IDEAS home Printed from https://ideas.repec.org/a/spr/telsys/v65y2017i3d10.1007_s11235-016-0240-9.html
   My bibliography  Save this article

Bayesian inference approach for establishing efficient routes in wireless ad-hoc networks

Author

Listed:
  • Wafa Alkhabbaz

    (King Abdulaziz City for Science and Technology)

  • Amr Alasaad

    (King Abdulaziz City for Science and Technology)

  • Meshal Alshaye

    (The University of Washington)

Abstract

Mobile ad hoc networks (MANETs) are dynamic wireless networks that have no fixed infrastructures and do not require predefined configurations. In this infrastructure-less paradigm, nodes in addition of being hosts, they also act as relays and forward data packets for other nodes in the network. Due to limited resources in MANETs such as bandwidth and power, the performance of the routing protocol plays a significant role. A routing protocol in MATET should not introduce excessive control messages to the network in order to save network bandwidth and nodes power. In this paper, we propose a probabilistic approach based on Bayesian inference to enable efficient routing in MANETs. Nodes in the proposed approach utilize the broadcast nature of the wireless channel to observe the network topology by overhearing wireless transmissions at neighboring nodes in a distributed manner, and learn from these observations when taking packet forwarding decision on the IP network layer. Our simulation results show that our routing approach reduces the number of control message (routing overhead) by a ratio up to 20 % when the network size is 60 nodes, while maintaining similar average route establishment delay as compared to the ad-hoc on demand routing protocol.

Suggested Citation

  • Wafa Alkhabbaz & Amr Alasaad & Meshal Alshaye, 2017. "Bayesian inference approach for establishing efficient routes in wireless ad-hoc networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 65(3), pages 387-405, July.
    • Handle: RePEc:spr:telsys:v:65:y:2017:i:3:d:10.1007_s11235-016-0240-9
    DOI: 10.1007/s11235-016-0240-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11235-016-0240-9
    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/s11235-016-0240-9?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:spr:telsys:v:65:y:2017:i:3:d:10.1007_s11235-016-0240-9. 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: 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.