Improved Job-Grouping Based PSO Algorithm for Task Scheduling in Grid Computing
The goal of grid computing is to provide powerful computing abilities for complicated tasks by using all available and free computational resources. A suitable and efficient scheduling algorithm is needed to schedule user jobs to heterogeneous resources distributed in the grid. So scheduling is an important issue in a grid computing environment. In this paper an improved heuristic approach based on Particle Swarm Optimization (PSO) algorithm is presented to solve task scheduling problem in grid. In this proposed scheduling approach tasks are grouped and allocated in an Un-uniform manner. The percentage of the processing capability of a resource on the total processing capability of all the resources is calculated.