Load Balancing Using Enhanced Ant Algorithm in Grid Computing

Abstract

Load balancing is one of the critical issues that must be considered in managing a grid computing environment. It is complicated due to the distributed and heterogeneous nature of the resources. An enhanced ant algorithm for load balancing in grid computing is proposed in this paper. The proposed algorithm will determine the best resource to be allocated to the jobs based on job characteristics and resource capacity, and at the same time to balance the entire resources. The proposed algorithm focuses on local pheromone trail update and trail limit. A grid resource table is used in this proposed technique to store all information about jobs, resources and pheromone value. The credibility of the proposed algorithm is compared with other approach and results produced showed that the algorithm can balance the load of the resources.