An AntNet-Based Load Balancing Algorithm for Grid Computing Environments

As a result of the rapid growth of computational needs, grid computing is gaining more and more attention. It becomes a viable high-performance alternative to the traditional supercomputing environments. However, grid performance can still be improved by effectively and efficiently utilizing the available grid resources using a good load balancing algorithm. Ant colony optimization is one of the most recent techniques for approximate optimization. It simulates the behavior of real ants in finding the optimal path food resources. In this paper, we propose an Ant based load balancing algorithm for the grid computing environment. The pheromone level in the proposed algorithm is associated with resources rather than paths. The pheromone level for a resource depends on communication bandwidth, workload status, and processing capacity. The performance of the proposed algorithm is evaluated using simulation. Experimental results show that the proposed algorithm can perform very well on the grid computing environments.