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...
| Publicado en: | Scientific World Journal pp. 350934 - 350935 |
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| Autores principales: | , , , |
| Formato: | research Journal Article |
| Publicado: |
Wiley-Blackwell
2013
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104123244&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104123244 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1537744X 1BX5 jtl: Scientific World Journal issn: 1537744X maglogo: N pubinfo: dt: 2013 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 104123244 NLM24319361 2012405558 10.1155/2013/350934 NLM24319361 PMC3835373 104123244 ppf: 350934 ppct: 1 formats: tig: 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 refInfo: holdings: @attributes: islocal: N |
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