Tremendous usage of internet has made huge data on the network, without compromising on the performance of network the end-users must obtain best service. As cloud provides different services on leasing basis many companies are migrating from their own Infrastructure to cloud,This migration should not compromise on performance of the cloud, The performance of the cloud can be improved by having excellent load balancing strategy such that the end user is satisfied. The paper reveals the method by which a cloud can be partitioned and a study of different algorithm with comparative study to balance the dynamic load. The comparative study between Ant Colony and Honey Bee algorithm gives the result which algorithm is optimal in normal load condition also the simplest round robin algorithm is applied when the partition are in Idle state

ABSTRACT

The Corporate Environment is diverting to Cloud Computing due to its property of scalability, versatility, dependability obtainability, hence it offers several different types of work in this area, much work in this technology is done still there is need of enhancement to escalate the technique, the major issue in cloud is balancing of load as the volume of information is vast also the number of resources and server used are numerous. There are numerous algorithms under Swarm intelligence (SI) which is Co-operative activity of noncentralized, self-organized natural or artificial system. The paper focuses to find which algorithm among the widely used Ant colony and Honey bee behavior is best for balancing of load under normal balancer condition, In Idle balancer condition round-robin is being applied which appears suitable for the condition. In addition for huge and complex corporate environs, the paper focuses on strategy of divisions based on region to simplify the load balancing. The cloud has a central controller (CC) that chooses the suitable partitions for arriving jobs.

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