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Facilitating an ant colony algorithm for multi-objective data-intensive service provisions

Journal Article


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Abstract


  • The explosion of enormous sources of digital data has led to greater dependence on data-intensive services. Applications

    based on data-intensive services have become one of the most challenging applications in cloud computing.

    The service provision, and in particular service composition, will face new challenges as the services and data grow.

    In this paper, we will evaluate an ant colony system to resolve the multi-objective data-intensive service composition

    problem. The algorithm for a multi-objective context will get a set of Pareto-optimal solutions considering two

    objectives at the same time: the total cost and the total execution time of a composite service.

Authors


  •   Wang, Lijuan (external author)
  •   Shen, Jun
  •   Luo, Junzhou (external author)

Publication Date


  • 2015

Citation


  • Wang, L., Shen, J. & Luo, J. (2015). Facilitating an ant colony algorithm for multi-objective data-intensive service provisions. Journal of Computer and System Sciences, 81 (4), 734-746.

Scopus Eid


  • 2-s2.0-84924987590

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=4228&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/3212

Has Global Citation Frequency


Number Of Pages


  • 12

Start Page


  • 734

End Page


  • 746

Volume


  • 81

Issue


  • 4

Place Of Publication


  • United States

Abstract


  • The explosion of enormous sources of digital data has led to greater dependence on data-intensive services. Applications

    based on data-intensive services have become one of the most challenging applications in cloud computing.

    The service provision, and in particular service composition, will face new challenges as the services and data grow.

    In this paper, we will evaluate an ant colony system to resolve the multi-objective data-intensive service composition

    problem. The algorithm for a multi-objective context will get a set of Pareto-optimal solutions considering two

    objectives at the same time: the total cost and the total execution time of a composite service.

Authors


  •   Wang, Lijuan (external author)
  •   Shen, Jun
  •   Luo, Junzhou (external author)

Publication Date


  • 2015

Citation


  • Wang, L., Shen, J. & Luo, J. (2015). Facilitating an ant colony algorithm for multi-objective data-intensive service provisions. Journal of Computer and System Sciences, 81 (4), 734-746.

Scopus Eid


  • 2-s2.0-84924987590

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=4228&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/3212

Has Global Citation Frequency


Number Of Pages


  • 12

Start Page


  • 734

End Page


  • 746

Volume


  • 81

Issue


  • 4

Place Of Publication


  • United States