IDEAS home Printed from https://ideas.repec.org/a/spr/telsys/v79y2022i2d10.1007_s11235-021-00862-2.html
   My bibliography  Save this article

Localization of isotropic and anisotropic wireless sensor networks in 2D and 3D fields

Author

Listed:
  • Soumya J. Bhat

    (Manipal Academy of Higher Education)

  • K. V. Santhosh

    (Manipal Academy of Higher Education)

Abstract

Internet of Things (IoT) has changed the way people live by transforming everything into smart systems. Wireless Sensor Network (WSN) forms an important part of IoT. This is a network of sensor nodes that is used in a vast range of applications. WSN is formed by the random deployment of sensor nodes in various fields of interest. The practical fields of deployment can be 2D or 3D, isotropic or anisotropic depending on the application. The localization algorithms must provide accurate localization irrespective of the type of field. In this paper, we have reported a localization algorithm called Range Reduction Based Localization (RRBL). This algorithm utilizes the properties of hop-based and centroid methods to improve the localization accuracy in various types of fields. In this algorithm, the location unknown nodes identify the close-by neighboring nodes within a predefined threshold and localize themselves by identifying and reducing the probable range of existence from these neighboring nodes. The nodes which do not have enough neighbors are localized using the least squares method. The algorithm is tested in various irregular and heterogeneous conditions. The results are compared with a few state-of-the-art hop-based and centroid-based localization techniques. RRBL has shown an improvement in localization accuracy of 28% at 10% reference node ratio and 26% at 20% reference node ratio when compared with other localization algorithms.

Suggested Citation

  • Soumya J. Bhat & K. V. Santhosh, 2022. "Localization of isotropic and anisotropic wireless sensor networks in 2D and 3D fields," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 79(2), pages 309-321, February.
    • Handle: RePEc:spr:telsys:v:79:y:2022:i:2:d:10.1007_s11235-021-00862-2
    DOI: 10.1007/s11235-021-00862-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11235-021-00862-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11235-021-00862-2?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Siqi Zhang & Fang Fan & Wei Li & Shu-Chuan Chu & Jeng-Shyang Pan, 2021. "A parallel compact sine cosine algorithm for TDOA localization of wireless sensor network," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 78(2), pages 213-223, October.
    2. M. Mazhar Rathore & Anand Paul & Awais Ahmad & Gwanggil Jeon, 2017. "IoT-Based Big Data: From Smart City towards Next Generation Super City Planning," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 13(1), pages 28-47, January.
    3. Sana Messous & Hend Liouane & Noureddine Liouane, 2020. "Improvement of DV-Hop localization algorithm for randomly deployed wireless sensor networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 73(1), pages 75-86, January.
    4. Gaurav Sharma & Ashok Kumar, 2018. "Fuzzy logic based 3D localization in wireless sensor networks using invasive weed and bacterial foraging optimization," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 67(2), pages 149-162, 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. Achour Achroufene, 2023. "RSSI-based Hybrid Centroid-K-Nearest Neighbors localization method," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 82(1), pages 101-114, January.

    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.
    1. Hilary I. Okagbue & Muminu O. Adamu & Timothy A. Anake & Ashiribo S. Wusu, 2019. "Nature inspired quantile estimates of the Nakagami distribution," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 72(4), pages 517-541, December.
    2. Nikhlesh Pathik & Rajeev Kumar Gupta & Yatendra Sahu & Ashutosh Sharma & Mehedi Masud & Mohammed Baz, 2022. "AI Enabled Accident Detection and Alert System Using IoT and Deep Learning for Smart Cities," Sustainability, MDPI, vol. 14(13), pages 1-24, June.
    3. Shilpi & Arvind Kumar, 2023. "A localization algorithm using reliable anchor pair selection and Jaya algorithm for wireless sensor networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 82(2), pages 277-289, February.
    4. Johannes Stübinger & Lucas Schneider, 2020. "Understanding Smart City—A Data-Driven Literature Review," Sustainability, MDPI, vol. 12(20), pages 1-23, October.
    5. Eunbee Gil & Yongjin Ahn & Youngsang Kwon, 2020. "Tourist Attraction and Points of Interest (POIs) Using Search Engine Data: Case of Seoul," Sustainability, MDPI, vol. 12(17), pages 1-21, August.
    6. Prabhjot Singh & Nitin Mittal & Parulpreet Singh, 2022. "A novel hybrid range-free approach to locate sensor nodes in 3D WSN using GWO-FA algorithm," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 80(3), pages 303-323, July.
    7. Shaohua Wang & Xianxiong Liu & Haiyin Wang & Qingwu Hu, 2018. "A Case Study on Spatio-Temporal Data Mining of Urban Social Management Events Based on Ontology Semantic Analysis," Sustainability, MDPI, vol. 10(6), pages 1-24, June.
    8. Rehman Abdul & Anand Paul & Junaid Gul M. & Won-Hwa Hong & Hyuncheol Seo, 2018. "Exploiting Small World Problems in a SIoT Environment," Energies, MDPI, vol. 11(8), pages 1-18, August.
    9. Hend Liouane & Sana Messous & Omar Cheikhrouhou, 2022. "Regularized least square multi-hops localization algorithm based on DV-Hop for wireless sensor networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 80(3), pages 349-358, July.
    10. Johan Meppelink & Jens Van Langen & Arno Siebes & Marco Spruit, 2020. "Beware Thy Bias: Scaling Mobile Phone Data to Measure Traffic Intensities," Sustainability, MDPI, vol. 12(9), pages 1-19, May.
    11. Zhanxue Gong & Xiyuan Li & Jiawen Liu & Yeming Gong, 2019. "Machine learning in explaining nonprofit organizations’ participation : a driving factors analysis approach," Post-Print hal-02880932, HAL.

    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:spr:telsys:v:79:y:2022:i:2:d:10.1007_s11235-021-00862-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.