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Research Article
Gossip-based search selection in hybrid peer-to-peer networks
Article first published online: 1 MAY 2007
DOI: 10.1002/cpe.1188
Copyright © 2007 John Wiley & Sons, Ltd.
Issue
1532-0634/asset/cover.gif?v=1&s=6094df24c795ce080ff6df6ff3b6bcec19adb708 "Concurrency and Computation: Practice and Experience")
Concurrency and Computation: Practice and Experience
Special Issue: Recent Advances in Peer-to-Peer Systems and Security (P2P 2006)
Volume 20, Issue 2, pages 139–153, February 2008
Additional Information
How to Cite
Zaharia, M. and Keshav, S. (2008), Gossip-based search selection in hybrid peer-to-peer networks. Concurrency Computat.: Pract. Exper., 20: 139–153. doi: 10.1002/cpe.1188
Publication History
- Issue published online: 19 DEC 2007
- Article first published online: 1 MAY 2007
- Manuscript Revised: 30 JAN 2007
- Manuscript Accepted: 30 JAN 2007
- Manuscript Received: 28 SEP 2006
Funded by
- National Science and Engineering Research Council of Canada
- Canada Research Chair Program
- Nortel Networks
- Sun Microsystems Canada
- Intel Corporation
- Sprint Corporation
- Abstract
- References
- Cited By
Keywords:
- peer-to-peer systems;
- search;
- global statistics;
- gossip
Abstract
We present GAB, a search algorithm for hybrid peer-to-peer networks, that is, networks that search using both flooding and a distributed hash table (DHT). GAB uses a gossip-style algorithm to collect global statistics about document popularity to allow each peer to make intelligent decisions about which search style to use for a given query. Moreover, GAB automatically adapts to changes in the operating environment. Synthetic and trace-driven simulations show that compared to a simple hybrid approach that always floods first, trying a DHT if too few results are found, GAB reduces the response time by 25–50% and the average query bandwidth cost by 45%, with no loss in recall. GAB scales well, with only a 7% degradation in performance despite a tripling in system size. Copyright © 2007 John Wiley & Sons, Ltd.