Variable-size Chunking

Variable-Size Chunking is a data segmentation method in which input data is divided into blocks of non-uniform length based on dynamic, content-dependent boundaries, typically determined by rolling hash functions or other content-aware algorithms, to improve redundancy detection in data deduplication systems.

21

Publications

803

Citations

62

Authors

30

Institutions

Publications per year

2017–2026

8

Authors

62

  1. CQ
    Chuan Qin

    University of Shanghai for Science and Technology, China

    2 publications · 62 citations

    2

    h-index

  2. CD
    Cezary Dubnicki

    Princeton University, United States

    2 publications · 156 citations

    2

    h-index

  3. SW
    Shinji Watanabe

    Johns Hopkins University, United States

    2 publications · 48 citations

    2

    h-index

  4. XZ
    Xiaosong Zhang

    University of Electronic Science and Technology of China, China

    2 publications · 62 citations

    2

    h-index

  5. YX
    Yawen Xue

    Johns Hopkins University, United States

    2 publications · 48 citations

    2

    h-index

1–5 of 62

Venues

  1. Cognition

    1 publications · 273 citations

    1

    h-index

  2. arXiv (Cornell University)

    Repository · 1 publications · 10 citations

    1

    h-index

  3. IEEE Transactions on Computers

    1 publications · 18 citations

    1

    h-index

  4. 1

    h-index

  5. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 1 publications · 22 citations

    1

    h-index

1–5