Data Locality Scheduling

Data Locality Scheduling is a distributed scheduling strategy that minimizes data transfer overhead by prioritizing the assignment of computational tasks to processing nodes physically co-located with their required data.

99

Publications

7.8K

Citations

304

Authors

132

Institutions

Publications per year

2017–2026

21

Authors

304

  1. LY
    Lei Ying

    Arizona State University, United States

    5 publications · 230 citations

    5

    h-index

  2. WW
    Weina Wang

    Arizona State University, United States

    5 publications · 230 citations

    5

    h-index

  3. IM
    Ishai Menache

    Microsoft (United States), United States

    4 publications · 292 citations

    4

    h-index

  4. MZ
    Matei Zaharia

    Stanford University, United States

    3 publications · 3.3K citations

    3

    h-index

  5. LZ
    Li Zhang

    IBM (United States), United States

    3 publications · 254 citations

    3

    h-index

1–5 of 304

Venues

  1. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 4 publications · 142 citations

    4

    h-index

  2. IEEE Transactions on Cloud Computing

    3 publications · 99 citations

    3

    h-index

  3. arXiv (Cornell University)

    Repository · 3 publications · 61 citations

    3

    h-index

  4. IEEE Transactions on Services Computing

    2 publications · 57 citations

    2

    h-index

  5. IEEE/ACM Transactions on Networking

    TON · 2 publications · 201 citations

    2

    h-index

1–5