IDEAS home Printed from https://ideas.repec.org/a/spr/metcap/v24y2022i3d10.1007_s11009-021-09903-4.html
   My bibliography  Save this article

Moments Computation for General Markov Fluid Models

Author

Listed:
  • Hédi Nabli

    (University of Sfax)

Abstract

This paper derives new algorithms for the computation of moments in general Markov fluid models. The first one is recursive: the nth moment is obtained from the preceding moment via a linear system. We show that these moments depend basically on buffer occupancy. Also, our approach proposes a unified code that does not distinguish between the case where the effective input rates matrix is invertible and the case where it is singular. The second algorithm is based on the matrix analytic method. These results are illustrated through numerical examples, where are considered server supporting multiple output rates. Keeping the traffic intensity constant, we study the impact of output rates management on the average fluid level.

Suggested Citation

  • Hédi Nabli, 2022. "Moments Computation for General Markov Fluid Models," Methodology and Computing in Applied Probability, Springer, vol. 24(3), pages 2055-2070, September.
  • Handle: RePEc:spr:metcap:v:24:y:2022:i:3:d:10.1007_s11009-021-09903-4
    DOI: 10.1007/s11009-021-09903-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11009-021-09903-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11009-021-09903-4?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
    ---><---

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

    References listed on IDEAS

    as
    1. Abdelghafour Es-Saghouani & Michel Mandjes, 2011. "Transient analysis of Markov-fluid-driven queues," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 19(1), pages 35-53, July.
    2. Eleonora Deiana & Guy Latouche & Marie-Ange Remiche, 2021. "Fluid Flow Model for Energy-Aware Server Performance Evaluation," Methodology and Computing in Applied Probability, Springer, vol. 23(3), pages 801-821, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hédi Nabli & Itidel Abdallah, 2023. "Stochastic Fluid Models with Upward Jumps and Phase Transitions," Methodology and Computing in Applied Probability, Springer, vol. 25(1), pages 1-26, March.

    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:spr:metcap:v:24:y:2022:i:3:d:10.1007_s11009-021-09903-4. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.