Deployment and scheduling of virtual machines in cloud computing: An "AHP" approach

A kind of strategy for the deployment and scheduling of virtual machines is proposed based on multiple attributes analysis to solve the uneven loads problem among physical servers in the cloud computing. The strategy classifies virtual machines according to the characteristic of resources, and it is composed of two aspects. Resources of hot spots are analyzed to quantify their important degrees in the virtual machines deployment, and evaluate all the physical servers according to the virtual machine vector, then the best physical server is selected to deploy. The vectors of virtual machines which are running on the overload physical servers are obtained in the virtual machines scheduling, and the rest of physical servers are evaluated in the right order. This strategy not only realizes the optimal allocation of the resources and reduces the overall loss caused by dynamic load balancing. The experimental results show that, when 20 virtual machines in five physical machines are applied in the same order, the average number of dynamic migration of the proposed algorithm significantly reduces about 80% than that the random equalization strategy does, and the rates of physical server resources usage are more balanced.