A clustering and selection model for service composition using granular computing

Abstract

Service Oriented Architecture (SOA) and Service Oriented Computing (SOC) are prevailing technologies for sharing and reusing resources. Service composition is an envisioned methodology used in SOA and SOC to build value-added services. The existed service clustering and selection models are mostly designed for service discovery and there is few considering the requirement of service composition from the point of view of end-users. A multi-grain clustering and selection model for service composition is proposed in this paper. This model considers the requirement of customers in service composition in the end-user view and we give a formal specification on this model using the methodology deriving from granular computing. The proposed model is more understandable for an end-user and conforms to the intuitive granular cognition mode. © 2009 IEEE.