IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v8y2020i4p583-d345371.html
   My bibliography  Save this article

Social Network Optimization for WSN Routing: Analysis on Problem Codification Techniques

Author

Listed:
  • Alessandro Niccolai

    (Dipartimento di Energia, Politecnico di Milano, Via Lambruschini 4, 20156 Milano, Italy)

  • Francesco Grimaccia

    (Dipartimento di Energia, Politecnico di Milano, Via Lambruschini 4, 20156 Milano, Italy)

  • Marco Mussetta

    (Dipartimento di Energia, Politecnico di Milano, Via Lambruschini 4, 20156 Milano, Italy)

  • Alessandro Gandelli

    (Dipartimento di Energia, Politecnico di Milano, Via Lambruschini 4, 20156 Milano, Italy)

  • Riccardo Zich

    (Dipartimento di Energia, Politecnico di Milano, Via Lambruschini 4, 20156 Milano, Italy)

Abstract

The correct design of a Wireless Sensor Network (WSN) is a very important task because it can highly influence its installation and operational costs. An important aspect that should be addressed with WSN is the routing definition in multi-hop networks. This problem is faced with different methods in the literature, and here it is managed with a recently developed swarm intelligence algorithm called Social Network Optimization (SNO). In this paper, the routing definition in WSN is approached with two different problem codifications and solved with SNO and Particle Swarm Optimization. The first codification allows the optimization algorithm more degrees of freedom, resulting in a slower and in many cases sub-optimal solution. The second codification reduces the degrees of freedom, speeding significantly the optimization process and blocking in some cases the convergence toward the real best network configuration.

Suggested Citation

  • Alessandro Niccolai & Francesco Grimaccia & Marco Mussetta & Alessandro Gandelli & Riccardo Zich, 2020. "Social Network Optimization for WSN Routing: Analysis on Problem Codification Techniques," Mathematics, MDPI, vol. 8(4), pages 1-21, April.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:4:p:583-:d:345371
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/8/4/583/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/8/4/583/
    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:jmathe:v:8:y:2020:i:4:p:583-:d:345371. 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.