Ranked Matching of OWL-S Process Model for Distributed Discovery of SWs in P2P Systems

Semantic Web services (SWs) and P2P computing have emerged as new paradigms for solving complex problems by enabling large-scale aggregation and sharing of distributed computational resources. In this paper, we present a scalable approach based on epidemic discovery algorithm to discover new distributed and heterogeneous collaborative applications of large-scale distributed systems in a P2P network, and to rank the results according to a similarity score expressing the affinities between each of them and a user-submitted query. In order to reduce the execution time and improve the applicability of the epidemic discovery algorithm for discovering SWs, we propose the matching of ontology OWL-S process model in the heart of this algorithm which reduces the search space while keeping an acceptable matching quality level. Moreover, our matching approach is able to detect complex mappings between OWL-S process models based on their parameters. Experiments showed that the matching technique reduces considerably the execution time, maintaining at the same time a good quality of the distributed discovery of SWs in a P2P network.