year period \[1\]. At the same time, a completely idle server consumes its maximum power at its peak.

A Cloud computing environment is built using one or more data centers, and these data centers have many computing resources which we call servers or hosts. Multiple virtual machines could be allocated for every host through virtual technology, and each virtual machine acts as an individual physical machine with their own OS and system resources. As a concept, cloud computing users are able to use computing resources as payment, because customer dissatisfaction should be avoided through SLA. When CPU utilization exceeds its limit due to an oversubscription agreement, SLA terms could be violated. However, a VM migration before a possible oversubscription is a viable solution to avoid SLA violation \[35\]. On the other hand, energy saving is possible through VM consolidation by defining under-loaded hosts. In both situations, it is necessary to choose VMs for migration and also a new placement is needed for the VMs to be migrated.

In this paper, we have described VM placement and selection models. We have proposed a new VM selection method. The proposed method works by analysing RAM and network bandwidth usages. It reduces energy 