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A Model for Energy-Awareness in Federated Cloud Computing Systems with Service-Level Agreements

Alessandro Ferreira Leite 1, 2, 3, * Alba Cristina de Melo 1 Christine Eisenbeis 2, 3 Claude Tadonki 4
* Corresponding author
2 GRAND-LARGE - Global parallel and distributed computing
CNRS - Centre National de la Recherche Scientifique : UMR8623, Inria Saclay - Ile de France, UP11 - Université Paris-Sud - Paris 11, LIFL - Laboratoire d'Informatique Fondamentale de Lille, LRI - Laboratoire de Recherche en Informatique
3 ParSys - LRI - Systèmes parallèles (LRI)
LRI - Laboratoire de Recherche en Informatique
Abstract : As data centers increase in size and computational capac- ity, numerous infrastructure issues become critical. Energy efficient is one of these issues because of the constantly increasing power consump- tion of CPUs, memory, and storage devices. A study shows that the whole energy consumed by data centers will be extremely high and it is like to overtake airlines in terms of carbon emissions. In that scenario, Cloud computing is gaining popularity since it can help companies to reduce costs and carbon footprint, usually distributing execution of ser- vices across distributed data centers. The research aims of this work are to propose and evaluate a Model for Federated Clouds that takes into account power consumption and Quality of Service (QoS) requirements. In our model, the energy reduction shall not result in negative impacts to the agreements between Cloud users and Cloud providers. Therefore, the model should ensure both energy-efficiency and QoS parameters, which sets up possibly conflicting objectives.
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Submitted on : Friday, October 10, 2014 - 1:17:22 PM
Last modification on : Thursday, June 17, 2021 - 3:46:15 AM
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  • HAL Id : hal-01073757, version 1


Alessandro Ferreira Leite, Alba Cristina de Melo, Christine Eisenbeis, Claude Tadonki. A Model for Energy-Awareness in Federated Cloud Computing Systems with Service-Level Agreements. PhD Symposium at the 2nd European Conference on Service-Oriented and Cloud Computing (ESSOC 2013), Sep 2013, Halle, Germany. pp.17-22. ⟨hal-01073757⟩



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