Relative Performance of Scheduling Algorithms in Grid Environments

Abstract

Effective scheduling is critical for the performance of an application launched onto the Grid environment. Finding effective scheduling algorithms for this problem is a challenging research area. Many scheduling algorithms have been proposed, studied and compared on heterogeneous parallel computers but there are few studies comparing the performance of scheduling algorithms in Grid environments. The Grid is unique because of the drastic cost differences between inter-cluster and the intra-cluster data transfers. In this paper, we compare several scheduling algorithms that represent two classes of schedulers used for Grid computing. We analyze the results to explain how different resource environments and workflow application structures affect the performance of these algorithms. Based on our experiments, we introduce a new measurement called effective aggregated computing power (EACP) that could drastically improve the performance of some schedulers.