Creating social networks to improve peer-to-peer networking

Authors:
Andrew Fast;David Jensen;Brian Neil Levine
Affiliations:
University of Massachusetts - Amherst, Amherst, MA;University of Massachusetts - Amherst, Amherst, MA;University of Massachusetts - Amherst, Amherst, MA
Venue:
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Year:
2005

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Abstract

We use knowledge discovery techniques to guide the creation of efficient overlay networks for peer-to-peer file sharing. An overlay network specifies the logical connections among peers in a network and is distinct from the physical connections of the network. It determines the order in which peers will be queried when a user is searching for a specific file. To better understand the role of the network overlay structure in the performance of peer-to-peer file sharing protocols, we compare several methods for creating overlay networks. We analyze the networks using data from a campus network for peer-to-peer file sharing that recorded anonymized data on 6,528 users sharing 291,925 music files over an 81-day period. We propose a novel protocol for overlay creation based on a model of user preference identified by latent-variable clustering with hierarchical Dirichlet processes (HDPs). Our simulations and empirical studies show that the clusters of songs created by HDPs effectively model user behavior and can be used to create desirable network overlays that outperform alternative approaches.