IDEAS home Printed from https://ideas.repec.org/a/eee/spapps/v129y2019i5p1749-1781.html
   My bibliography  Save this article

A scaling analysis of a star network with logarithmic weights

Author

Listed:
  • Robert, Philippe
  • Véber, Amandine

Abstract

The paper investigates the properties of a class of resource allocation algorithms for communication networks: if a node of this network has L requests to transmit and is idle, it tries to access the channel at a rate proportional to log(1+L). A stochastic model of such an algorithm is investigated in the case of the star network, in which J nodes can transmit simultaneously, but interfere with a central node 0 in such a way that node 0 cannot transmit while one of the other nodes does. One studies the impact of the log policy on these J+1 interacting communication nodes. A fluid scaling analysis of the network is derived with the scaling parameter N being the norm of the initial state. It is shown that the asymptotic fluid behavior of the system is a consequence of the evolution of the state of the network on a specific time scale (Nt,t∈(0,1)). The main result is that, on this time scale and under appropriate conditions, the state of a node with index j≥1 is of the order of Naj(t), with 0≤aj(t)<1, where t↦aj(t) is a piecewise linear function. Convergence results on the fluid time scale and a stability property are derived as a consequence of this study.

Suggested Citation

  • Robert, Philippe & Véber, Amandine, 2019. "A scaling analysis of a star network with logarithmic weights," Stochastic Processes and their Applications, Elsevier, vol. 129(5), pages 1749-1781.
  • Handle: RePEc:eee:spapps:v:129:y:2019:i:5:p:1749-1781
    DOI: 10.1016/j.spa.2018.06.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304414918302746
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.spa.2018.06.002?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.

    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:129:y:2019:i:5:p:1749-1781. 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.