Scalable bloom filters

Detalhes bibliográficos
Autor(a) principal: Baquero, Carlos
Data de Publicação: 2007
Outros Autores: Almeida, Paulo Sérgio, Preguiça, Nuno
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/1822/6627
Resumo: Bloom filters provide space-efficient storage of sets at the cost of a probability of false positives on membership queries. The size of the filter must be defined a priori based on the number of elements to store and the desired false positive probability, being impossible to store extra elements without increasing the false positive probability. This leads typically to a conservative assumption regarding maximum set size, possibly by orders of magnitude, and a consequent space waste. This paper proposes Scalable Bloom Filters, a variant of Bloom filters that can adapt dynamically to the number of elements stored, while assuring a maximum false positive probability.
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spelling Scalable bloom filtersData structuresBloom filtersDistributed systemsRandomized algorithmsScience & TechnologyBloom filters provide space-efficient storage of sets at the cost of a probability of false positives on membership queries. The size of the filter must be defined a priori based on the number of elements to store and the desired false positive probability, being impossible to store extra elements without increasing the false positive probability. This leads typically to a conservative assumption regarding maximum set size, possibly by orders of magnitude, and a consequent space waste. This paper proposes Scalable Bloom Filters, a variant of Bloom filters that can adapt dynamically to the number of elements stored, while assuring a maximum false positive probability.ElsevierUniversidade do MinhoBaquero, CarlosAlmeida, Paulo SérgioPreguiça, Nuno2007-032007-03-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/6627eng“Information processing letters”. ISSN 0020-0190.101:6 (Mar. 2007) 255-261.0020-019010.1016/j.ipl.2006.10.007info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:32:34Zoai:repositorium.sdum.uminho.pt:1822/6627Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:27:56.270646Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Scalable bloom filters
title Scalable bloom filters
spellingShingle Scalable bloom filters
Baquero, Carlos
Data structures
Bloom filters
Distributed systems
Randomized algorithms
Science & Technology
title_short Scalable bloom filters
title_full Scalable bloom filters
title_fullStr Scalable bloom filters
title_full_unstemmed Scalable bloom filters
title_sort Scalable bloom filters
author Baquero, Carlos
author_facet Baquero, Carlos
Almeida, Paulo Sérgio
Preguiça, Nuno
author_role author
author2 Almeida, Paulo Sérgio
Preguiça, Nuno
author2_role author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Baquero, Carlos
Almeida, Paulo Sérgio
Preguiça, Nuno
dc.subject.por.fl_str_mv Data structures
Bloom filters
Distributed systems
Randomized algorithms
Science & Technology
topic Data structures
Bloom filters
Distributed systems
Randomized algorithms
Science & Technology
description Bloom filters provide space-efficient storage of sets at the cost of a probability of false positives on membership queries. The size of the filter must be defined a priori based on the number of elements to store and the desired false positive probability, being impossible to store extra elements without increasing the false positive probability. This leads typically to a conservative assumption regarding maximum set size, possibly by orders of magnitude, and a consequent space waste. This paper proposes Scalable Bloom Filters, a variant of Bloom filters that can adapt dynamically to the number of elements stored, while assuring a maximum false positive probability.
publishDate 2007
dc.date.none.fl_str_mv 2007-03
2007-03-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1822/6627
url http://hdl.handle.net/1822/6627
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv “Information processing letters”. ISSN 0020-0190.101:6 (Mar. 2007) 255-261.
0020-0190
10.1016/j.ipl.2006.10.007
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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