AN IMPROVED VIRTUAL MACHINE PLACEMENT IN CLOUD DATA CENTER USING PARTICLE SWARM OPTIMIZATION ALGORITHM

IaaS is a service model where the cloud providers offer different resources such as processor cores, memory, and storage on demand by its customers. The cloud service provider will host a cloud data center with multiple Virtual machines running on various physical Machines using virtualization technology. The virtual machine placement is always an NP-hard problem. Proper placing of Virtual Machines (VM) reduces energy consumptions and increases resource usage efficiency. There are many resource optimization constraints on cloud data centers in solving the problem of Virtual Machines (VM) placement. In this paper, we propose a New Improved Particle Swarm Optimization (NIM-PSO) which mainly focuses on reducing power usage and increasing the load-bearing capacity. The reduced energy consumption is achieved by reducing the number of active Physical Machines (PM) and the resource usage efficiency is achieved by properly packing the Virtual Machines in the available active Physical Machines. Simulations are done using cloudsim for the user customized Virtual Machines and the standard Physical Machines, the results illustrate that the proposed method is better than the existing approaches.