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GA-ETI: An enhanced genetic algorithm for the scheduling of scientific workflows in cloud environments
The University of Sydney, Sydney, Australia.
Karlstad University, Faculty of Health, Science and Technology (starting 2013).ORCID iD: 0000-0001-9194-010X
CSIRO, Australia.
School of Computer Science, China University of Geosciences, China.
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2016 (English)In: Journal of Computational Science, ISSN 1877-7503, E-ISSN 1877-7511Article in journal (Refereed) Epub ahead of print
Place, publisher, year, edition, pages
Elsevier, 2016.
Keyword [en]
Cloud computing; Scientific workflow; Scheduling algorithms; Genetic algorithm; Virtual machine
National Category
Computer Science
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-45845DOI: 10.1016/j.jocs.2016.08.007OAI: oai:DiVA.org:kau-45845DiVA: diva2:968107
Available from: 2016-09-12 Created: 2016-09-12 Last updated: 2017-02-20Bibliographically approved

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Taheri, Javid
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Faculty of Health, Science and Technology (starting 2013)
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