On the minimization of the energy consumption in federated data centers

Abstract

As cloud services are becoming increasingly popular, the number of operating data centers is accordingly increasing, together with the need of implementing federated data centers and clouds. In this context, we consider a framework for achieving energy efficiency in federated clouds, by means of continuous monitoring and SLA renegotiation, coupled with the operation of prediction and multi-layered optimization components. In this paper, relevant prediction and optimization components, based on Support Vector Regression and Bin-Packing solving heuristics, operating at local data center level are examined and the experimental results of their deployment in a real-life testbed are presented and discussed.