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Genetic Programming with Greedy Search for Web Service Composition

  • Anqi Wang
  • Hui Ma
  • Mengjie Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8056)

Abstract

Service compositions build new web services by orchestrating sets of existing web services provided in service repositories. Due to the increasing number of available web services, the search space for finding best service compositions is growing exponentially. In this paper, a combination of genetic programming and random greedy search is proposed for service composition. The greedy algorithm is utilized to generate valid and locally optimized individuals to populate the initial generation for genetic programming, and to perform mutation operations during genetic programming. A full experimental evaluation has been carried out using public benchmark test cases with repositories of up to 15,000 web services and 31,000 properties. The results show good performance in searching for best service compositions, where the number of atomic web services used and the tree depth are used as objectives for minimization.

Keywords

Genetic Programming Greedy Algorithm Service Composition Composite Service Service Repository 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Anqi Wang
    • 1
  • Hui Ma
    • 1
  • Mengjie Zhang
    • 1
  1. 1.Victoria University of WellingtonNew Zealand

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