Content-defined Chunking
Content-Defined Chunking is a data segmentation method that partitions a data stream into variable-sized blocks based on locally computed content fingerprints, ensuring that identical content segments align across different instances, thereby enabling efficient data deduplication and reducing storage redundancy in content-addressable storage systems.
21
Publications
1.2K
Citations
59
Authors
26
Institutions
Publications per year
2017–2026
11
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1–5 of 21
59
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The University of Texas at Arlington
Arlington, United States
6 h-index
6 publications
287 citations

Huazhong University of Science and Technology
Wuhan, China
6 h-index
27 publications
1.8K citations

Harbin Institute of Technology
Harbin, China
2 h-index
5 publications
277 citations

South China University of Technology
Guangzhou, China
2 h-index
11 publications
142 citations
Wuhan National Laboratory for Optoelectronics
Wuhan, China
2 h-index
7 publications
449 citations
Peng Cheng Laboratory
Shenzhen, China
2 h-index
6 publications
318 citations
NetApp (United States)
Sunnyvale, United States
2 h-index
3 publications
70 citations
Shenzhen Institutes of Advanced Technology
Shenzhen, China
1 h-index
1 publications
11 citations
1–8 of 26
FGCS · 2 publications · 104 citations
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2 publications · 25 citations
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1 publications · 16 citations
1
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1 publications · 64 citations
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Conference · 1 publications · 123 citations
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1–5