Performing Content-Based Image Retrieval (CBIR) in Internet connected databases through Peer-to-Peer (P2P) network (P2P-CBIR) helps to effectively explore the large-scale image database distributed over connected peers. Decentralized unstructured P2P framework is adopted in our system to compromise with the structured one while still reserving flexible routing control when peers join/leave or network fails. The P2P- CBIR search engine is designed to provide multi-instance query with multi-feature types to effectively reduce network traffic while maintaining high retrieval accuracy. In addition, the proposed P2P-CBIR system is also designed in the way to provide scalable retrieval function, which can adaptively control the query scope and progressively refine the accuracy of retrieved results. To reflect the most updated local database characteristics for the P2P-CBIR users, reconfiguring system at each regular interval time can effectively reduce trivial peer routing and retrieval operations due to imprecise configuration. Experiments demonstrated that the average recall rate of the proposedP2P-CBIR with reconfiguration is higher than the one without about 20%, and the latter outperforms previous methods, i.e., firework query model (FQM) and breadth-first search (BFS) about 20% and 120%, respectively, under the same range of TTL values.
A Semantic Peer-to-Peer Network for Service Composition in Scientific Domains