A machine learning model for improving virtual machine migration in cloud computing

Cloud Computing is a paradigm allowing access to physical and application resources online via the Internet. These are virtualized using virtualization software make them available users as service. Virtual machines (VMs) migration technique provided by technology impacts performance of cloud. It significant concern in this environment. When allocating resources, distribution VMs unbalanced, their movement from one server another can increase energy consumption network overhead, necessitating an improvement VM migrations. This paper addresses issue applying machine learning model reduce number consumption. The proposed algorithm (named VMLM) based on improving VM’s process selection. has been benchmarked with JVCMMD EVSP solutions. simulation results demonstrate efficiency our proposal, which includes two phases preparing stage stage.