期刊名称：International Journal of Grid and Distributed Computing
印刷版ISSN：2005-4262
出版年度：2011
卷号：4
期号：3
出版社：SERSC
摘要：Recent advancement in meta-heuristics grid scheduling studies have applied various techniques such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Ant Colony Optimization (ACO) to solve the grid scheduling problem. All of these technique requires an initial scheduler in order to initiate the scheduling process and the priority rule algorithms will typically be used. However, from the literature, none of these studies elaborate and justify their selection of a particular priority rule algorithms over another. Since the initial scheduler can significantly affect the entire scheduling process, it is important that the correct initial scheduler be selected. In this paper we quantitatively compared six initial scheduler algorithms to determine the best algorithm performance. We believe the performance comparison would enable users to utilize the best initial scheduler to fit their meta-heuristics grid scheduling studies
