Deduplication Performance Evaluation

Deduplication Performance Evaluation is a methodological framework within data management research that systematically assesses the efficiency, effectiveness, and scalability of deduplication techniques by quantifying their computational overhead, reduction ratio, and accuracy in eliminating redundant data instances.

96

Publications

4.5K

Citations

306

Authors

120

Institutions

Publications per year

2017–2026

35

Authors

306

  1. HJ
    Hong Jiang

    University of Nebraska–Lincoln, United States

    9 publications · 424 citations

    9

    h-index

  2. DF
    Dan Feng

    Huazhong University of Science and Technology, China

    6 publications · 339 citations

    6

    h-index

  3. AB
    André Brinkmann

    Johannes Gutenberg University Mainz, Germany

    5 publications · 236 citations

    5

    h-index

  4. JK
    Jürgen Kaiser

    Johannes Gutenberg University Mainz, Germany

    5 publications · 236 citations

    5

    h-index

  5. VT
    Vasily Tarasov

    IBM Research - Almaden, United States

    5 publications · 168 citations

    5

    h-index

1–5 of 306

Venues

  1. File and Storage Technologies

    Conference · 5 publications · 357 citations

    5

    h-index

  2. ACM Transactions on Storage

    TOS · 4 publications · 778 citations

    4

    h-index

  3. IEEE Transactions on Computers

    3 publications · 109 citations

    3

    h-index

  4. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 3 publications · 99 citations

    3

    h-index

  5. USENIX Annual Technical Conference

    Conference · 3 publications · 94 citations

    3

    h-index

1–5