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Economical data-intensive service provision supported with a modified genetic algorithm

Conference Paper


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Abstract


  • The explosion of digital data and the dependence

    on data-intensive services have been recognized as the most

    significant characteristics of the decade. Providing efficient mechanisms

    for optimized data-intensive services will become critical

    to meet the expected growing demand. In order to create a

    cost minimizing data-intensive service composition solution, we

    design two steps and two negotiation processes over the lifetime

    of a data-intensive service composition. The solution for the first

    step is presented in this paper. The proposed service selection

    algorithm is based on a modified genetic algorithm, which some

    modifications of crossover and mutation operators are adopted

    in order to escape from local optima. The performance of the

    algorithm has been tested by simulations.

Authors


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

Publication Date


  • 2013

Citation


  • Wang, L. & Shen, J. (2013). Economical data-intensive service provision supported with a modified genetic algorithm. IEEE 2nd International Congress on Big Data (pp. 355-362). United States: IEEE.

Scopus Eid


  • 2-s2.0-84886013793

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=2110&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/1101

Has Global Citation Frequency


Start Page


  • 355

End Page


  • 362

Place Of Publication


  • United States

Abstract


  • The explosion of digital data and the dependence

    on data-intensive services have been recognized as the most

    significant characteristics of the decade. Providing efficient mechanisms

    for optimized data-intensive services will become critical

    to meet the expected growing demand. In order to create a

    cost minimizing data-intensive service composition solution, we

    design two steps and two negotiation processes over the lifetime

    of a data-intensive service composition. The solution for the first

    step is presented in this paper. The proposed service selection

    algorithm is based on a modified genetic algorithm, which some

    modifications of crossover and mutation operators are adopted

    in order to escape from local optima. The performance of the

    algorithm has been tested by simulations.

Authors


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

Publication Date


  • 2013

Citation


  • Wang, L. & Shen, J. (2013). Economical data-intensive service provision supported with a modified genetic algorithm. IEEE 2nd International Congress on Big Data (pp. 355-362). United States: IEEE.

Scopus Eid


  • 2-s2.0-84886013793

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=2110&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/1101

Has Global Citation Frequency


Start Page


  • 355

End Page


  • 362

Place Of Publication


  • United States