A Genetic Algorithm Based Approach to Service Identification

One of the key activities in service-oriented solution development is the identification of services according to a set of predefined design principles. Existing service identification approaches are often prescriptive and based on the architect's experience, therefore might lead to non-optimal designs which results in lower performance, reduced scalability, and complicated dependencies between services. In this paper, an automated method for identifying business services has been proposed by adopting design metrics based on top-down decomposition of processes. This method takes a set of enterprise business processes as input and produces a set of non-dominated solutions representing appropriate business services using a multi-objective genetic algorithm. The method has been realized in form of a tool implementation and a case study has been conducted to show its applicability.