Research Article
A tool based on traffic traces and stochastic monotonicity to analyze data centers and their energy consumption
@ARTICLE{10.4108/eai.14-12-2015.2262652, author={Marziyeh Bayati and Mohammed Dahmoune and Jean-Michel Fourneau and Nihal Pekergin and Dimitrios Vekris}, title={A tool based on traffic traces and stochastic monotonicity to analyze data centers and their energy consumption}, journal={EAI Endorsed Transactions on Energy Web}, volume={3}, number={10}, publisher={ACM}, journal_a={EW}, year={2016}, month={1}, keywords={queues, energy saving, discrete stochastic process, numerical analysis, data center}, doi={10.4108/eai.14-12-2015.2262652} }- Marziyeh Bayati
Mohammed Dahmoune
Jean-Michel Fourneau
Nihal Pekergin
Dimitrios Vekris
Year: 2016
A tool based on traffic traces and stochastic monotonicity to analyze data centers and their energy consumption
EW
EAI
DOI: 10.4108/eai.14-12-2015.2262652
Abstract
We present a tool to study the trade-off between energy consumption and performance evaluation. The tool uses real traffic traces to model arrivals, and it allows to consider general discrete arrival processes. Some servers are switched on (resp. off) if the monitored QoS becomes less (resp. more) than the {\it up} (resp. {\it down}) threshold. A set of threshold couples and the cost function taking into account both the performance measure and the energy consumption are provided by the user. The tool determines the best one for this cost function among the analyzed scenarios. Our method is numerically based but it takes into account some stochastic properties of the model to speed up the computation.
Copyright © 2015 J.-M. Fourneau et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
