IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0156880.html
   My bibliography  Save this article

Pliable Cognitive MAC for Heterogeneous Adaptive Cognitive Radio Sensor Networks

Author

Listed:
  • Mohammed Al-Medhwahi
  • Fazirulhisyam Hashim
  • Borhanuddin Mohd Ali
  • Aduwati Sali

Abstract

The rapid expansion of wireless monitoring and surveillance applications in several domains reinforces the trend of exploiting emerging technologies such as the cognitive radio. However, these technologies have to adjust their working concepts to consider the common characteristics of conventional wireless sensor networks (WSNs). The cognitive radio sensor network (CRSN), still an immature technology, has to deal with new networks that might have different types of data, traffic patterns, or quality of service (QoS) requirements. In this paper, we design and model a new cognitive radio-based medium access control (MAC) algorithm dealing with the heterogeneous nature of the developed networks in terms of either the traffic pattern or the required QoS for the node applications. The proposed algorithm decreases the consumed power on several fronts, provides satisfactory levels of latency and spectrum utilization with efficient scheduling, and manages the radio resources for various traffic conditions. An intensive performance evaluation is conducted to study the impact of key parameters such as the channel idle time length, node density, and the number of available channels. The performance evaluation of the proposed algorithm shows a better performance than the comparable protocols. Moreover, the results manifest that the proposed algorithm is suitable for real time monitoring applications.

Suggested Citation

  • Mohammed Al-Medhwahi & Fazirulhisyam Hashim & Borhanuddin Mohd Ali & Aduwati Sali, 2016. "Pliable Cognitive MAC for Heterogeneous Adaptive Cognitive Radio Sensor Networks," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-22, June.
    • Handle: RePEc:plo:pone00:0156880
    DOI: 10.1371/journal.pone.0156880
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0156880
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0156880&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0156880?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
    ---><---

    References listed on IDEAS

    as
    1. Xiao Yu Wang & Alexander Wong, 2013. "Multi-Parametric Clustering for Sensor Node Coordination in Cognitive Wireless Sensor Networks," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-10, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mohammed Al-Medhwahi & Fazirulhisyam Hashim & Borhanuddin Mohd Ali & A Sali & Abdulsalam Alkholidi, 2019. "Resource allocation in heterogeneous cognitive radio sensor networks," International Journal of Distributed Sensor Networks, , vol. 15(7), pages 15501477198, July.
    2. Xin Yang & Ling Wang & Jian Xie & Zhaolin Zhang, 2018. "Cross-layer model design in wireless ad hoc networks for the Internet of Things," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-11, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      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:plo:pone00:0156880. 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.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

      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.