Research Article
On the Minimization of the Energy Consumption in Federated Data Centers
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@INPROCEEDINGS{10.1007/978-3-319-47063-4_40, author={Alexis Aravanis and Panagiotis Karkazis and Artemis Voulkidis and Theodore Zahariadis}, title={On the Minimization of the Energy Consumption in Federated Data Centers}, proceedings={Internet of Things. IoT Infrastructures. Second International Summit, IoT 360° 2015, Rome, Italy, October 27-29, 2015. Revised Selected Papers, Part I}, proceedings_a={IOT360}, year={2017}, month={1}, keywords={Federated data centers Energy minimization Optimization Support vector regression Bin-packing problem}, doi={10.1007/978-3-319-47063-4_40} }- Alexis Aravanis
Panagiotis Karkazis
Artemis Voulkidis
Theodore Zahariadis
Year: 2017
On the Minimization of the Energy Consumption in Federated Data Centers
IOT360
Springer
DOI: 10.1007/978-3-319-47063-4_40
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.
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