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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
computer science
A parallel bi-objective hybrid metaheuristic for energy-aware scheduling for cloud computing systems
Journal of Parallel and Distributed Computing, Volume 71, No. 11, Year 2011
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Description
In this paper, we investigate the problem of scheduling precedence-constrained parallel applications on heterogeneous computing systems (HCSs) like cloud computing infrastructures. This kind of application was studied and used in many research works. Most of these works propose algorithms to minimize the completion time (makespan) without paying much attention to energy consumption. We propose a new parallel bi-objective hybrid genetic algorithm that takes into account, not only makespan, but also energy consumption. We particularly focus on the island parallel model and the multi-start parallel model. Our new method is based on dynamic voltage scaling (DVS) to minimize energy consumption. In terms of energy consumption, the obtained results show that our approach outperforms previous scheduling methods by a significant margin. In terms of completion time, the obtained schedules are also shorter than those of other algorithms. Furthermore, our study demonstrates the potential of DVS. © 2011 Elsevier Inc. All rights reserved.
Authors & Co-Authors
Mezmaz, Mohand Said
Belgium, Mons
Université de Mons
Melab, Nouredine
France, Le Chesnay
Inria Institut National de Recherche en Informatique et en Automatique
Kessaci, Yacine
France, Le Chesnay
Inria Institut National de Recherche en Informatique et en Automatique
Lee, Y. C.
Australia, Sydney
The University of Sydney
Talbi, Emna Ghazali
France, Le Chesnay
Inria Institut National de Recherche en Informatique et en Automatique
Saudi Arabia, Riyadh
King Saud University
Zomaya, Albert Y.H.
Australia, Sydney
The University of Sydney
Tuyttens, Daniel
Belgium, Mons
Université de Mons
Statistics
Citations: 312
Authors: 7
Affiliations: 4
Identifiers
Doi:
10.1016/j.jpdc.2011.04.007
ISSN:
07437315
Research Areas
Genetics And Genomics