A Multi-Objective Hybrid Particle Swarm Optimization-based Service Identification

Service identification step is a basic requirement for a detailed design and implementation of services in a Service Oriented Architecture (SOA). Existing methods for service identification ignore the automation capability while providing human based prescriptive guidelines, which mostly are not applicable at enterprise scales. In this paper, we propose a top down approach to identify automatically services from business process. We use for clustering a hybrid particle swarm optimization algorithm and several design metrics for produce reusable services with proper granularity and acceptable level of cohesion and coupling. The experimental results show that our method HPSOSI (Hybrid Particle Swarm Algorithm for Service Identification) can achieve a high performance in terms of execution time, and significant quality in terms of high modularization, strong cohesion, and weak coupling of the identified services..