A Novel Virtual Machine Placement Algorithm Using an Energy-Aware Meta-Heuristics Approach

Abstract

The paramount concern associated with the Virtual Machine Placement (VMP) relates to the mapping of Virtual Machine (VMs) to the Physical Machine’s (PMs). This mapping goal is to utilize the PMs to their maximum potential. In order to attain the full proficiency from the mapping process it is required not to impede already active instances of Virtual machine. Incompetence in mapping process substantially results in resource wastage and increase in energy consumption and consequentially increasing the overall functional cost at the data canter. A meta-heuristic based algorithm for virtual machine placement is recommended to redress the aforementioned issues. A cr-Cuckoo algorithm is proposed which integrates the concept of correlation and Cuckoo Search. The work given here is contrasted with varied familiar algorithm of the domain. The acquired results exhibit a distinguished reduction in the consumption of power and count of migrations by VMs and violation in SLA.