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Ternary Bloom Filter Replacing Counting Bloom Filter

IEEE Communications Letters, 2017
A counting Bloom filter (CBF) is commonly used in many applications for the membership queries of dynamic data since the CBF can provide delete operations. A CBF uses an array of $c$ -bit counters. The $c$ should be large enough to avoid overflows.
Hyesook Lim   +3 more
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Ternary Bloom filter replacing counting Bloom filter

2016 IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia), 2016
A counting Bloom filter (CBF) generalizes a standard 1-bit vector Bloom filter and allows not only membership queries but also insertion and deletion operations for dynamic sets. However, the CBF can cause false negatives because of counter overflows. A 4-bit vector CBF, which provides the probability of false negatives sufficiently small, is generally
Hayoung Byun, Jungwon Lee, Hyesook Lim
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Compressed Bloom filters

IEEE/ACM Transactions on Networking, 2001
A Bloom filter is a simple space-efficient randomized data structure for representing a set in order to support membership queries. Although Bloom filters allow false positives, for many applications the space savings outweigh this draw-back when the probability of an error is sufficiently low.
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Beyond bloom filters

ACM SIGCOMM Computer Communication Review, 2006
Many networking applications require fast state lookups in a concurrent state machine,which tracks the state of a large number of flows simultaneously.We consider the question of how to compactly represent such concurrent state machines. To achieve compactness,we consider data structures for Approximate Concurrent State Machines (ACSMs)that can return ...
Flavio Bonomi   +4 more
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Incremental Bloom Filters

2008 Proceedings IEEE INFOCOM - The 27th Conference on Computer Communications, 2008
A bloom filter is a randomized data structure for performing approximate membership queries. It is being increasingly used in networking applications ranging from security to routing in peer to peer networks. In order to meet a given false positive rate, the amount of memory required by a bloom filter is a function of the number of elements in the set.
F. Hao, M. Kodialam, T. V. Lakshman
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Spectral bloom filters

Proceedings of the 2003 ACM SIGMOD international conference on Management of data, 2003
A Bloom Filter is a space-efficient randomized data structure allowing membership queries over sets with certain allowable errors. It is widely used in many applications which take advantage of its ability to compactly represent a set, and filter out effectively any element that does not belong to the set, with small error probability.
Saar Cohen, Yossi Matias
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Multiple Bloom filters

Proceedings of the 2017 VI International Conference on Network, Communication and Computing, 2017
A standard technique from the cryptanalysis is to use exhaustive search that consists of systematically enumerating all possible candidates for the solution and checking whether each candidate satisfies the hash value. But this will take a lot of storage space and the time spent on query will be very long.
Yuanhang Yang, Shuhui Chen
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Persistent Bloom Filter

Proceedings of the 2018 International Conference on Management of Data, 2018
Membership testing is the problem of testing whether an element is in a set of elements. Performing the test exactly is expensive space-wise, requiring the storage of all elements in a set. In many applications, an approximate testing that can be done quickly using small space is often desired.
Yanqing Peng   +4 more
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Compacted Bloom Filter

2016 IEEE 2nd International Conference on Collaboration and Internet Computing (CIC), 2016
A Bloom filter is a space-efficient probabilistic data structure that is used in many domains including networking applications to test for set memberships. Such applications often require sending Bloom filters using messages. Consequently, it is important to minimize the size of the filters such that the storage, transmission, and processing costs are
Negar Mosharraf   +2 more
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Weighted Bloom Filter

2006 IEEE International Symposium on Information Theory, 2006
A Bloom filter is a simple randomized data structure that answers membership query with no false negative and a small false positive probability. It is an elegant data compression technique for membership information and has broad applications. In this paper, we generalize the traditional Bloom filter to Weighted Bloom Filter, which incorporates the ...
Jehoshua Bruck, Jie Gao, Anxiao Jiang
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