Concepedia

Data-intensive Scheduling

Data-Intensive Scheduling is a scheduling paradigm that orchestrates computational tasks with primary emphasis on minimizing data movement and maximizing data locality, particularly in environments where the volume, velocity, and variability of data significantly influence scheduling decisions.

101

Publications

4K

Citations

313

Authors

158

Institutions

Publications per year

2017–2026

24

Parents

Publications

101

Efficient coflow scheduling with Varys

Mosharaf Chowdhury, Yuan Zhong, Ion Stoica · 2014 · 432 citations · Full text

, , +17

Task scheduling strategies for workflow-based applications in grids

James M. Blythe, Shweta Jain, Ewa Deelman et al. · 2005 · 366 citations

, , +17

Reservation-based Scheduling

Carlo Curino, Djellel Difallah, Chris Douglas et al. · 2014 · 133 citations

, , +13

Scheduling Data-IntensiveWorkflows onto Storage-Constrained Distributed Resources

Arun Ramakrishnan, Gurmeet Singh, Henan Zhao et al. · 2007 · 129 citations

, , +17

DLJSF: Data-Locality Aware Job Scheduling IoT tasks in fog-cloud computing environments

Edris Khezri, Rebaz Othman Yahya, Hiwa Hassanzadeh et al. · Results in Engineering · 2024 · 110 citations · Full text

, , +17

1–5 of 101

Authors

313

  1. ED
    Ewa Deelman

    University of Southern California, United States

    5 publications · 596 citations

    5

    h-index

  2. KW
    Kun Wang

    Nanjing University of Posts and Telecommunications, China

    3 publications · 108 citations

    3

    h-index

  3. KV
    Karan Vahi

    University of Southern California, United States

    3 publications · 535 citations

    3

    h-index

  4. ÜV
    Ümit V. Çatalyürek

    The Ohio State University, United States

    3 publications · 111 citations

    3

    h-index

  5. QZ
    Qihua Zhou

    Hong Kong Polytechnic University, Hong Kong SAR China

    3 publications · 108 citations

    3

    h-index

1–5 of 313

Institutions

158

  1. The Ohio State University

    Columbus, United States

    5 h-index

    15 publications

    399 citations

  2. Shanghai Jiao Tong University

    Shanghai, China

    4 h-index

    11 publications

    265 citations

  3. Microsoft (United States)

    Redmond, United States

    3 h-index

    12 publications

    931 citations

  4. Louisiana State University

    Baton Rouge, United States

    3 h-index

    4 publications

    111 citations

  5. California Institute of Technology

    Pasadena, United States

    3 h-index

    10 publications

    704 citations

  6. Hong Kong Polytechnic University

    Hong Kong, Hong Kong

    3 h-index

    4 publications

    136 citations

  7. The University of Sydney

    Sydney, Australia

    3 h-index

    5 publications

    206 citations

  8. University at Buffalo, State University of New York

    Buffalo, United States

    3 h-index

    8 publications

    210 citations

1–8 of 158

Venues

  1. Future Generation Computer Systems

    FGCS · 5 publications · 251 citations

    5

    h-index

  2. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 3 publications · 90 citations

    3

    h-index

  3. 3

    h-index

  4. Journal of Grid Computing

    3 publications · 143 citations

    3

    h-index

  5. The Computer Journal

    2 publications · 36 citations

    2

    h-index

1–5