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PAIS: A Proximity-Aware Interest-Clustered P2P File Sharing System

Haiying Shen

Open publisher page 3 citations

Abstract

Efficient file query is important to the overall performance of peer-to-peer (P2P) file sharing systems. Clustering peers by their common interests can significantly enhance the efficiency of file query. On the other hand, clustering peers by their physical proximity can also improve file query performance. Few current works are able to cluster peers based on both peer interest and physical proximity. It is even harder to realize it in structured P2Ps due to their strictly defined topologies, although they provide higher file query efficiency than unstructured P2Ps. In this paper, we introduce a proximity-aware and interest-clustered P2P file sharing system (PAIS) based on a structured P2P. It groups peers based on both interest and proximity. PAIS supports sophisticated routing and clustering strategies based on a hierarchical topology. Theoretical analysis and simulation results demonstrate that PAIS dramatically reduces the overhead and enhances efficiency in file sharing.

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What this paper is about

Efficient file query is important to the overall performance of peer-to-peer (P2P) file sharing systems. Clustering peers by their common interests can significantly enhance the efficiency of file query. On the other hand, clustering peers by their physical proximity can also improve file query performance. Few current works are able to cluster peers based on both peer interest and physical proximity. It is even harder to realize it in structured P2Ps due to their strictly defined topologies, although they provide higher file query efficiency than unstructured P2Ps. In this paper, we introduce a proximity-aware and interest-clustered P2P file sharing system (PAIS) based on a structured P2P. It groups peers based on both interest and proximity. PAIS supports sophisticated routing and clustering strategies based on a hierarchical topology. Theoretical analysis and simulation results demonstrate that PAIS dramatically reduces the overhead and enhances efficiency in file sharing.

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Available abstract

Efficient file query is important to the overall performance of peer-to-peer (P2P) file sharing systems. Clustering peers by their common interests can significantly enhance the efficiency of file query. On the other hand, clustering peers by their physical proximity can also improve file query performance. Few current works are able to cluster peers based on both peer interest and physical proximity. It is even harder to realize it in structured P2Ps due to their strictly defined topologies, although they provide higher file query efficiency than unstructured P2Ps. In this paper, we introduce a proximity-aware and interest-clustered P2P file sharing system (PAIS) based on a structured P2P. It groups peers based on both interest and proximity. PAIS supports sophisticated routing and clustering strategies based on a hierarchical topology. Theoretical analysis and simulation results demonstrate that PAIS dramatically reduces the overhead and enhances efficiency in file sharing.

Key concepts: File sharing, Computer science, Torrent file, Peer-to-peer, Cluster analysis, Distributed computing, Overhead (engineering), Network topology

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