IDEAS home Printed from https://ideas.repec.org/a/sae/intdis/v13y2017i3p1550147717700895.html
   My bibliography  Save this article

Variable-dimension swarm meta-heuristic for the optimal placement of relay nodes in wireless sensor networks

Author

Listed:
  • Yi-Han Xu
  • Wan-Guo Jiao
  • Yin Wu
  • Jun Song

Abstract

A wireless sensor network is a network consisting of wireless sensor nodes. There are usually requirements that need to be met when deploying a wireless sensor network, one being the placement of nodes. Due to placement requirements and limited node transmission range, a network might be partitioned initially. Therefore, additional relay nodes are added to the network to form an interconnected network. In this article, the minimum relay nodes placement problem in wireless sensor networks is addressed. This problem addresses the placement of relay nodes: the minimum number needed and where the nodes should be placed. The problem is formulated as a Steiner tree problem with minimum Steiner points and a bounded edge length problem, which is NP-hard. In this article, we present a variable-dimension meta-heuristic based on particle swarm optimization called multi-space particle swarm optimization to address the problem. We tested multi-space particle swarm optimization using randomly generated instances of the Steiner tree problem with minimum Steiner points and a bounded edge length problem of varying sizes and found that multi-space particle swarm optimization is effective in addressing the Steiner tree problem with minimum Steiner points and a bounded edge length problem.

Suggested Citation

  • Yi-Han Xu & Wan-Guo Jiao & Yin Wu & Jun Song, 2017. "Variable-dimension swarm meta-heuristic for the optimal placement of relay nodes in wireless sensor networks," International Journal of Distributed Sensor Networks, , vol. 13(3), pages 15501477177, March.
    • Handle: RePEc:sae:intdis:v:13:y:2017:i:3:p:1550147717700895
    DOI: 10.1177/1550147717700895
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1550147717700895
    Download Restriction: no
    File URL: https://libkey.io/10.1177/1550147717700895?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
    ---><---

    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:13:y:2017:i:3:p:1550147717700895. 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.