Context-Aware Dynamic Service Matchmaking

In pervasive environments, the current service matchmaking is lack of context information with machine understandable and unable to deal with uncertainty of service properties, so it cannot achieve intelligent service discovery. This paper presents a fuzzy rough set theory based context-aware dynamic service matchmaking approach that composes an application through combining semantic information and context information. The proposed approach consists of formalized service description model with semantics and context attributes, and fuzzy rough set based service matchmaking. By describing the context attributes, the proposed approach is capable of composing context-aware application. Through a transformation technique, the incomplete information system is converted into a simpler system and then reducts are obtained from the transformed system based fuzzy rough set theory. Afterwards, the candidate service sets are selected by the function of the degree of keyword match and ranked through the function of the degree of service match. This paper describes the design and mechanism of the proposed approach. The proposed approach is expected to increase users´ satisfaction in pervasive environments.