IDEAS home Printed from https://ideas.repec.org/a/wly/intnem/v27y2017i4ne1979.html
   My bibliography  Save this article

Learning ensemble strategy for static and dynamic localization in wireless sensor networks

Author

Listed:
  • Hanen Ahmadi
  • Federico Viani
  • Alessandro Polo
  • Ridha Bouallegue

Abstract

Indoor localization in wireless sensor networks is a challenging task. Static localization and moving target monitoring are addressed using ensemble learning method and received signal strength indicator. The suggested strategy combines several regression trees to have better performance. This solution has been experimentally evaluated using real measurements in an office room. The performance results have been analyzed through a comparison with learning‐based localization algorithms currently available in the literature. The analysis shows that the adopted solution is simple in term of computation, accurate and robust to environmental variation.

Suggested Citation

  • Hanen Ahmadi & Federico Viani & Alessandro Polo & Ridha Bouallegue, 2017. "Learning ensemble strategy for static and dynamic localization in wireless sensor networks," International Journal of Network Management, John Wiley & Sons, vol. 27(4), July.
    • Handle: RePEc:wly:intnem:v:27:y:2017:i:4:n:e1979
    DOI: 10.1002/nem.1979
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/nem.1979
    Download Restriction: no
    File URL: https://libkey.io/10.1002/nem.1979?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. A. R. Ashok Kumar & S. V. Rao & Diganta Goswami, 2016. "Simple, efficient location‐based routing for data center network using IP address hierarchy," International Journal of Network Management, John Wiley & Sons, vol. 26(6), pages 492-514, November.
    Full references (including those not matched with items on IDEAS)

    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:wly:intnem:v:27:y:2017:i:4:n:e1979. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1002/(ISSN)1099-1190 .

      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.