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

Abstract

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.