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Top1. Introduction
Grid technology plays a major role in managing large-scale problems, by integrating distributed resources to provide users with a supercomputer with a capacity for data sharing and computation (Tang & Zhang, 2005; Ian & Carl, 1997; Ian & Carl, 1999). Participating sites may be physically distributed, heterogeneous, and governed by different administrative domains. Numerous related studies and projects have proposed solutions for large-scale scientific problems, such as earthquake simulation, atmosphere and ocean simulation, high energy and nuclear physics, bioinformatics, and medical image processing. A number of other proposed grid projects are Globus, Condor, LEGION, Grid PP, EGEE, P-Grid, DutchGrid, ESnet, and Grid Bus (http://nws.cs.ucsb.edu/ewiki/) tools to monitor resource status and network-related information (Yang, Shih, & Chen, 2006), respectively. Understanding the influence of each parameter is not only crucial for an application to achieve a good performance, but also helps develop effective schedule heuristics and design high-quality grids.