Optimizing the Semantic Web Service Composition Process Using Cuckoo Search

  • Viorica Rozina Chifu
  • Cristina Bianca Pop
  • Ioan Salomie
  • Dumitru Samuel Suia
  • Alexandru Nicolae Niculici
Part of the Studies in Computational Intelligence book series (SCI, volume 382)

Abstract

The behavior of biological individuals which efficiently deal with complex life problems represents an inspiration source in the design of meta-heuristics for solving optimization problems. The Cuckoo Search is such a meta-heuristic inspired by the behavior of cuckoos in search for the appropriate nest where to lay eggs. This paper investigates how the Cuckoo Search meta-heuristic can be adapted and enhanced to solve the problem of selecting the optimal solution in semantic Web service composition. To improve the performance of the cuckoo-inspired algorithm we define a 1-OPT heuristic which expands the search space in a controlled way so as to avoid the stagnation on local optimal solutions. The search space is modeled as an Enhanced Planning Graph, dynamically built for each user request. To identify the optimal solution encoded in the graph we define a fitness function which uses the QoS attributes and the semantic quality as selection criteria. The cuckoo-inspired method has been evaluated on a set of scenarios from the trip planning domain.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Viorica Rozina Chifu
    • 1
  • Cristina Bianca Pop
    • 1
  • Ioan Salomie
    • 1
  • Dumitru Samuel Suia
    • 1
  • Alexandru Nicolae Niculici
    • 1
  1. 1.Department of Computer ScienceTechnical University of Cluj-NapocaRomania

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