[en] This article presents a new parallel hybrid evolutionary
algorithm to solve the problem of virtual machines
subletting in cloud systems. The problem deals with the efficient
allocation of a set of virtual machine requests from customers
into available pre-booked resources from a cloud broker, in
order to maximize the broker profit. The proposed parallel
algorithm uses a distributed subpopulations model, and a
Simulated Annealing operator. The experimental evaluation
analyzes the profit and makespan results of the proposed
methods over a set of problem instances that account for
realistic workloads and scenarios using real data from cloud
providers. A comparison with greedy heuristics indicates that
the proposed method is able to compute solutions with up to
133.8% improvement in the profit values, while accounting for
accurate makespan results.
Disciplines :
Sciences informatiques
Auteur, co-auteur :
iturriaga, Santiago
Nesmachnow, Sergio
Dorronsoro, Bernabe
El-Ghazali, Talbi
BOUVRY, Pascal ; University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
A parallel hybrid evolutionary algorithm for the optimization of broker virtual machines subletting in cloud systems
Date de publication/diffusion :
2013
Nom de la manifestation :
The 2-nd International Workshop on Soft Computing Techniques in Cluster and Grid Computing Systems (SCCG), part of the 8th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing
Date de la manifestation :
October, 2013
Manifestation à portée :
International
Titre de l'ouvrage principal :
International Conference on P2P, Parallel, Grid, Cloud and Internet Computing
