IDEAS home Printed from https://ideas.repec.org/a/eee/spapps/v115y2005i5p849-873.html
   My bibliography  Save this article

Conditional limit theorems for queues with Gaussian input, a weak convergence approach

Author

Listed:
  • Dieker, A.B.

Abstract

We consider a buffered queueing system that is fed by a Gaussian source and drained at a constant rate. The fluid offered to the system in a time interval (0,t] is given by a separable continuous Gaussian process Y with stationary increments. The variance function of Y is assumed to be regularly varying with index 2H, for some 0 [infinity]. In addition, we study how a busy period longer than T typically occurs as T-->[infinity], and we find the logarithmic asymptotics for the probability of such a long busy period. The study relies on the weak convergence in an appropriate space of to a fractional Brownian motion with Hurst parameter H as [alpha]-->[infinity]. We prove this weak convergence under a fairly general condition on [sigma]2, sharpening recent results of Kozachenko et al. (Queueing Systems Theory Appl. 42 (2002) 113). The core of the proof consists of a new type of uniform convergence theorem for regularly varying functions with positive index.

Suggested Citation

  • Dieker, A.B., 2005. "Conditional limit theorems for queues with Gaussian input, a weak convergence approach," Stochastic Processes and their Applications, Elsevier, vol. 115(5), pages 849-873, May.
  • Handle: RePEc:eee:spapps:v:115:y:2005:i:5:p:849-873
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304-4149(04)00185-1
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Barbe, Ph. & McCormick, W.P., 2012. "Heavy-traffic approximations for fractionally integrated random walks in the domain of attraction of a non-Gaussian stable distribution," Stochastic Processes and their Applications, Elsevier, vol. 122(4), pages 1276-1303.
    2. Debicki, K. & Kosinski, K.M. & Mandjes, M. & Rolski, T., 2010. "Extremes of multidimensional Gaussian processes," Stochastic Processes and their Applications, Elsevier, vol. 120(12), pages 2289-2301, December.
    3. Mandjes, Michel & Mannersalo, Petteri & Norros, Ilkka & van Uitert, Miranda, 2006. "Large deviations of infinite intersections of events in Gaussian processes," Stochastic Processes and their Applications, Elsevier, vol. 116(9), pages 1269-1293, September.

    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:eee:spapps:v:115:y:2005:i:5:p:849-873. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/505572/description#description .

    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.