Gossip-based search selection in hybrid peer-to-peer networks (2006)
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| Venue: | in Proceedings of the 5th International Workshop on Peer-to-Peer Systems (IPTPS’06 |
| Citations: | 15 - 0 self |
BibTeX
@INPROCEEDINGS{Zaharia06gossip-basedsearch,
author = {M. Zaharia and S. Keshav},
title = {Gossip-based search selection in hybrid peer-to-peer networks},
booktitle = {in Proceedings of the 5th International Workshop on Peer-to-Peer Systems (IPTPS’06},
year = {2006}
}
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Abstract
Abstract: We present GAB, a search algorithm for hybrid P2P networks, that is, networks that search using both flooding and a DHT. GAB uses a gossipstyle 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, 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. I.
