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Expandable Bloom filter enquiring method and element inserting method thereof

A query method and filter technology, applied in the field of extensible Bloom filter query method and its element insertion, can solve the problems of high query time complexity, limited mitigation, and rapid growth rate of misjudgment rate

Inactive Publication Date: 2009-05-13
HUNAN UNIV
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  • Summary
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  • Claims
  • Application Information

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Problems solved by technology

However, when this method of linearly expanding vectors is actually used, as the number of elements increases, the number of vectors increases rapidly, the false positive rate increases rapidly, and the degree of relief is limited.
At the same time, the query time complexity of such methods is high, and there is still room for improvement in the query time complexity

Method used

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  • Expandable Bloom filter enquiring method and element inserting method thereof
  • Expandable Bloom filter enquiring method and element inserting method thereof
  • Expandable Bloom filter enquiring method and element inserting method thereof

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Embodiment Construction

[0130] This embodiment provides a H-based 3 Extensible Bloom filter implemented by hash function, in which H 3 Hash function is a kind of universal hash function (universal Hash) defined by Carter and Wegman. h 3 The function has a strong hash property and is a common implementation function of Bloom filter; and because the hash calculation of each input element only requires simple "AND" and "XOR" operations, it is convenient Implementations, especially hardware implementations, are among the most commonly used hash functions for computer hardware.

[0131] h 3 A hash function is a linear transformation B T =Q r×w A T , the element A=a of w-bit length 1 a 2 L a w Hash address converted to r-bit B=b 1 b 2 L b r ,Right now

[0132] b 1 b 2 ...

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Abstract

The invention discloses an inquiring method of scalable Bloom filter and element inserting method of the inquiring method of scalable Bloom filter, which is characterized by the following: adding filter with length increased times by times to keep low error judging rate under data set element increasing condition; controlling the error judging rate at 1%; obtaining the one-time element inquiring time at 20us in the CPU machine at 3.0GHz with faster speed than DBF inquiry; possessing widely applying prospect due to supporting dynamic expansion of set.

Description

technical field [0001] The invention relates to the technical field of distributed computing, in particular to an application in which a large amount of data is generated by a distributed system and requires interactive query, and specifically relates to an extensible Bloom filter query method and an element insertion method thereof. Background technique [0002] With the rapid development of computing technology and the Internet, the amount of data continues to increase, the heterogeneity and complexity of the network continue to increase, and the increasingly diverse and complex computer environment requires multiple levels of form, scale, function and performance. Conduct scalability research on computing systems. The scalability of storage systems is a hotspot in current computer research. The Bloom filter uses a bit string to represent the data set and can effectively support the hash lookup of the elements. It is a concise data structure that can represent the set and...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30
Inventor 谢鲲闵应骅张大方文吉刚谢高岗
Owner HUNAN UNIV
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