Grid load balancing using ant colony optimization

An enhanced ant colony optimization technique for jobs and resources scheduling in grid computing is proposed in this paper. The proposed technique combines the techniques from Ant Colony System and Max – Min Ant System and focused on local pheromone trail update and trail limit. The agent concept is also integrated in this proposed technique for the purpose of updating the grid resource table. This facilitates in scheduling jobs to available resources efficiently which will enable jobs to be processed in minimum time and also balance all the resource in grid system