Bridging the Gap between Semantic Web Service Composition and Common Implementation Architectures

Semantic web techniques have been leveraged in planning methods for automated service composition. Typically, inputs and outputs of services are described in abstract concepts for efficient and meaningful matching between output of one service and input of another. However, existing methods have not examined concrete data structures, which are essential for successful service interaction in common implementation architectures. To address the problem, this paper proposes a matching method that can be incorporated into existing planning methods to ensure consistency in concrete data structures. The proposed method applies a two-phase matching process to efficiently filter out services that do not match at the abstract level. It also applies a data structure to organize similar services according to their relationships for efficient matching during the planning process.