Flexible fingerprint cuckoo filter for information retrieval optimization in distributed network

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Publicat a:Distributed and Parallel Databases vol. 42, no. 3 (Sep 2024), p. 377
Autor principal: Lian, Wenhan
Altres autors: Wang, Jinlin, You, Jiali
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Springer Nature B.V.
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024 7 |a 10.1007/s10619-024-07440-w  |2 doi 
035 |a 3255420243 
045 2 |b d20240901  |b d20240930 
100 1 |a Lian, Wenhan  |u Institute of Acoustics, Chinese Academy of Sciences, National Network New Media Engineering Research Center, Beijing, China (GRID:grid.458455.d) (ISNI:0000 0004 0644 4702); University of Chinese Academy of Sciences, Beijing, China (GRID:grid.410726.6) (ISNI:0000 0004 1797 8419) 
245 1 |a Flexible fingerprint cuckoo filter for information retrieval optimization in distributed network 
260 |b Springer Nature B.V.  |c Sep 2024 
513 |a Journal Article 
520 3 |a In a large-scale distributed network, a naming service is used to achieve location transparency and provide effective content discovery. However, fast and accurate name retrieval in the massive name set is laborious. Approximate set membership data structures, such as Bloom filter and Cuckoo filter, are very popular in distributed information systems. They obtain high query performance and reduce memory requirements through the abstract representation of information, but at the cost of introducing query error rates, which will ultimately affect content service quality. In this paper, in order to obtain higher space utilization and a lower query false positive rate, we propose a flexible fingerprint cuckoo filter (FFCF) for information storage and retrieval, which can change the length and type of fingerprints adaptively. In our scheme, FFCF uses longer fingerprints under low occupancy and has the ability to correct errors by changing the type of stored fingerprints. Moreover, we give a theoretical proof and evaluate the performance of FFCF by experimental simulations with synthetic data sets and real network packets. The results demonstrate that FFCF can improve memory utilization, significantly reduce false positive errors by nearly 90%<inline-graphic specific-use="web" mime-subtype="GIF" xlink:href="10619_2024_7440_Article_IEq1.gif" /> at 50%<inline-graphic specific-use="web" mime-subtype="GIF" xlink:href="10619_2024_7440_Article_IEq2.gif" /> occupancy and outperform Cuckoo filter in the full range of occupancy. 
653 |a Names 
653 |a Packets (communication) 
653 |a Performance evaluation 
653 |a Information systems 
653 |a Information storage 
653 |a Queries 
653 |a Information retrieval 
653 |a Data structures 
653 |a Fingerprints 
653 |a Error reduction 
653 |a Retrieval performance measures 
653 |a Efficiency 
653 |a Synthetic data 
700 1 |a Wang, Jinlin  |u Institute of Acoustics, Chinese Academy of Sciences, National Network New Media Engineering Research Center, Beijing, China (GRID:grid.458455.d) (ISNI:0000 0004 0644 4702); University of Chinese Academy of Sciences, Beijing, China (GRID:grid.410726.6) (ISNI:0000 0004 1797 8419); Peng Cheng Lab, Shenzhen, China (GRID:grid.508161.b) (ISNI:0000 0005 0389 1328) 
700 1 |a You, Jiali  |u Institute of Acoustics, Chinese Academy of Sciences, National Network New Media Engineering Research Center, Beijing, China (GRID:grid.458455.d) (ISNI:0000 0004 0644 4702); University of Chinese Academy of Sciences, Beijing, China (GRID:grid.410726.6) (ISNI:0000 0004 1797 8419); Peng Cheng Lab, Shenzhen, China (GRID:grid.508161.b) (ISNI:0000 0005 0389 1328) 
773 0 |t Distributed and Parallel Databases  |g vol. 42, no. 3 (Sep 2024), p. 377 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3255420243/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch 
856 4 0 |3 Full Text  |u https://www.proquest.com/docview/3255420243/fulltext/embedded/L8HZQI7Z43R0LA5T?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3255420243/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch