Using genetic algorithm to implement cost-driven web service selection

  • Authors:

  • Lei Cao;Minglu Li;Jian Cao

  • Affiliations:

  • Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China. E-mail: clcao@sjtu.edu.cn/ {li-ml,cao-jian}@cs.sjtu.edu.cn;Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China. E-mail: clcao@sjtu.edu.cn/ {li-ml,cao-jian}@cs.sjtu.edu.cn;Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China. E-mail: clcao@sjtu.edu.cn/ {li-ml,cao-jian}@cs.sjtu.edu.cn

  • Venue:
  • Multiagent and Grid Systems - Special Issue on Nature inspired systems for parallel, asynchronous and decentralised environments
  • Year:
  • 2007

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Abstract

Web services composition has been one of the hottest research topics. But with the ever-increasing number of functional similar web services being made available on the Internet, there is a need to be able to distinguish them using a set of well-defined Quality of Service (QoS) criteria. The cost is the primary concern of many business processes. This paper proposes a new solution using Genetic Algorithm (GA) to implement cost-driven web service selection. GA is utilized to optimize a business process composed of many service agents (SAgs). Each SAg corresponds to a collection of available web services provided by multiple service providers to perform a specific function. Service selection is an optimization process taking into account the relationships among the services. Better performance has been gotten using GA in the paper than using a local service selection strategy. The global optimal solution might also be achieved with proper GA parameters.