An Intelligent Water Drop Algorithm for Optimizing Task Scheduling in Grid Environment

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 inspired Intelligent Water Drops (IWD) algorithm. In the proposed approach IWD algorithm is adopted to improve the performance of task scheduling 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 using IWD can efficiently and effectively allocate tasks to suitable resources in the grid.