Chunk Boundary Detection

Chunk Boundary Detection is a content-partitioning method in content-addressable storage systems that identifies optimal segmentation points within data streams by analyzing local content characteristics to ensure granularity alignment with object boundaries.

29

Publications

1.9K

Citations

91

Authors

50

Institutions

Publications per year

2017–2026

8

Authors

91

  1. LK
    Latifur Khan

    The University of Texas at Dallas, United States

    2 publications · 287 citations

    2

    h-index

  2. DW
    David W. Embley

    Brigham Young University, United States

    2 publications · 371 citations

    2

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  3. AH
    Ahsanul Haque

    The University of Texas at Dallas, United States

    2 publications · 287 citations

    2

    h-index

  4. PP
    Partha Pakray

    National Institute Of Technology Silchar, India

    2 publications · 20 citations

    2

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  5. DM
    Dipti Misra Sharma

    International Institute of Information Technology, Hyderabad, India

    2 publications · 58 citations

    2

    h-index

1–5 of 91

Venues

  1. IEEE Transactions on Computers

    2 publications · 85 citations

    2

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  2. 1

    h-index

  3. 1

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  4. Data & Knowledge Engineering

    DKE · 1 publications · 16 citations

    1

    h-index

  5. NeuroImage

    1 publications · 16 citations

    1

    h-index

1–5