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A systematic review of bio-inspired service concretization

Journal Article


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Abstract


  • In service oriented computing, Web service selection is an important part of Web service composition. The Web service composition is achieved by solving the Web service concretization problem. The literature presents two types of Web service concretization approaches: local optimization approaches and global optimization approaches. There are three types of algorithmic methods in the global optimization approaches: optimal methods, sub-optimal methods, and soft constraints-based methods. The bio-inspired algorithms are sub-optimal methods. This paper will firstly present a hierarchical taxonomy of Web service concretization approaches. Then we conduct a systematic review on the current research of Web service concretization based on three bio-inspired algorithms, namely, ant colony optimization algorithms, genetic algorithms, and particle swarm optimization algorithms. Based on the findings from the systematic review, this paper also discusses the underlying applications of bio-inspired algorithms to the data-intensive service concretization problems.

Authors


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

Publication Date


  • 2017

Citation


  • Wang, L. & Shen, J. (2017). A systematic review of bio-inspired service concretization. IEEE Transactions on Services Computing, 10 (4), 493-505.

Scopus Eid


  • 2-s2.0-85029389680

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=6400&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/5372

Has Global Citation Frequency


Number Of Pages


  • 12

Start Page


  • 493

End Page


  • 505

Volume


  • 10

Issue


  • 4

Place Of Publication


  • United States

Abstract


  • In service oriented computing, Web service selection is an important part of Web service composition. The Web service composition is achieved by solving the Web service concretization problem. The literature presents two types of Web service concretization approaches: local optimization approaches and global optimization approaches. There are three types of algorithmic methods in the global optimization approaches: optimal methods, sub-optimal methods, and soft constraints-based methods. The bio-inspired algorithms are sub-optimal methods. This paper will firstly present a hierarchical taxonomy of Web service concretization approaches. Then we conduct a systematic review on the current research of Web service concretization based on three bio-inspired algorithms, namely, ant colony optimization algorithms, genetic algorithms, and particle swarm optimization algorithms. Based on the findings from the systematic review, this paper also discusses the underlying applications of bio-inspired algorithms to the data-intensive service concretization problems.

Authors


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

Publication Date


  • 2017

Citation


  • Wang, L. & Shen, J. (2017). A systematic review of bio-inspired service concretization. IEEE Transactions on Services Computing, 10 (4), 493-505.

Scopus Eid


  • 2-s2.0-85029389680

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=6400&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/5372

Has Global Citation Frequency


Number Of Pages


  • 12

Start Page


  • 493

End Page


  • 505

Volume


  • 10

Issue


  • 4

Place Of Publication


  • United States