An approach to virtual machine placement in cloud data centers

Abstract

A widespread use of the cloud computing paradigm has increased the necessity and significance of improving the management efficiency of cloud data centers. Special attention is paid to solving cloud resource management problems. Due to the intensive changes of virtual machine (VM) workloads and different conditions of resource utilization the VM placement and migration problems should be solved and optimized continuously in an online manner. To address such problems the authors present an approach to continuous new VM allocation and VM migration. The authors also evaluate a particular policy of the VM allocation in a data center using an adaptive genetic algorithm. The proposed Adaptive Software Defined approach to the cloud data centers management is implemented by using the policy selector, that allows to select different algorithms or policies for resources and virtual machines management in order to adapt to the impact of disturbing influences.