Task Scheduling Performance Models

Task Scheduling Performance Models is a formal analytical framework that characterizes the efficiency and effectiveness of task scheduling strategies in computational systems by modeling performance metrics such as execution time, resource utilization, and throughput under varying workload conditions.

59

Publications

2.1K

Citations

152

Authors

82

Institutions

Publications per year

2017–2026

5

Authors

152

  1. HD
    Helen D. Karatza

    Aristotle University of Thessaloniki, Greece

    4 publications · 78 citations

    4

    h-index

  2. HJ
    Howard Jay Siegel

    Colorado State University, United States

    3 publications · 106 citations

    3

    h-index

  3. WC
    Walfredo Cirne

    Universidade Federal de Campina Grande, Brazil

    2 publications · 225 citations

    2

    h-index

  4. FB
    Fran Berman

    University of California San Diego, United States

    2 publications · 225 citations

    2

    h-index

  5. WZ
    Wei Zhang

    Nanjing University of Science and Technology, China

    2 publications · 72 citations

    2

    h-index

1–5 of 152

Venues

  1. SIAM Journal on Computing

    2 publications · 179 citations

    2

    h-index

  2. Journal of Parallel and Distributed Computing

    2 publications · 118 citations

    2

    h-index

  3. Simulation Modelling Practice and Theory

    2 publications · 51 citations

    2

    h-index

  4. ACM SIGMETRICS Performance Evaluation Review

    PER · 2 publications · 26 citations

    2

    h-index

  5. The Journal of Supercomputing

    1 publications · 19 citations

    1

    h-index

1–5