Multi-objective approach for energy-aware workflow scheduling in cloud computing environments.

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 o...

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Publicado en:Scientific World Journal pp. 350934 - 350935
Autores principales: Yassa, Sonia, Chelouah, Rachid, Kadima, Hubert, Granado, Bertrand
Formato: research Journal Article
Publicado: Wiley-Blackwell 2013
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 2013
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      pub: Wiley-Blackwell
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        10.1155/2013/350934
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        atl: Multi-objective approach for energy-aware workflow scheduling in cloud computing environments.
      aug:
        au:
          Yassa, Sonia
          Chelouah, Rachid
          Kadima, Hubert
          Granado, Bertrand
        affil: L@RIS Laboratory, EISTI, Avenue du Parc, 95011 Cergy-Pontoise, France ; ETIS Laboratory, CNRS UMR8051, University of Cergy-Pontoise, ENSEA, 6 Avenue du Ponceau, 95014 Cergy-Pontoise, France.
      sug:
        subj:
          Algorithms
          Information Retrieval Methods
          Internet
          Signal Processing, Computer Assisted
          Software
          Systems Analysis
          Energy Transfer
      ab: 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.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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