Scalable Bloom Filters

• Type: Article in International Scientific Journal
• Date: 2007

Authors

Almeida, PS (Author) Other; Baquero, C (Author) Other; Preguica, N (Author) Other; Hutchison, D (Author) Other

Journal

Title: Information Processing Letters

Vol. 101

Pages: 255-261

ISSN: 0020-0190

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 136 Citations

Scopus - 181 Citations

Other information

Authenticus ID: 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 7