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Optimal Bloom Filters and Adaptive Merging for LSM-Trees
ACM Transactions on Database Systems, 2018In this article, we show that key-value stores backed by a log-structured merge-tree (LSM-tree) exhibit an intrinsic tradeoff between lookup cost, update cost, and main memory footprint, yet all existing designs expose a suboptimal and difficult to tune ...
Stratos Idreos, Manos Athanassoulis
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Ternary Bloom Filter Replacing Counting Bloom Filter
IEEE Communications Letters, 2017A 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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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.
Fang Hao +2 more
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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.
Fang Hao +2 more
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2019 International Conference on Electronics, Information, and Communication (ICEIC), 2019
A membership identification is a key functionality in many network applications. Various data structures have been introduced in order to support the efficient membership identification. Since a Bloom filter can provide simple but efficient membership checking, it is widely used in many network applications.
Ju Hyoung Mun, Hyesook Lim
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A membership identification is a key functionality in many network applications. Various data structures have been introduced in order to support the efficient membership identification. Since a Bloom filter can provide simple but efficient membership checking, it is widely used in many network applications.
Ju Hyoung Mun, Hyesook Lim
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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 +2 more
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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 +2 more
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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 0002, Yossi Matias
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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 0002, Yossi Matias
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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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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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Securing Bloom Filters for Privacy-preserving Record Linkage
International Conference on Information and Knowledge Management, 2020Privacy-preserving record linkage (PPRL) facilitates the matching of records that correspond to the same real-world entities across different databases while preserving the privacy of the individuals in these databases.
Thilina Ranbaduge, Rainer Schnell
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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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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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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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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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