Locality-aware Scheduling

Locality-Aware Scheduling is a task scheduling methodology that optimizes data access efficiency by prioritizing the assignment of computational tasks to processing units in proximity to their required data, thereby minimizing data movement and leveraging spatial and temporal locality in distributed computing environments.

252

Publications

16.3K

Citations

779

Authors

305

Institutions

Publications per year

2017–2026

67

Authors

779

  1. JT
    Jian Tan

    IBM (United States), United States

    6 publications · 421 citations

    6

    h-index

  2. LY
    Lei Ying

    Arizona State University, United States

    6 publications · 303 citations

    6

    h-index

  3. LZ
    Li Zhang

    IBM (United States), United States

    6 publications · 421 citations

    6

    h-index

  4. WW
    Weina Wang

    Arizona State University, United States

    6 publications · 303 citations

    6

    h-index

  5. ZT
    Zhuo Tang

    Hunan University, China

    5 publications · 139 citations

    5

    h-index

1–5 of 779

Venues

  1. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 9 publications · 358 citations

    9

    h-index

  2. Future Generation Computer Systems

    FGCS · 6 publications · 271 citations

    6

    h-index

  3. IEEE Transactions on Cloud Computing

    6 publications · 233 citations

    6

    h-index

  4. 5

    h-index

  5. IEEE Transactions on Computers

    3 publications · 86 citations

    3

    h-index

1–5