Data Redundancy Reduction

Data Redundancy Reduction is a computational technique in content-addressable storage systems that eliminates duplicate or overlapping data representations by identifying and retaining only unique data segments, thereby optimizing storage efficiency and retrieval accuracy.

846

Publications

40.8K

Citations

2.8K

Authors

924

Institutions

Publications per year

2017–2026

300

Authors

2.8K

  1. PP
    Patrick P. C. Lee

    Chinese University of Hong Kong, Hong Kong SAR China

    11 publications · 503 citations

    11

    h-index

  2. HJ
    Hong Jiang

    University of Nebraska–Lincoln, United States

    8 publications · 336 citations

    8

    h-index

  3. ZS
    Zhirong Shen

    Tsinghua University, China

    6 publications · 104 citations

    6

    h-index

  4. KV
    K. V. Rashmi

    Carnegie Mellon University, United States

    6 publications · 630 citations

    6

    h-index

  5. SW
    Suzhen Wu

    Xiamen University, China

    5 publications · 183 citations

    5

    h-index

1–5 of 2.8K

Venues

  1. IEEE Access

    18 publications · 916 citations

    14

    h-index

  2. arXiv (Cornell University)

    Repository · 15 publications · 1.3K citations

    12

    h-index

  3. IEEE Transactions on Computers

    13 publications · 480 citations

    12

    h-index

  4. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 15 publications · 312 citations

    11

    h-index

  5. IEEE Transactions on Information Theory

    9 publications · 881 citations

    9

    h-index

1–5