Efficient search based on content similarity over self-organizing P2P networks |
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Authors: | Christos Doulkeridis Akrivi Vlachou Kjetil Nørvåg Yannis Kotidis Michalis Vazirgiannis |
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Affiliation: | (1) Department of Computer and Information Science, NTNU, 7491 Trondheim, Norway;(2) Department of Informatics, AUEB, 10434 Athens, Greece |
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Abstract: | The advent of the World Wide Web has made an enormous amount of information available to everyone and the widespread use of digital equipment enables end-users (peers) to produce their own digital content. This vast amount of information requires scalable data management systems. Peer-to-peer (P2P) systems have so far been well established in several application areas, with file-sharing being the most prominent. The next challenge that needs to be addressed is (more complex) data sharing, management and query processing, thus facilitating the delivery of a wide spectrum of novel data-centric applications to the end-user, while providing high Quality-of-Service. In this paper, we propose a self-organizing P2P system that is capable to identify peers with similar content and intentionally assign them to the same super-peer. During content retrieval, fewer super-peers need to be contacted and therefore efficient similarity search is supported, in terms of reduced network traffic and contacted peers. Our approach increases the responsiveness and reliability of a P2P system and we demonstrate the advantages of our approach using large-scale simulations. |
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