Resource prediction based on double exponential smoothing in cloud computing

With the development of cloud computing, customers are more and more concerned with cost on the resources which are not free in the cloud. Cloud resource providers can offer users two payment plans, i.e., reservation and on-demand plans for resource provision. In general, cost on resources gained by reservation plan is cheaper than on-demand plan. So the accuracy of resource prediction is of importance. In this paper, we present a resource prediction model based on double exponential smoothing, which considers not only the current state of resources but also the history records. Experiments performed on CloudSim cloud simulator show that the proposed method has a better performance on prediction accuracy.