我们提出了一种新的方法,它使用定制的遗传算法为HEDCS生产高质量任务计划。将新算法的性能与HEDCSS的两个前导调度算法进行了比较。在基于某种随机生成的任务图和某些实际数值应用的任务图的比较,就调度长度,加速和效率而言,展示了旧算法的新算法的至上。

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