Constrained evolutionary computing approach to Web service compositions

Chun Che Huang, Wen Yau Liang, Wei Che Lee, Yung Huan Lai

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Web services are being adopted as a viable means of accessing Web-based applications. Web services are not only used to exchange information between enterprises but also to help software developers provide value-added services for various demands. Web service compositions are synthesised by researchers from elementary Web services, offering the opportunity for service providers and application developers to create value-added services. However, a problem exists in the current distribution process of Web service compositions: the general analysis and selection of services can be overly complex and are completed manually. Therefore, there is a need to manage composite Web services automatically. But the research related to ranking candidate services and selection of optimisation strategies is sparse. Yet, few have been published that consider the constraints of non-functional properties. In this article, a systemic but autonomous composition process has been proposed. This study proposes an evolutionary approach that applies the characteristics of the object-oriented concept of Web services and the genetic algorithm to effectively manage and optimise the Web service composition. It is capable of escaping not only from local optima due to a population-based approach, but also from unbiased nature, which enables it to perform well in a situation with little domain knowledge. In this article, the related literature is reviewed. Then, the Web service composition model incorporated with a genetic algorithm is proposed. Finally, a practical implementation is illustrated and shows a good result in terms of solution quality.

Original languageEnglish
Pages (from-to)1625-1638
Number of pages14
JournalInternational Journal of Systems Science
Volume42
Issue number10
DOIs
Publication statusPublished - 2011 Oct 1

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All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computer Science Applications

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