NDLI: MultiLayer Compressed Counting Bloom Filters

Content Provider	IEEE Xplore Digital Library
Author	Ficara, D. Giordano, S. Procissi, G. Vitucci, F.
Copyright Year	2008
Description	Author affiliation: Dept. of Inf. Eng., Pisa Univ., Pisa (Ficara, D.; Giordano, S.; Procissi, G.; Vitucci, F.)
Abstract	Bloom filters are efficient randomized data structures for membership queries on a set with a certain known false positive probability. Counting bloom filters (CBFs) allow the same operation on dynamic sets that can be updated via insertions and deletions with larger memory requirements. This paper first presents a new upper bound for counters overflow probability in CBFs. This bound is much tighter than that usually adopted in literature and it allows for designing more efficient CBFs. Three novel data structures are proposed, which introduce the idea of a hierarchical structure as well as the use of Huffman code. Our algorithms improve standard CBFs in terms of fast access and limited memory consumption (up to 50% of memory saving): the target could be the implementation of the compressed data structures in the small (but fast) local memory or "on-chip SRAM" of devices such as network processors .
Starting Page	311
Ending Page	315
File Size	292038
Page Count	5
File Format	PDF
ISBN	9781424420254
ISSN	0743166X
DOI	10.1109/INFOCOM.2008.71
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-04-13
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Nonhomogeneous media Data structures Counting circuits Information filtering Information filters Upper bound Network-on-a-chip Random access memory Huffman coding Communications Society
Content Type	Text
Resource Type	Article
Subject	Computer Science Electrical and Electronic Engineering

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