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Scalable Bloom Filters

Almeida, Paulo Sérgio and Baquero, Carlos and Preguiça, Nuno and Hutchison, David (2007) Scalable Bloom Filters. Information Processing Letters, 101 (6). pp. 255-261. ISSN 1872-6119

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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.

Item Type: Journal Article
Journal or Publication Title: Information Processing Letters
Uncontrolled Keywords: Data structures ; Bloom filters ; Distributed systems ; Randomized algorithms
Subjects: ?? qa75 ??
Departments: Faculty of Science and Technology > School of Computing & Communications
ID Code: 57381
Deposited By: ep_importer_pure
Deposited On: 05 Oct 2012 11:33
Refereed?: Yes
Published?: Published
Last Modified: 19 Jun 2018 03:20
Identification Number:

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