File-level Deduplication
File-Level Deduplication is a data deduplication technique that eliminates redundant data by identifying and storing only one unique instance of entire files, distinguishing itself from block-level or byte-level methods by operating at the complete file granularity.
33
Publications
1.8K
Citations
107
Authors
45
Institutions
Publications per year
2017–2026
16
33
A Comprehensive Study of the Past, Present, and Future of Data Deduplication
Wen Xia, Hong Jiang, Dan Feng et al. · Proceedings of the IEEE · 2016 · 308 citations
MAD2: A scalable high-throughput exact deduplication approach for network backup services
Jiansheng Wei, Hong Jiang, Ke Zhou et al. · 2010 · 89 citations
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45

Huazhong University of Science and Technology
Wuhan, China
9 h-index
32 publications
3.5K citations
Wuhan National Laboratory for Optoelectronics
Wuhan, China
7 h-index
23 publications
3K citations
Virginia Tech
Blacksburg, United States
5 h-index
17 publications
605 citations
University of Nebraska–Lincoln
Lincoln, United States
5 h-index
8 publications
625 citations
IBM Research - Almaden
San Jose, United States
3 h-index
13 publications
487 citations

Xidian University
Xi'an, China
3 h-index
9 publications
287 citations

Barcelona Supercomputing Center
Barcelona, Spain
2 h-index
2 publications
184 citations
The University of Texas at Arlington
Arlington, United States
2 h-index
2 publications
352 citations
1–8 of 45
2 publications · 80 citations
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1 publications · 308 citations
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Conference · 1 publications · 95 citations
1
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Repository · 1 publications · 89 citations
1
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1 publications · 11 citations
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