Enhanced Bee Colony Algorithm for Efficient Load Balancing and Scheduling in Cloud

Abstract

Cloud computing is a promising paradigm which provides resources to customers on their demand with minimum cost. Cost effective optimal scheduling and load balancing are major challenges in adopting cloud computation. Good load balancing and scheduling methods avoids under loaded and heavy loaded conditions in datacenters. When some VMs are overloaded with several number of tasks, these tasks are migrated to the under loaded VMs of the same datacenter in order to maintain Quality of Service (QoS). Frequent VM migrations also affect the performance of the cloud eco system. Nature inspired algorithms are efficient in solving this kind of dynamic problems. This paper proposes a modification in the bee colony algorithm for efficient and effective load balancing in cloud environment. The honey bees foraging behaviour is used to balance load across virtual machines. The tasks removed from over loaded VMs are treated as honeybees and under loaded VMs are the food sources. The method also tries to minimize makespan as well as number of VM migrations. The algorithm also tries to reduce the imbalance in the cloud eco system. The experimental result shows that there is significant improvement in the QoS delivered to the customers.