Optimizing Cloud providers revenues via energy efficient server allocation

Cloud providers, like Amazon, offer their data centers’ computational and storage capacities for lease to paying customers. High electricity consumption, not only reflects on the data center's carbon footprint but also increases the costs of running the data center itself. We examine the problem of managing a server farm in a way that attempts to maximize the net revenue earned by a Cloud provider renting servers to customers according to a typical Platform-as-a-Service model. As a solution allocation policies which are based on the dynamic powering servers on and off are introduced and evaluated. The policies aim at satisfying the conflicting goals of maximizing the users’ experience while minimizing the amount of consumed electricity. Special emphasis is given to cases where user demand is time-varying and cannot be predicted with absolute accuracy. In order to deal with that, allocation policies resilient to errors in the forecasting, as well as a method for finding the parameters leading to the highest revenues are introduced. The results of several experiments are described, showing that the proposed scheme performs well under different traffic conditions.