An improved genetic algorithm for web services selection

  • Authors:

  • Sen Su;Chengwen Zhang;Junliang Chen

  • Affiliations:

  • State Key Lab of Networking and Switching Technology, Beijing University of Posts & Telecommunications, Beijing, China;State Key Lab of Networking and Switching Technology, Beijing University of Posts & Telecommunications, Beijing, China;State Key Lab of Networking and Switching Technology, Beijing University of Posts & Telecommunications, Beijing, China

  • Venue:
  • DAIS'07 Proceedings of the 7th IFIP WG 6.1 international conference on Distributed applications and interoperable systems
  • Year:
  • 2007

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Abstract

An improved genetic algorithm is presented to select optimal web services composite plans from a lot of composite plans on the basis of global Quality-of-Service (QoS) constraints. The relation matrix coding scheme of genome is its basis. In this genetic algorithm, an especial fitness function and a mutation policy are proposed on the basis of the relation matrix coding scheme of genome. They enhance convergence of genetic algorithm and can get more excellent composite service plan because they accord with web services selection very well. The simulation results on QoS-aware web services selection have shown that the improved genetic algorithm can gain effectively the composite service plan that satisfies the global QoS requirements, and that the convergence of genetic algorithm was improved very well.