Presenting a Method to Reduce Energy Consumption in Cloud Data Centers using Genetic Optimization Algorithm

Cloud computing environment is a payment method for utilization which provides network access based on demand to a large amount of common computing sources like networks, servers, application storage and services. These sources can be provided quickly and transmitted with minimum management effort and interaction with service provider. There are many problems for using cloud computing environment where one of the most important ones is virtual machine placement in datacenters. Placement in datacenters should be done accurately due to various conditions of VMs in cloud computing environment like VM Memory Usage and VM CPU Performance. This paper presents a genetic optimization method for VM placement in cloud data centers. Using the genetic optimization method for VM placement in cloud data centers, VM can be places based on its cloud computing capability. The proposed method is analyzed using Matlab based on designed datasets. Analysis results indicate error reduction in VM placement which results in more accurate VM placement and reduction in energy consumption in cloud data centers. Energy consumption in cloud data centers is extracted using the proposed VM placement method and compared with PSO and random placement. Final results indicate reduction of mentioned metrics in the proposed method due to higher accuracy of VM placement in cloud data centers.

Keywords:

cloud computing , placement , virtual machine , genetic optimization model , energy consumption , data centers