Using genetic algorithm to implement cost-driven web service selection

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.