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Adaptive neighborhood selection in peer-to-peer networks based on content similarity and reputation

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Abstract

To address the two most critical issues in P2P file-sharing systems: efficient information discovery and authentic data acquisition, we propose a Gnutella-like file-sharing protocol termed Adaptive Gnutella Protocol (AGP) that not only improves the querying efficiency in a P2P network but also enhances the quality of search results at the same time. The reputation scheme in the proposed AGP evaluates the credibility of peers based on their contributions to P2P services and subsequently clusters nodes together according to their reputation and shared content, essentially transforming the P2P overlay network into a topology with collaborative and reputed nodes as its core. By detecting malicious peers as well as free-riders and eventually pushing them to the edge of the overlay network, our AGP propagates search queries mainly within the core of the topology, accelerating the information discovery process. Furthermore, the clustering of nodes based on authentic and similar content in our AGP also improves the quality of search results. We have implemented the AGP with the PeerSim simulation engine and conducted thorough experiments on diverse network topologies and various mixtures of honest/dishonest nodes to demonstrate improvements in topology transformation, query efficiency, and search quality by our AGP.

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Notes

  1. Another metric could be the node’s buffer space for outgoing messages, during an epoch.

  2. Ultra-peers are nodes with high bandwidth capacity and high number of direct connections.

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Authors and Affiliations

  1. University of Athens, Athens, 15784, Greece

    Ioannis Pogkas & Alex Delis

  2. Polytechnic Institute of New York University, Brooklyn, NY, 11201, USA

    Vassil Kriakov

  3. Yahoo! Inc., Santa Clara, CA, 95054, USA

    Zhongqiang Chen

Authors
  1. Ioannis Pogkas
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  2. Vassil Kriakov
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  3. Zhongqiang Chen
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  4. Alex Delis
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Correspondence to Vassil Kriakov.

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Pogkas, I., Kriakov, V., Chen, Z. et al. Adaptive neighborhood selection in peer-to-peer networks based on content similarity and reputation. Peer-to-Peer Netw. Appl. 2, 37–59 (2009). https://doi.org/10.1007/s12083-008-0018-2

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