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Scalable retrieval and mining with optimal peer-to-peer configuration

IEEE TRANSACTIONS ON multiMEDIA 2008年第2期10卷 209-220页

作者： Chen, Jiann-Jone Hu, Chia-Jung Su, Chun-Rong Natl Taiwan Univ Sci & Technol Dept Elect Engn Taipei 106 Taiwan

We proposed to utilize the scalable peer-to-peer network to perform the content-based image retrieval and mining, Le, P2P-CBIRM. The decentralized unstructured P2P model with certain overheads, i.e., peer clustering and update procedures, is adopted to compromise with the structured one while still reserving flexible routing control when peers join/leave or network fails. The peer CBIRM engine is designed to utilize multi-instance query with multi-feature types to effectively reduce network traffic while maintaining high retrieval accuracy. It helps to enhance the knowledge discovery and image data mining capability. The proposed P2P-CBIRM system provides the scalable retrieval and mining function that the query scope and retrieval accuracy can be adaptively and progressively controlled. To improve the query efficiency (recall-rate/query-scope), it effectively utilizes both: 1) forwarding query message (forward phase) to reduce the query scope and 2) transmitting retrieval results (backward phase) such that activated peers keep filtering high similarity images on the link-path toward the query peer. Experiments show that the query efficiency of the scalable retrieval approach is better than previous methods, i.e., firework query model and breadth-first search. It provides a scalable knowledge discovery platform for efficient image data mining applications. We also proposed to optimally configure the P2P-CBIRM system such that, under a certain number of online users, it would yield the highest recall rate. Simulations demonstrate that, with the optimal configuration, recall rates can be improved to 2.5 to 3 times larger while the network traffic of each peer is reduced to 30% of the original, under the same number of on-line users.

关键词： content-based information retrieval and mining image database multi-instance query optimal system configuration peer-to-peer (P2P) networks scalable retrieval and mining

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Content-Based Image Retrieval on Reconfigurable Peer-to-Peer Networks

Content-Based Image Retrieval on Reconfigurable Peer-to-Peer...

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International Symposium on Biometrics and Security Technologies (ISBAST)

作者： Su, Chun-Rong Chen, Jiann-Jone Chang, Kai-Lin Natl Taiwan Univ Sci & Technol Dept Elect Engn Taipei 10673 Taiwan

ISBN: (纸本)9780769550107

Performing Content-Based Image Retrieval (CBIR) from Internet databases connected through Peer-to-Peer (P2P) network, abbreviated as 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 and maintain high retrieval accuracy. The proposed P2P-CBIR system is also designed to provide scalable retrieval control, which can adaptively control the query scope and progressively refine the accuracy of retrieved results. We also proposed to provide the most updated local database characteristics for the P2P-CBIR users. By reconfiguring system at each regular interval time, we can effectively reduce trivial peer routing and retrieval operations due to imprecise configuration. Experiments demonstrated that the average recall rate of the proposed P2P-CBIR with reconfiguration is higher than that of the one without about 10.73%, and the latter outperforms previous methods, i.e., firework query model (FQM) and breadth-first search (BFS) about 27% and 57%, respectively, under the same range of TTL values.

关键词： peer-to-peer networks multi-instance query content-based image retrieval scalable retrieval network search reconfiguration

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Reconfigurable content-based image retrieval on peer-to-peer networks

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INTERNATIONAL JOURNAL OF AD HOC AND UBIQUITOUS COMPUTING 2015年第1-2期18卷 23-36页

作者： Su, Chun-Rong Chen, Jiann-Jone Natl Taiwan Univ Sci & Technol Dept Elect Engn Dept Taipei 10607 Taiwan

Performing content-based image retrieval (CBIR) from Internet scale databases connected through peer-to-peer (P2P) networks, abbreviated as P2P-CBIR, helps to explore the large-scale image database distributed over connected peers. For P2P topology, the flexible decentralised unstructured P2P network topology is adopted, based on which informed-like searching approach enables flexible routing control when peers join/leave. The scalable retrieval control can be developed based on the P2P-CBIR framework, which can adapt the query scope and progressively refine the accuracy during the retrieval process. By reconfiguring system at each regular interval times, we can effectively reduce trivial peer routing and retrieval operations due to imprecise configurations. Experiments demonstrated that the average recall rate of the proposed P2P-CBIR method with reconfiguration is higher than that without about 10.73%, while the latter outperforms previous methods, i.e., firework query model (FQM) and breadth-first search (BFS), about 27% and 57%, respectively, under the same time-to-live (TTL) setting.

关键词： P2P peer-to-peer networks multi-instance query CBIR content-based image retrieval scalable retrieval peer linking reconfiguration ubiquitous computing

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