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Experimental performance evaluation of job scheduling and processor allocation algorithms for grid computing on metacomputers

机译:元计算机上网格计算的作业调度和处理器分配算法的实验性能评估

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Summary form only given. Scheduling is a fundamental issue in achieving high performance on metacomputers and computational grids. The job scheduling problem for grid computing on metacomputers has been studied as a combinatorial optimization problem. In this paper, we compare the performance of various job scheduling and processor allocation algorithms for grid computing on metacomputers. We evaluate the performance of 128 combinations of two job scheduling algorithms, four initial job ordering strategies, four processor allocation algorithms, and four metacomputers by extensive simulation. It is found that the combination of LJF and MEET or LMF yields the best performance, and the choice of FCFS and LS depends on the range of job sizes.
机译:仅提供摘要表格。在元计算机和计算网格上实现高性能时,调度是一个基本问题。作为组合优化问题,已经研究了基于元计算机的网格计算的作业调度问题。在本文中,我们比较了用于元计算机上的网格计算的各种作业调度和处理器分配算法的性能。通过广泛的仿真,我们评估了两种作业调度算法,四种初始作业排序策略,四种处理器分配算法和四种元计算机的128种组合的性能。已经发现,LJF和MEET或LMF的组合可产生最佳性能,而FCFS和LS的选择取决于作业大小的范围。

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