Execution analysis of load balancing particle swarm optimization algorithm in cloud data center

摘要

Cloud Computing is a latest research topic for the researchers. Due to the fast growth of Internet cloud computing have become a source of online computing for big, medium and small IT companies. The users of the cloud-computing can access the services anywhere from the world. Therefore it is becoming a big challenge for cloud data centers to handle the requests efficiently, which comes from these countless users, and services those users in an efficient manner. By load balancing in this environment it means to equally distribute the workload across all the nodes. Load balancing is a way of achieving the optimum utilization of resources and better user satisfaction. Therefore, designing an efficient load balancing algorithm is mandatory for virtual machine or server selection. This paper focuses on the reduction of Dirty memory during Live Migration of Virtual machine. The data center environment considered is Heterogeneous Environment where the physical hosts have different configurations. Our proposed algorithm is implemented on cloudsim simulator A Particle Swarm Optimization (PSO) package is integrated in our simulator so as to achieve an effective result where PSO will randomly find the suitable Physical host in heterogeneous environment so as to transfer the load. We compare our proposed algorithm with the Shortest Job First in homogeneous environment of virtual machines. The experiment carried out in the paper shows that the proposed algorithm performs better than the existing algorithms.