Discovery of services in context using rough sets

Abstract

In pervasive computing environment, service discovery plays an important role for automatically locating and executing the most suitable services according to related contextual information to fulfill user requirements. Current service discovery mechanisms rarely take context into consideration, leading to poor user experiences. In this paper, we propose an approach to service discovery that makes a good use of contextual information from both user query and service advertisement to offer better quality of service. Based on selected services that functionally satisfy a user query, the rough set theory is applied to further deal with contextual properties for decision on invoking the best service. An ontology-based model of context is constructed to enable knowledge sharing, and semantic matchmaking, and an evaluation model is set up for service ranking during the discovery process.