Bloom filter based on hash fingerprints

A filter and multi-dimensional sub-Bloom technology, applied in instruments, special data processing applications, electrical digital data processing, etc., can solve problems such as difficult hardware implementation, complex genetic algorithm solution, complex algorithm, etc.

Pending Publication Date: 2020-01-21
杉树岭网络科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0016] SBF and CBF algorithms are complex, simple and usable, and more difficult to implement in hardware than NCBF;
[0017] BBF tries to dynamically change the number of has

Method used

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  • Bloom filter based on hash fingerprints
  • Bloom filter based on hash fingerprints
  • Bloom filter based on hash fingerprints

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Embodiment Construction

[0057] In order to make the object, technical solution and advantages of the present invention clearer, the embodiments of the present invention will be further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0058] It should be noted that all the expressions using "first" and "second" in the embodiments of the present invention are to distinguish two entities with the same name but different parameters or parameters that are not the same. It can be seen that "first" and "second " is only for the convenience of expression, and should not be understood as a limitation to the embodiments of the present invention, and will not be described one by one in the subsequent embodiments.

[0059] Based on the above purpose, an embodiment of the present invention proposes a Bloom filter based on a hash fingerprint.

[0060] At first the elaboration of the Bloom filter (Bloom Filter) involved in the present invention is...

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Abstract

The invention discloses a Bloom filter based on a hash fingerprint. The Bloom filter based on the hash fingerprint is formed by the following steps: dividing the structure of a counting type Bloom filter into a plurality of sub-Bloom filters; dividing each dimensional sub-Bloom filter into a plurality of barrels again; and then introducing a hash fingerprint method to enable the storage unit of each bucket to be obtained through calculation of a corresponding hash function. According to the Bloom filter based on the hash fingerprint, concise storage and rapid query of set elements are achieved. The Bloom filter (HFBF) based on the hash fingerprint has relatively low error probability and calculation complexity, and meanwhile, relatively high space utilization rate can be maintained.

Description

technical field [0001] The present invention relates to a highly spatially multiplexed summary data structure Bloom filter, more specifically, a Bloom filter based on a hash fingerprint. Background technique [0002] With the continuous expansion of the scale of the Internet, the rapid expansion of the number of users, and the increasingly complex business environment, the scale of shared data has shown geometric growth, which has brought huge challenges to the storage, access, interaction, and management of network resources. How to quickly represent and query large-scale data, and effectively extract and store content summary information is the key to network and distributed system resource sharing, and has always been a research hotspot in domestic and foreign academic circles. [0003] Bloom Filter (Bloom Filter) is a highly spatially multiplexed synopsis data structure (SynopsisData Structure), which supports collection element representation and query, and is widely us...

Claims

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Application Information

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IPC IPC(8): G06F16/22G06F16/23G06F16/2455
CPCG06F16/2255G06F16/23G06F16/2455
Inventor 陈庶樵
Owner 杉树岭网络科技有限公司
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