Queueing Network Approximation

Queueing Network Approximation is a mathematical modeling technique that distinguishes itself by simplifying complex queueing network systems through analytical or computational methods to estimate performance metrics such as throughput, latency, and congestion, while preserving essential structural and stochastic characteristics of the original system.

437

Publications

19.9K

Citations

640

Authors

289

Institutions

Publications per year

2017–2026

28

Variants

Queuing Network Approximation

Authors

640

  1. HG
    Harry G. Perros

    North Carolina State University, United States

    20 publications · 1K citations

    15

    h-index

  2. WW
    Ward Whitt

    AT&T (United States), United States

    11 publications · 736 citations

    11

    h-index

  3. GC
    Giuliano Casale

    Imperial College London, United Kingdom

    10 publications · 185 citations

    10

    h-index

  4. KM
    K. Mani Chandy

    The University of Texas at Austin, United States

    9 publications · 557 citations

    9

    h-index

  5. HC
    Hong Chen

    China University of Mining and Technology, China

    8 publications · 615 citations

    9

    h-index

1–5 of 640

Venues

  1. Operations Research

    22 publications · 2K citations

    18

    h-index

  2. Performance Evaluation

    27 publications · 860 citations

    17

    h-index

  3. ACM SIGMETRICS Performance Evaluation Review

    PER · 22 publications · 674 citations

    14

    h-index

  4. Queueing Systems

    12 publications · 504 citations

    14

    h-index

  5. IEEE Transactions on Computers

    15 publications · 846 citations

    14

    h-index

1–5