IDEAS home Printed from https://ideas.repec.org/a/igg/jitn00/v11y2019i2p12-23.html
   My bibliography  Save this article

An Improved Data Collection Algorithm for Wireless Sensor Networks

Author

Listed:
  • Vemula Manohar Reddy

    (Sam Houston State University, Huntsville, USA)

  • Min Kyung An

    (Sam Houston State University, Huntsville, USA)

  • Hyuk Cho

    (Sam Houston State University, Huntsville, USA)

Abstract

This article studies the minimum latency collection scheduling (MLCS) problem in wireless sensor networks (WSNs). The MLCS problem targets to compute a schedule with minimum number of timeslots that guarantees to collect data from all nodes to a sink node without any collision. Several scheduling algorithms have been proposed for the NP-hard problem, and they assign timeslots based on hop distances among nodes. The proposed algorithm not only uses hop distances, but also partitions a network into square cells and assign timeslots based on cell distances among nodes. The latency performance of the proposed algorithm is compared with an existing algorithm whose approximation ratio is currently the best, and the simulations show that the proposed algorithm performs better.

Suggested Citation

  • Vemula Manohar Reddy & Min Kyung An & Hyuk Cho, 2019. "An Improved Data Collection Algorithm for Wireless Sensor Networks," International Journal of Interdisciplinary Telecommunications and Networking (IJITN), IGI Global, vol. 11(2), pages 12-23, April.
  • Handle: RePEc:igg:jitn00:v:11:y:2019:i:2:p:12-23
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJITN.2019040102
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shereen Ismail & Diana W. Dawoud & Hassan Reza, 2023. "Securing Wireless Sensor Networks Using Machine Learning and Blockchain: A Review," Future Internet, MDPI, vol. 15(6), pages 1-45, May.

    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:igg:jitn00:v:11:y:2019:i:2:p:12-23. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.