An Energy-aware Multi-start Local Search ...
Type de document :
Communication dans un congrès avec actes
Titre :
An Energy-aware Multi-start Local Search Heuristic for Scheduling VMs on the OpenNebula Cloud Distribution
Auteur(s) :
Kessaci, Yacine [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Nouredine, Melab [Auteur]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Talbi, El-Ghazali [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Nouredine, Melab [Auteur]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Talbi, El-Ghazali [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Titre de la manifestation scientifique :
HPCS 2012
Ville :
Madrid
Pays :
Espagne
Date de début de la manifestation scientifique :
2012-07-02
Date de publication :
2012-07-02
Mot(s)-clé(s) en anglais :
local search
energy-aware scheduling
cloud distribution
cloud computing
resource allocation
OpenNebula
multi-start
local search.
energy-aware scheduling
cloud distribution
cloud computing
resource allocation
OpenNebula
multi-start
local search.
Discipline(s) HAL :
Informatique [cs]/Calcul parallèle, distribué et partagé [cs.DC]
Résumé en anglais : [en]
Reducing energy consumption is an increasingly important issue in cloud computing, more specifically when dealing with a cloud distribution dispatched over a huge number of machines. Minimizing energy consumption can ...
Lire la suite >Reducing energy consumption is an increasingly important issue in cloud computing, more specifically when dealing with a cloud distribution dispatched over a huge number of machines. Minimizing energy consumption can significantly reduce the amount of energy bills, and the greenhouse gas emissions. Therefore, many researches are carried out to develop new methods in order to consume less energy. In this paper, we present an Energy-aware Multi-start Local Search algorithm for an OpenNebula based Cloud (EMLS-ONC) that optimizes the energy consumption of an OpenNebula managed geographically distributed cloud computing infrastructure. The results of our EMLS-ONC scheduler are compared to the results obtained by the default scheduler of OpenNebula. The two approaches have been experimented using different (VMs) arrival scenarios and different hardware infrastructures. The results show that EMLS-ONC outperforms the previous OpenNebula's scheduler by a significant margin in terms of energy consumption. In addition, EMLS-ONC is also proved to schedule more applications.Lire moins >
Lire la suite >Reducing energy consumption is an increasingly important issue in cloud computing, more specifically when dealing with a cloud distribution dispatched over a huge number of machines. Minimizing energy consumption can significantly reduce the amount of energy bills, and the greenhouse gas emissions. Therefore, many researches are carried out to develop new methods in order to consume less energy. In this paper, we present an Energy-aware Multi-start Local Search algorithm for an OpenNebula based Cloud (EMLS-ONC) that optimizes the energy consumption of an OpenNebula managed geographically distributed cloud computing infrastructure. The results of our EMLS-ONC scheduler are compared to the results obtained by the default scheduler of OpenNebula. The two approaches have been experimented using different (VMs) arrival scenarios and different hardware infrastructures. The results show that EMLS-ONC outperforms the previous OpenNebula's scheduler by a significant margin in terms of energy consumption. In addition, EMLS-ONC is also proved to schedule more applications.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
Source :
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