DMCA
Multimedia Correlation Analysis in Unstructured Peer-to-Peer Networks *
BibTeX
@MISC{Yang_multimediacorrelation,
author = {Bo Yang and Ali R. Hurson and Yu Jiao and Thomas E. Potok},
title = {Multimedia Correlation Analysis in Unstructured Peer-to-Peer Networks *},
year = {}
}
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Abstract
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 represent-tation 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. 1.
Keyphrases
p2p network multimedia correlation analysis unstructured peer-to-peer network much system similarity search major shortcoming dynamic topology efficient similarity search multiple constraint network traffic data object traditional caching technique semantic locality represent-tation content distribution great variety rapid development similarity-based k-nn retrieval similarity-based k-nearest-neighbor retrieval proposed scheme attractive solution unpredictable data update technological constraint simulation study semantic-aware caching scheme recent year challenging task several search scheme
