Single-server Queue Asymptotics

Single-Server Queue Asymptotics is a theoretical framework within queueing theory that characterizes the limiting behavior of performance metrics in single-server queues under asymptotic regimes, particularly as system load approaches capacity, distinguishing it from multi-server or finite-capacity asymptotic analyses.

178

Publications

6.9K

Citations

218

Authors

137

Institutions

Publications per year

2017–2026

18

Authors

218

  1. AJ
    Austin J. Lemoine

    Systems Control (United States), United States

    8 publications · 214 citations

    8

    h-index

  2. LT
    Lajos Takács

    Case Western Reserve University, United States

    7 publications · 139 citations

    7

    h-index

  3. WW
    Ward Whitt

    AT&T (United States), United States

    6 publications · 621 citations

    6

    h-index

  4. OB
    Onno Boxma

    Eindhoven University of Technology, Netherlands

    5 publications · 206 citations

    5

    h-index

  5. SK
    Sarat Kumar Acharya

    Sambalpur University, India

    5 publications · 91 citations

    5

    h-index

1–5 of 218

Venues

  1. Journal of Applied Probability

    JAP · 25 publications · 890 citations

    17

    h-index

  2. Queueing Systems

    20 publications · 711 citations

    17

    h-index

  3. Operations Research

    10 publications · 430 citations

    10

    h-index

  4. Advances in Applied Probability

    AAP · 9 publications · 293 citations

    9

    h-index

  5. The Annals of Applied Probability

    7 publications · 266 citations

    7

    h-index

1–5