Smart elastic scheduling algorithm for virtual machine migration in cloud computing

Cloud Computing has the facility to transform a large part of information technology into services in which computer resources are virtualized and made available as a utility service. From here comes the importance of scheduling virtual resources to get the maximum utilization of physical resources. This paper presents two cooperative algorithms: a Smart Elastic Scheduling Algorithm (SESA) and an Adaptive Worst Fit Decreasing Virtual Machine Placement (AWFDVP) algorithm. The proposed algorithms work to dynamically distribute the cloud system’s physical resources to obtain a load-balanced consolidated system with minimal used power, memory, and processing time. SESA arranges VMs in clusters based on their memory and CPU parameters’ value. Then it deals with the colocated VMs that share some of their memory pages and located on the same physical machine, as a group. Then the migration decision is made based on the evaluation for the entire system by AWFDVP. This process minimizes the number of migrations among the system, saves the consumed power, and prevents performance degradation for the VM while preserving the load-balance state of the entire system. SESA reduces the power consumption in the cloud system by 28.1%, the number of migrations by 57.77%, and performance degradation by 57.1%.