Partition Optimization

Partition Optimization is a methodological framework within data partitioning that systematically enhances the efficiency, scalability, and performance of distributed data processing by determining optimal criteria and configurations for dividing datasets into subsets according to specific computational and storage objectives.

207

Publications

9.4K

Citations

618

Authors

293

Institutions

Publications per year

2017–2026

60

Authors

618

  1. YZ
    Yanchun Zhang

    Victoria University, Australia

    3 publications · 98 citations

    3

    h-index

  2. GK
    George Karypis

    University of Minnesota, United States

    3 publications · 849 citations

    3

    h-index

  3. SM
    Scott Mahlke

    University of Michigan, United States

    3 publications · 132 citations

    3

    h-index

  4. DD
    Dong Deng

    Tsinghua University, China

    3 publications · 228 citations

    3

    h-index

  5. JW
    Jiannan Wang

    Tsinghua University, China

    3 publications · 242 citations

    3

    h-index

1–5 of 618

Venues

  1. Proceedings of the VLDB Endowment

    PVLDB · 6 publications · 522 citations

    6

    h-index

  2. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 5 publications · 274 citations

    5

    h-index

  3. Information Sciences

    4 publications · 68 citations

    4

    h-index

  4. Future Generation Computer Systems

    FGCS · 3 publications · 115 citations

    3

    h-index

  5. IEEE Transactions on Software Engineering

    TSE · 3 publications · 184 citations

    3

    h-index

1–5