A stochastic approach for optimizing green ...
Document type :
Communication dans un congrès avec actes
Title :
A stochastic approach for optimizing green energy consumption in distributed clouds
Author(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]
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]
Design and Implementation of Autonomous Distributed Systems [MYRIADS]
Conference title :
SMARTGREENS 2017 - International Conference on Smart Cities and Green ICT Systems
City :
Porto
Country :
Portugal
Start date of the conference :
2017-04-22
English keyword(s) :
on/off techniques
Data centers
distributed clouds
energy efficiency
renewable energy
scheduling
Data centers
distributed clouds
energy efficiency
renewable energy
scheduling
HAL domain(s) :
Informatique [cs]/Réseaux et télécommunications [cs.NI]
English abstract : [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 ...
Show more >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.Show less >
Show more >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.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
Source :
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