A stochastic approach for optimizing green ...
Type de document :
Communication dans un congrès avec actes
Titre :
A stochastic approach for optimizing green energy consumption in distributed clouds
Auteur(s) :
Camus, Benjamin [Auteur]
Design and Implementation of Autonomous Distributed Systems [MYRIADS]
Dufossé, Fanny [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Orgerie, Anne-Cécile [Auteur]
Centre National de la Recherche Scientifique [CNRS]
Design and Implementation of Autonomous Distributed Systems [MYRIADS]
Design and Implementation of Autonomous Distributed Systems [MYRIADS]
Dufossé, Fanny [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Orgerie, Anne-Cécile [Auteur]
Centre National de la Recherche Scientifique [CNRS]
Design and Implementation of Autonomous Distributed Systems [MYRIADS]
Titre de la manifestation scientifique :
SMARTGREENS 2017 - International Conference on Smart Cities and Green ICT Systems
Ville :
Porto
Pays :
Portugal
Date de début de la manifestation scientifique :
2017-04-22
Mot(s)-clé(s) en anglais :
on/off techniques
Data centers
distributed clouds
energy efficiency
renewable energy
scheduling
Data centers
distributed clouds
energy efficiency
renewable energy
scheduling
Discipline(s) HAL :
Informatique [cs]/Réseaux et télécommunications [cs.NI]
Résumé en anglais : [en]
The energy drawn by Cloud data centers is reaching worrying levels, thus inciting providers to install on-site green energy producers, such as photovoltaic panels. Considering distributed Clouds, workload managers need to ...
Lire la suite >The energy drawn by Cloud data centers is reaching worrying levels, thus inciting providers to install on-site green energy producers, such as photovoltaic panels. Considering distributed Clouds, workload managers need to geographically allocate virtual machines according to the green production in order not to waste energy. In this paper, we propose SAGITTA: a Stochastic Approach for Green consumption In disTributed daTA centers. We show that compared to the optimal solution, SAGITTA consumes 4% more brown energy, and wastes only 3.14% of the available green energy, while a traditional round-robin solution consumes 14.4% more energy overall than optimum, and wastes 28.83% of the available green energy.Lire moins >
Lire la suite >The energy drawn by Cloud data centers is reaching worrying levels, thus inciting providers to install on-site green energy producers, such as photovoltaic panels. Considering distributed Clouds, workload managers need to geographically allocate virtual machines according to the green production in order not to waste energy. In this paper, we propose SAGITTA: a Stochastic Approach for Green consumption In disTributed daTA centers. We show that compared to the optimal solution, SAGITTA consumes 4% more brown energy, and wastes only 3.14% of the available green energy, while a traditional round-robin solution consumes 14.4% more energy overall than optimum, and wastes 28.83% of the available green energy.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
Source :
Fichiers
- https://hal.inria.fr/hal-01475431/document
- Accès libre
- Accéder au document
- https://hal.inria.fr/hal-01475431/document
- Accès libre
- Accéder au document
- https://hal.inria.fr/hal-01475431/document
- Accès libre
- Accéder au document
- document
- Accès libre
- Accéder au document
- paper-extended.pdf
- Accès libre
- Accéder au document