Cloud computing is a collection of IT services that have been provided to a person on the network on a leased basis i.e pay-per –use in nature, same as we pay mobile and electricity bills as per our use. For maintaining various data and applications, this technology uses the internet and central remote servers. In cloud computing, Load balancing is the main challenge in which distribution of the dynamic workload across multiple nodes is required so that no single node is overloaded. It helps in proper utilization of resources and therefore enhancing the performance of the system. To assign the client’s requests to various Cloud nodes, many algorithms were designed. These approaches aim to improve the overall performance of the cloud and provide the user more satisfying services. This paper will analysis the performance of proposed algorithm and compares the simulation outcomes in terms of throughput, migration time and overhead associated , with the existing approaches i.e. Ant Colony Optimization(ACO), Equally Spread Current Execution(ESCE) and Round Robin(RR).
Cloud Computing, Load balancing, Ant Colony Optimization (ACO), Bee Colony Optimization (BCO), Response Time, DC Processing Time, Total Cost.