Identifying frequent items in P2P systems

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Scopus citations

Abstract

As peer-to-peer (P2P) systems receive growing acceptance, the need of identifying 'frequent items' in such systems appears in a variety of applications. In this paper, we define the problem of identifying frequent items (IFI) and propose an efficient in-network processing technique, called in-network filtering (netFilter), to address this important fundamental problem. netFilter operates in two phases: 1) candidate filtering: data items are grouped into item groups to obtain aggregates for pruning of infrequent items; and 2) candidate verification: the aggregates for the remaining candidate items are obtained to filter out false frequent items. We address various issues faced in realizing netFilter, including aggregate computation, candidate set optimization, and candidate set materialization. In addition, we analyze the performance of netFilter, derive the optimal setting analytically, and discuss how to achieve the optimal setting in practice. Finally, we validate the effectiveness of netFilter through extensive simulation.

Original languageEnglish (US)
Title of host publicationProceedings - The 28th International Conference on Distributed Computing Systems, ICDCS 2008
Pages36-44
Number of pages9
DOIs
StatePublished - Sep 22 2008
Event28th International Conference on Distributed Computing Systems, ICDCS 2008 - Beijing, China
Duration: Jul 17 2008Jul 20 2008

Publication series

NameProceedings - The 28th International Conference on Distributed Computing Systems, ICDCS 2008

Other

Other28th International Conference on Distributed Computing Systems, ICDCS 2008
Country/TerritoryChina
CityBeijing
Period7/17/087/20/08

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Software

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