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A parallel hybrid evolutionary algorithm for the optimization of broker virtual machines subletting in cloud systems
iturriaga, Santiago; Nesmachnow, Sergio; Dorronsoro, Bernabe et al.
2013In International Conference on P2P, Parallel, Grid, Cloud and Internet Computing
Peer reviewed
 

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Keywords :
parallel evolutionary algorithms; scheduling; cloud computing
Abstract :
[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 :
Computer science
Author, co-author :
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)
External co-authors :
yes
Language :
English
Title :
A parallel hybrid evolutionary algorithm for the optimization of broker virtual machines subletting in cloud systems
Publication date :
2013
Event name :
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
Event date :
October, 2013
Audience :
International
Main work title :
International Conference on P2P, Parallel, Grid, Cloud and Internet Computing
ISBN/EAN :
978-0-7695-5094-7
Peer reviewed :
Peer reviewed
Available on ORBilu :
since 20 December 2013

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