Abstract The goal of grid computing is to provide powerful computing for complex scientific problems by utilizing and sharing large scale resources available in the grid. Efficient scheduling algorithms are needed to allocate suitable resources for each submitted task. So scheduling is one of the most important issues for achieving high performance computing in grid. This paper addresses an approach for optimizing scheduling using a nature inspiredIntelligent Water Drops(IWD) algorithm. In the proposed approachIWDalgorithm is adopted to improve the performance of taskscheduling in grid environment.The performance of Ant Colony Optimization(ACO)algorithm for task scheduling is compared with the proposed IWD approach and it is proved that task scheduling usingIWD can efficiently and effectively allocate tasks to suitable resources in the grid.

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[15]Song X.,Li B.,andYangH., ImprovedAnt Colony Algorithmand itsApplicationsin TSP, in Proceedingsof the6thInternational Conferenceon Intelligent Systems Design and Applications,Jinan,pp.1145-1148. Soarnapandy Selvaranireceived herBE degree in Computer Science and Engineering from Bharathiar University in 1991, and MEdegree in Computer Science and Engineering from Manonmaniam Sundaranar University in 2004. Currently,She is working toward the PhD degree in Computer Science and Engineering under Anna University, Chennai, India. Her research work is in the area ofgrid and cloud computingwith techniques for resource management and task scheduling. GangadharanSadhasivamis working as a Professor in Department of Computer Science andEngineering in PSG College of Technology, Coimbatore, India. Her areas of interest includedistributed computing, distributed object technology, grid and cloud computing. She has published 20 research papers in referredJournalsand 32 papers in National and International Conferences. She has coordinated two AICTE-RPS projects in Distributed andGrid computing areas. She is also the coordinator for PSG-Yahoo research on Grid and Cloud computing.