IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/6342421.html
   My bibliography  Save this article

Congested Link Inference Algorithms in Dynamic Routing IP Network

Author

Listed:
  • Yu Chen
  • Zhe-min Duan

Abstract

The performance descending of current congested link inference algorithms is obviously in dynamic routing IP network, such as the most classical algorithm CLINK. To overcome this problem, based on the assumptions of Markov property and time homogeneity, we build a kind of Variable Structure Discrete Dynamic Bayesian (VSDDB) network simplified model of dynamic routing IP network. Under the simplified VSDDB model, based on the Bayesian Maximum A Posteriori (BMAP) and Rest Bayesian Network Model (RBNM), we proposed an Improved CLINK (ICLINK) algorithm. Considering the concurrent phenomenon of multiple link congestion usually happens, we also proposed algorithm CLILRS (Congested Link Inference algorithm based on Lagrangian Relaxation Subgradient) to infer the set of congested links. We validated our results by the experiments of analogy, simulation, and actual Internet.

Suggested Citation

  • Yu Chen & Zhe-min Duan, 2017. "Congested Link Inference Algorithms in Dynamic Routing IP Network," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-17, January.
    • Handle: RePEc:hin:jnlmpe:6342421
    DOI: 10.1155/2017/6342421
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2017/6342421.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2017/6342421.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2017/6342421?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
    ---><---

    More about this item

    Statistics

    Access and download statistics

    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:hin:jnlmpe:6342421. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.