Prediction Model for Physical Machine Selection for Virtual Machine Placement

Virtual Machine migration and placement is one of the important tasks in cloud data center to balance the load and energy consumption of physical machine (host). Most of the present VM migration and VM placement methods work on present scenario of PMs load and VM's requirements. In live scenario of cloud data centers various VM are to be migrated from one server to other. At the same time both VMs and PMs are consolidated to keep it balanced in terms of resource and energy consumption optimization. The selection of VMs to be migrated and PMs to accommodate the migrating VMs are selected live as per requirements. It would be useful and beneficial if suitable servers can be predicted in advance. The selection of suitable PMs is based on various factors. In this paper a Bayesian Network bases PM Selection Prediction Model (BNPM-SPM) is proposed. The proposed model will predict the suitable PM in advance which will make the VM migration and VM placement process efficient and beneficial in terms of resource optimization and energy consumption optimization on cloud data center.