Counting with TinyTable: Every bit counts!

Gil Einziger, Roy Friedman

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Counting Bloom filters (CBF) and their variants are data structures that support membership or multiplicity queries with a low probabilistic error. Yet, they incur a significant memory space overhead when compared to lower bounds as well as to (plain) Bloom filters, which can only represent set membership without removals. This work presents TinyTable, an efficient hash table based construction that supports membership queries, multiplicity queries (statistics) and removals. TinyTable is more space efficient than existing alternatives, both those derived from Bloom filters and other hash table based schemes. In fact, when the required false positive rate is smaller than 1%, it is even more space efficient than (plain) Bloom filters.

Original languageEnglish
Title of host publication2015 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages77-78
Number of pages2
ISBN (Electronic)9781467371315
DOIs
StatePublished - 4 Aug 2015
Externally publishedYes
EventIEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2015 - Hong Kong, Hong Kong
Duration: 26 Apr 20151 May 2015

Publication series

NameProceedings - IEEE INFOCOM
Volume2015-August
ISSN (Print)0743-166X

Conference

ConferenceIEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2015
Country/TerritoryHong Kong
CityHong Kong
Period26/04/151/05/15

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