A New Placement Optimization Approach in Hybrid Cloud Based on Genetic Algorithm

Abstract

With the evolution of cloud computing technology, companies develop their private cloud to deploy and run applications. A company can also combine public and private cloud services through the deployment of a hybrid cloud. Thus, if the company needs exceed the capacity of the private cloud, they can migrate to the public cloud. The deployment of new applications consists to choose the placement of some components in the private cloud and some others in the public cloud. Our objective is to minimize the costs caused by the applications deployment in the public cloud and communication costs between application of the private and public cloud. For this purpose, we have proposed a new service placement optimization approach based on genetic algorithm. The experimental results show that our approach outperforms the related works and seems to be promising in respect to optimal solution.