IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v9y2017i4p91-d120383.html
   My bibliography  Save this article

High Throughput and Acceptance Ratio Multipath Routing Algorithm in Cognitive Wireless Mesh Network

Author

Listed:
  • Zhufang Kuang

    (School of Computer and Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China
    School of Software, Central South University, Changsha 410083, China)

  • Gongqiang Li

    (School of Computer and Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China)

  • Junshan Tan

    (School of Computer and Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China)

  • Zhigang Chen

    (School of Software, Central South University, Changsha 410083, China)

Abstract

The link failure due to the secondary users exiting the licensed channels when primary users reoccupy the licensed channels is very important in cognitive wireless mesh networks (CWMNs). A multipath routing and spectrum allocation algorithm based on channel interference and reusability with Quality of Service (QoS) constraints in CWMNs (MRIR) was proposed. Maximizing the throughput and the acceptance ratio of the wireless service is the objective of the MRIR. First, a primary path of resource conservation with QoS constraints was constructed, then, a resource conservation backup path based on channel interference and reusability with QoS constraints was constructed. The MRIR algorithm contains the primary path routing and spectrum allocation algorithm, and the backup path routing and spectrum allocation algorithm. The simulation results showed that the MRIR algorithm could achieve the expected goals and could achieve a higher throughput and acceptance ratio.

Suggested Citation

  • Zhufang Kuang & Gongqiang Li & Junshan Tan & Zhigang Chen, 2017. "High Throughput and Acceptance Ratio Multipath Routing Algorithm in Cognitive Wireless Mesh Network," Future Internet, MDPI, vol. 9(4), pages 1-15, November.
    • Handle: RePEc:gam:jftint:v:9:y:2017:i:4:p:91-:d:120383
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/9/4/91/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1999-5903/9/4/91/
    Download Restriction: no
    ---><---

    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:gam:jftint:v:9:y:2017:i:4:p:91-:d:120383. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.