Ark Filter: A General and Space-Efficient Sketch for Network Flow Analysis Article Swipe
Lailong Luo
,
Pengtao Fu
,
Shangsen Li
,
Deke Guo
,
Qianzhen Zhang
,
Huaimin Wang
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1109/tnet.2023.3263839
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1109/tnet.2023.3263839
Sketches are widely deployed to represent network flows to support complex flow analysis. Typical sketches usually employ hash functions to map elements into a hash table or bit array. Such sketches still suffer from potential weaknesses upon throughput, flexibility, and functionality. To this end, we propose Ark filter, a novel sketch that stores the element information with either of two candidate buckets indexed by the quotient or remainder between the fingerprint and filter length. In this way, no further hash calculations are required for future queries or reallocations. We further extend the Ark filter to enable capacity elasticity and more functionalities (such as frequency estimation and top- query). Comprehensive experiments demonstrate that, compared with Cuckoo filter, Ark filter has , , and throughput of deletion, insertion, and hybrid query, respectively; compared with Quotient filter, Ark filter has , , and throughput of deletion, insertion, and hybrid query, respectively; compared with Bloom filter, Ark filter has and throughput of insertion and hybrid query, respectively.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/tnet.2023.3263839
- https://ieeexplore.ieee.org/ielx7/90/4359146/10102434.pdf
- OA Status
- hybrid
- Cited By
- 6
- References
- 47
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4365799142
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4365799142Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/tnet.2023.3263839Digital Object Identifier
- Title
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Ark Filter: A General and Space-Efficient Sketch for Network Flow AnalysisWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-04-13Full publication date if available
- Authors
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Lailong Luo, Pengtao Fu, Shangsen Li, Deke Guo, Qianzhen Zhang, Huaimin WangList of authors in order
- Landing page
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https://doi.org/10.1109/tnet.2023.3263839Publisher landing page
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https://ieeexplore.ieee.org/ielx7/90/4359146/10102434.pdfDirect link to full text PDF
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://ieeexplore.ieee.org/ielx7/90/4359146/10102434.pdfDirect OA link when available
- Concepts
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Hash function, Quotient, Computer science, Sketch, Filter (signal processing), Notation, Algorithm, Theoretical computer science, Mathematics, Discrete mathematics, Arithmetic, Combinatorics, Programming language, Computer visionTop concepts (fields/topics) attached by OpenAlex
- Cited by
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6Total citation count in OpenAlex
- Citations by year (recent)
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2025: 3, 2024: 2, 2023: 1Per-year citation counts (last 5 years)
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47Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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