IDEAS home Printed from https://ideas.repec.org/a/sae/intdis/v11y2015i7p614643.html
   My bibliography  Save this article

On the Optimality of Generic Rate-Based AIMD and AIAD Congestion Control Schemes in Cognitive Radio Sensor Networks

Author

Listed:
  • Vahid Esmaeelzadeh
  • Reza Berangi

Abstract

Investigating the optimality and the modeling of congestion control schemes is crucial in order to provide quality of service (QoS) for various applications in cognitive radio sensor networks (CRSNs). This paper develops an analytical framework to study the optimality of rate-based generic AIMD and AIAD congestion control schemes. In this way, a congestion model is introduced to describe the congestion behavior of CRSNs. A semi-Markov chain (SMC) is proposed to model the steady-state sending rate distribution of source nodes based on the congestion model. The optimality of generic AIMD and AIAD, based on the proposed models, is analyzed in order to maximize the defined rate-congestion ratio (RCR). The analytical results are verified through various NS2-based simulations in CRSNs.

Suggested Citation

  • Vahid Esmaeelzadeh & Reza Berangi, 2015. "On the Optimality of Generic Rate-Based AIMD and AIAD Congestion Control Schemes in Cognitive Radio Sensor Networks," International Journal of Distributed Sensor Networks, , vol. 11(7), pages 614643-6146, July.
  • Handle: RePEc:sae:intdis:v:11:y:2015:i:7:p:614643
    DOI: 10.1155/2015/614643
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1155/2015/614643
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2015/614643?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:sae:intdis:v:11:y:2015:i:7:p:614643. 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: SAGE Publications (email available below). General contact details of provider: .

    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.