By Topic

DHTs over Peer Clusters for Distributed Information Retrieval

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Odysseas Papapetrou ; Leibniz Universitat Hannover, Germany ; Wolf Siberski ; Wolf-Tilo Balke ; Wolfgang Nejdl

Distributed hash tables (DHTs) are very efficient for querying based on key lookups, if only a small number of keys has to be registered by each individual peer. However, building huge term indexes, as required for IR-style keyword search, are impractical with plain DHTs. Due to the large sizes of document term vocabularies, joining peers cause huge amounts of key inserts, and subsequently large numbers of index maintenance messages. Thus, the key to exploiting DHTs for distributed information retrieval is to reduce index maintenance. We show that this can be achieved by combining DHTs with peer clustering. Peers are first clustered into communities, each of the communities having a representative super-peer. Then all occurrences of a term in a community are published to the global DHT in a batch by the representative super-peer. Our evaluation shows that this reduces index maintenance cost by an order of magnitude, while still keeping a complete and correct term index for query processing.

Published in:

21st International Conference on Advanced Information Networking and Applications (AINA '07)

Date of Conference:

21-23 May 2007