Adaptive and Dynamic Load Balancing in Grid Using Ant Colony Optimization

Abstract

Grid Computing involves coupled and coordinated use of geographically distributed resources for purposes such as large-scale computation and distributed data analysis. With the Grid becoming a viable high-performance alternative to the traditional supercomputing environment, a suitable and efficient load balancing algorithm is needed to equally spread the load on each computing node in the grid. This research work presents Ant based algorithm to solve the load balancing problem in computational grid. In proposed algorithm, the pheromone is associated with resources, rather than path. The increase or decrease of pheromone represent load and depends on task status at resources. The main objective of proposed algorithm is to map tasks to resources in a way that balance out the load resulting in improved utilization of resources.