IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/4826388.html
   My bibliography  Save this article

BioWSN: A Bio-Inspired Method for Optimization of Routing in Wireless Sensor Networks

Author

Listed:
  • Ramin Ahmadi
  • Gholamhossein Ekbatanifard
  • Peyman Bayat
  • Jian Li

Abstract

Wireless sensor networks (WSN) have been recently gaining traction for many applications in monitoring and surveillance systems in the physical world specifically in agriculture, healthcare, and smart cities. Many clustering and routing approaches have been introduced to reduce the consumption of energy in WSNs to increase the lifetime of the network. In this study, we propose an improved version of grey wolf optimizer (GWO), a nature-inspired metaheuristic optimization algorithm, to perform cluster head selection and routing in WSN while maximizing the lifetime of WSN. GWO has a propensity to converge to local optima. To overcome this drawback of the conventional GWO, we introduce a balancing factor between the exploration and exploitation phases of the algorithm in addition to a mapping scheme. Comparative simulation and analysis of the proposed algorithm show significant improvement compared to frequently used and well-known approaches namely LEACH and PSO.

Suggested Citation

  • Ramin Ahmadi & Gholamhossein Ekbatanifard & Peyman Bayat & Jian Li, 2022. "BioWSN: A Bio-Inspired Method for Optimization of Routing in Wireless Sensor Networks," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-12, April.
    • Handle: RePEc:hin:jnlmpe:4826388
    DOI: 10.1155/2022/4826388
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/mpe/2022/4826388.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/mpe/2022/4826388.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2022/4826388?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:4826388. 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.