Load Balancing in Cloud Computing using Mutative ABC
Cloud computing provides its user dynamically scalable virtual resources via Internet on a pay per use model. A large number of users and organization have move on to the cloud for accessing services provided by different cloud service providers. To manage such a large number of requests and users, cloud service provider needs to manage their data centers effectively. Thus, load balancing is required by the providers to ensure that the utilization of resources is effective. Cloud load balancing is an NP-hard optimization problem and various researchers have proposed different meta-heuristic algorithm in literature. Aiming to minimize makespan time and better utilization of resources, the paper provides a mutative bacterial foraging algorithm. The algorithm not only minimize the makespan time but also improves the fitness function. The proposed algorithm has been compared with different algorithm present in literature and the result indicates that the algorithm performs has lower makespan time in a heterogeneous cloud environment with dynamic task being considered.