List scheduling heuristics for virtual ...
Type de document :
Communication dans un congrès avec actes
Titre :
List scheduling heuristics for virtual machine mapping in cloud systems
Auteur(s) :
Nesmachnow, Sergio [Auteur]
UDELAR, Facultad de Ingenieria [Montevideo] [UDELAR]
Iturriaga, Santiago [Auteur]
Universidad de la República [Montevideo] [UDELAR]
Dorronsoro, Bernabé [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Talbi, El-Ghazali [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Bouvry, Pascal [Auteur]
Université du Luxembourg = University of Luxembourg = Universität Luxemburg [uni.lu]
UDELAR, Facultad de Ingenieria [Montevideo] [UDELAR]
Iturriaga, Santiago [Auteur]
Universidad de la República [Montevideo] [UDELAR]
Dorronsoro, Bernabé [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Talbi, El-Ghazali [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Bouvry, Pascal [Auteur]
Université du Luxembourg = University of Luxembourg = Universität Luxemburg [uni.lu]
Titre de la manifestation scientifique :
HPCLatAm 2013 - VI Latin American Symposium on High Performance Computing
Ville :
Mendoza
Pays :
Argentine
Date de début de la manifestation scientifique :
2013-07-29
Date de publication :
2013-07-29
Discipline(s) HAL :
Informatique [cs]/Intelligence artificielle [cs.AI]
Résumé en anglais : [en]
This article introduces the formulation of the Virtual MachinePlanning Problem in cloud computing systems. It deals with the effi-cient allocation of a set of virtual machine requests from customers intothe available ...
Lire la suite >This article introduces the formulation of the Virtual MachinePlanning Problem in cloud computing systems. It deals with the effi-cient allocation of a set of virtual machine requests from customers intothe available pre-booked resources the broker has in a number of cloudproviders, maximizing the broker profit. Eight list scheduling heuristicsare proposed to solve the problem, by taking into account different criteriafor mapping request to available virtual machines. The experimentalevaluation analyzes the profit, makespan, and flowtime results of theproposed methods over a set of 400 problem instances that account forrealistic workloads and scenarios using real data from cloud providers.Lire moins >
Lire la suite >This article introduces the formulation of the Virtual MachinePlanning Problem in cloud computing systems. It deals with the effi-cient allocation of a set of virtual machine requests from customers intothe available pre-booked resources the broker has in a number of cloudproviders, maximizing the broker profit. Eight list scheduling heuristicsare proposed to solve the problem, by taking into account different criteriafor mapping request to available virtual machines. The experimentalevaluation analyzes the profit, makespan, and flowtime results of theproposed methods over a set of 400 problem instances that account forrealistic workloads and scenarios using real data from cloud providers.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
Source :