Scalable Bloom Filters

• Tipo: Artigo em Revista Científica Internacional
• Data: 2007

Autores

Almeida, PS (Autor) Outra; Baquero, C (Autor) Outra; Preguica, N (Autor) Outra; Hutchison, D (Autor) Outra

Revista

Título: Information Processing Letters

Vol. 101

Páginas: 255-261

ISSN: 0020-0190

Editora: Elsevier

Indexação

ISI Web of Knowledge - 136 Citações

Scopus - 181 Citações

Outras Informações

ID Authenticus: P-004-B3N

DOI: 10.1016/j.ipl.2006.10.007

Abstract (EN): 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 7