Implementation and performance analysis of various VM placement strategies in CloudSim

Infrastructure as a Service (IaaS) has become one of the most dominant features that cloud computing offers nowadays. IaaS enables datacenter's hardware to get virtualized which allows Cloud providers to create multiple Virtual Machine (VM) instances on a single physical machine, thus improving resource utilization and increasing the Return on Investment (ROI). VM consolidation includes issues like choosing appropriate algorithm for selection of VMs for migration and placement of VMs to suitable hosts. VMs need to be migrated from overutilized host to guarantee that demand for computer resources and performance requirements are accomplished. Besides, they need to be migrated from underutilized host to deactivate that host for saving power consumption. In order to solve the problem of energy and performance, efficient dynamic VM consolidation approach is introduced in literature. In this work, we have proposed multiple redesigned VM placement algorithms and introduced a technique by clustering VMs to migrate by taking account both CPU utilization and allocated RAM. We implement and study the performance of our algorithms on a cloud computing simulation toolkit known as CloudSim using PlanetLab workload data. Simulation results demonstrate that our proposed techniques outperform the default VM Placement algorithm designed in CloudSim.