Recent years saw the rapid development of peer-topeer (P2P) networks in a great variety of applications. However, similarity-based k-nearest-neighbor retrieval (k-NN) is still a challenging task in P2P networks due to the multiple constraints such as the dynamic topologies and the unpredictable data updates. Caching is an attractive solution that reduces network traffic and hence could remedy the technological constraints of P2P networks. However, traditional caching techniques have some major shortcomings that make them unsuitable for similarity search, such as the lack of semantic locality representation and the rigidness of exact matching on data objects. To facilitate the efficient similarity search, we propose semantic-aware caching scheme (SAC) in this paper. The proposed scheme is hierarchy-free, fully dynamic, non-flooding, and do not add much system overhead. By exploring the content distribution, SAC drastically reduces the cost of similarity-based k-NN retrieval in P2P networks. The performance of SAC is evaluated through simulation study and compared against several search schemes as advanced in the literature.
B. Yang et al., "Multimedia Correlation Analysis in Unstructured Peer-to-Peer Network," Proceedings of the 2006 International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM'06), Institute of Electrical and Electronics Engineers (IEEE) Computer Society, Jan 2006.
The definitive version is available at https://doi.org/10.1109/WOWMOM.2006.76
2006 International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM'06)
Keywords and Phrases
Peer-To-Peer Networks; Caching; K-Nearest-Neighbor Retrieval; Network Traffic; Semantic Locality Representation; Ultimedia Correlation
Article - Conference proceedings
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