Estimation based load balancing algorithm for data-intensive heterogeneous grid environments

Abstract

Grid computing holds the great promise to effectively share geographically distributed heterogeneous resources to solve large-scale complex scientific problems. One of the distinct characteristics of the Grid system is resource heterogeneity. The effective use of the Grid requires an approach to manage the heterogeneity of the involved resources that can include computers, data, network, etc. In this paper, we proposed a de-centralized and adaptive load balancing algorithm for heterogeneous Grid environment. Our algorithm estimates different system parameters (such as job arrival rate, CPU processing rate, load at processor) and effectively performs load balancing by considering all necessary affecting criteria. Simulation results demonstrate that our algorithm outperforms conventional approaches in the event of heterogeneous environment and when communication overhead is significant. © 2006 Springer-Verlag.