• DocumentCode
    2664499
  • Title

    A Penalty-Based Genetic Algorithm for QoS-Aware Web Service Composition with Inter-service Dependencies and Conflicts

  • Author

    Ai, Lifeng ; Tang, Maolin

  • Author_Institution
    Queensland Univ. of Technol., Brisbane, QLD, Australia
  • fYear
    2008
  • fDate
    10-12 Dec. 2008
  • Firstpage
    738
  • Lastpage
    743
  • Abstract
    In Web service based systems, new value-added Web services can be constructed by integrating existing Web services. A Web service may have many implementations, which are functionally identical, but have different quality of service (QoS) attributes, such as response time, price, reputation, reliability, availability and so on. Thus, a significant research problem in Web service composition is how to select an implementation for each of the component Web services so that the overall QoS of the composite Web service is optimal. This is so called QoS-aware Web service composition problem. In some composite Web services there are some dependencies and conflicts between the Web service implementations. However, existing approaches cannot handle the constraints. This paper tackles the QoS-aware Web service composition problem with inter-service dependencies and conflicts using a penalty-based genetic algorithm (GA). Experimental results demonstrate the effectiveness and the scalability of the penalty-based GA.
  • Keywords
    Web services; genetic algorithms; quality of service; software quality; QoS-aware Web service composition; composite Web service; interservice conflicts; interservice dependencies; penalty-based genetic algorithm; quality of service attributes; value-added Web service; Australia; Availability; Collaboration; Delay; Genetic algorithms; Quality of service; Scalability; Simple object access protocol; Web services; XML; QoS; Web service composition; genetic algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence for Modelling Control & Automation, 2008 International Conference on
  • Conference_Location
    Vienna
  • Print_ISBN
    978-0-7695-3514-2
  • Type

    conf

  • DOI
    10.1109/CIMCA.2008.104
  • Filename
    5172717