Workload Process Approximation

Workload Process Approximation is a stochastic process model in queueing theory that approximates the evolution of system workload under heavy-traffic conditions by diffusive scaling, distinguishing itself through its focus on aggregate service demand as a unified measure of congestion dynamics.

8

Publications

237

Citations

17

Authors

13

Institutions

Publications per year

2017–2026

1

Authors

17

  1. RW
    Ruth Williams

    University of California San Diego, United States

    3 publications · 95 citations

    3

    h-index

  2. WN
    W. N. Kang

    University of California San Diego, United States

    2 publications · 76 citations

    2

    h-index

  3. KS
    Karl Sigman

    Columbia University, United States

    1 publications · 56 citations

    1

    h-index

  4. KD
    Krzysztof Dȩbicki

    University of Wrocław, Poland

    1 publications · 19 citations

    1

    h-index

  5. FP
    F. P. Kelly

    University of Cambridge, United Kingdom

    1 publications · 29 citations

    1

    h-index

1–5 of 17

Venues

  1. Queueing Systems

    1 publications · 19 citations

    1

    h-index

  2. The Annals of Applied Probability

    1 publications · 14 citations

    1

    h-index

  3. Management Science

    1 publications · 17 citations

    1

    h-index

  4. 1

    h-index

  5. Stochastic Systems

    1 publications · 47 citations

    1

    h-index

1–5