Enhancing P2P File-Sharing with an Internet-Scale Query Processor

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Hellerstein, Joseph M
Huebsch, Ryan
Shenker, Scott
Stoica, Ion

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In this paper, we address the problem of designing a scalable, accurate query processor for peer-to-peer filesharing and similar distributed keyword search systems. Using a globally-distributed monitoring infrastructure, we perform an extensive study of the Gnutella filesharing network, characterizing its topology, data and query workloads. We observe that Gnutella's query processing approach performs well for popular content, but quite poorly for rare items with few replicas. We then consider an alternate approach based on Distributed Hash Tables (DHTs). We describe our implementation of PIERSearch, a DHT-based system, and propose a hybrid system where Gnutella is used to locate popular items, and PIERSearch for handling rare items. We develop an analytical model of the two approaches, and use it in concert with our Gnutella traces to study the tradeoff between query recall and system overhead of the hybrid system. We evaluate a variety of localized schemes for identifying items that are rare and worth handling via the DHT. Lastly, we show in a live deployment on fifty nodes on two continents that it nicely complements Gnutella in its ability to handle rare items.

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2004-09-01

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Departmental Papers (CIS)

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2023-05-17T00:28:07.000

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Postprint version. Published in Proceedings of the Thirtieth International Conference on Very Large Databases (VLDB), September 2004, pages 432-443. NOTE: At the time of publication, author Boon Thau Loo was affiliated with the University of California at Berkeley. Currently (March 2007), he is a faculty member in the Department of Computer and Information Science at the University of Pennsylvania. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the VLDB copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Very Large Data Base Endowment. To copy otherwise, or to republish, requires a fee and/or special permission from the Endowment.

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