IDEAS home Printed from https://ideas.repec.org/a/inm/oropre/v42y1994i1p119-136.html
   My bibliography  Save this article

Sequential Bottleneck Decomposition: An Approximation Method for Generalized Jackson Networks

Author

Listed:
  • J. G. Dai

    (Georgia Institute of Technology, Atlanta, Georgia)

  • Viên Nguyen

    (Massachusetts Institute of Technology, Cambridge, Massachusetts)

  • Martin I. Reiman

    (AT&T Bell Laboratories, Murray Hill, New Jersey)

Abstract

In heavy traffic analysis of open queueing networks, processes of interest such as queue lengths and workload levels are generally approximated by a multidimensional reflected Brownian motion (RBM). Decomposition approximations, on the other hand, typically analyze stations in the network separately, treating each as a single queue with adjusted interarrival time distribution. We present a hybrid method for analyzing generalized Jackson networks that employs both decomposition approximation and heavy traffic theory: Stations in the network are partitioned into groups of “bottleneck subnetworks” that may have more than one station; the subnetworks then are analyzed “sequentially” with heavy traffic theory. Using the numerical method of J. G. Dai and J. M. Harrison for computing the stationary distribution of multidimensional RBMs, we compare the performance of this technique to other methods of approximation via some simulation studies. Our results suggest that this hybrid method generally performs better than other approximation techniques, including W. Whitt's QNA and J. M. Harrison and V. Nguyen's QNET.

Suggested Citation

  • J. G. Dai & Viên Nguyen & Martin I. Reiman, 1994. "Sequential Bottleneck Decomposition: An Approximation Method for Generalized Jackson Networks," Operations Research, INFORMS, vol. 42(1), pages 119-136, February.
    • Handle: RePEc:inm:oropre:v:42:y:1994:i:1:p:119-136
    DOI: 10.1287/opre.42.1.119
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/opre.42.1.119
    Download Restriction: no
    File URL: https://libkey.io/10.1287/opre.42.1.119?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ward Whitt & Wei You, 2022. "New decomposition approximations for queueing networks," Queueing Systems: Theory and Applications, Springer, vol. 100(3), pages 365-367, April.
    2. Ward Whitt & Wei You, 2020. "Heavy-traffic limits for stationary network flows," Queueing Systems: Theory and Applications, Springer, vol. 95(1), pages 53-68, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:oropre:v:42:y:1994:i:1:p:119-136. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.