By Topic

Enhancing Counting Bloom Filters Through Huffman-Coded Multilayer Structures

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Ficara, D. ; Dipt. di Ing. dell''Inf., Univ. di Pisa, Pisa, Italy ; Di Pietro, A. ; Giordano, S. ; Procissi, G.
more authors

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 simple tight upper bound for counters overflow probability in CBFs, which is adopted in the design of more efficient CBFs. On the basis of such theoretical achievements, we introduce the idea of a hierarchical structure as well as the use of Huffman code to 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. As an application of our algorithms, an anti-evasion system is finally proposed.

Published in:

Networking, IEEE/ACM Transactions on  (Volume:18 ,  Issue: 6 )