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The Scientific World Journal
Volume 2013, Article ID 350934, 13 pages
Research Article

Multi-Objective Approach for Energy-Aware Workflow Scheduling in Cloud Computing Environments

1L@RIS Laboratory, EISTI, Avenue du Parc, 95011 Cergy-Pontoise, France
2ETIS Laboratory, CNRS UMR8051, University of Cergy-Pontoise, ENSEA, 6 Avenue du Ponceau, 95014 Cergy-Pontoise, France

Received 6 August 2013; Accepted 12 September 2013

Academic Editors: S. H. Rubin and A. F. Zobaa

Copyright © 2013 Sonia Yassa et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


We address the problem of scheduling workflow applications on heterogeneous computing systems like cloud computing infrastructures. In general, the cloud workflow scheduling is a complex optimization problem which requires considering different criteria so as to meet a large number of QoS (Quality of Service) requirements. Traditional research in workflow scheduling mainly focuses on the optimization constrained by time or cost without paying attention to energy consumption. The main contribution of this study is to propose a new approach for multi-objective workflow scheduling in clouds, and present the hybrid PSO algorithm to optimize the scheduling performance. Our method is based on the Dynamic Voltage and Frequency Scaling (DVFS) technique to minimize energy consumption. This technique allows processors to operate in different voltage supply levels by sacrificing clock frequencies. This multiple voltage involves a compromise between the quality of schedules and energy. Simulation results on synthetic and real-world scientific applications highlight the robust performance of the proposed approach.