Mutative ABC Based Load Balancing in Cloud Environment

Abstract

Cloud computing provides its users with adjustable, on-demand virtual resources over the Internet with pay-per-use models. Due to the cost-benefits, a large number of individuals and organizations have moved their business on the cloud. The services offered by service providers range from software to infrastructure. To accommodate such a large number of users, it becomes vital for the service providers to use the resources efficiently. Thus, load balancing becomes one of the major concerns for service providers. Load balancing in the cloud environment is an NP-hard problem and where researchers have proposed different meta-heuristic solutions for it. To utilize resources efficiently and reducing makespan time of the submitted jobs, the paper proposes an algorithm based on the foraging behavior of honey bees, a mutative artificial bee colony algorithm. The proposed algorithm reduces makespan time as well as improves the fitness function. Through experiments implemented in CloudSim, the results verify that the proposed algorithm reduces makespan when compared with algorithms in literature.