Abstract
Locating contents is an essential function, but it presents a very difficult and challenging problem for large-scale Peer-to-Peer (P2P) systems. Many P2P systems, protocols, architectures, and search strategies are proposed for this problem. In this paper, we focus on the self-organization of a community structure based on user preferences for P2P systems. We propose these methods to improve P2P search performance: 1) Extended Pong, 2) Pong Proxy, 3) QRP with Firework 4) Backward Learning, and 5) Community Self-Organization Algorithm. We evaluate the performance of the self-organized community network through simulations. These results show that the self-organized community network maintains a high query hit rate without overflow.
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Kojima, K. (2004). Self-Organization Approach of Communities for P2P Networks. In: Papatriantafilou, M., Hunel, P. (eds) Principles of Distributed Systems. OPODIS 2003. Lecture Notes in Computer Science, vol 3144. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27860-3_12
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DOI: https://doi.org/10.1007/978-3-540-27860-3_12
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