IDEAS home Printed from https://ideas.repec.org/a/hin/jnljam/934610.html
   My bibliography  Save this article

Analysis and Enhancement of IEEE 802.15.4e DSME Beacon Scheduling Model

Author

Listed:
  • Kwang-il Hwang
  • Sung-wook Nam

Abstract

In order to construct a successful Internet of things (IoT), reliable network construction and maintenance in a sensor domain should be supported. However, IEEE 802.15.4, which is the most representative wireless standard for IoT, still has problems in constructing a large-scale sensor network, such as beacon collision. To overcome some problems in IEEE 802.15.4, the 15.4e task group proposed various different modes of operation. Particularly, the IEEE 802.15.4e deterministic and synchronous multichannel extension (DSME) mode presents a novel scheduling model to solve beacon collision problems. However, the DSME model specified in the 15.4e draft does not present a concrete design model but a conceptual abstract model. Therefore, in this paper we introduce a DSME beacon scheduling model and present a concrete design model. Furthermore, validity and performance of DSME are evaluated through experiments. Based on experiment results, we analyze the problems and limitations of DSME, present solutions step by step, and finally propose an enhanced DSME beacon scheduling model. Through additional experiments, we prove the performance superiority of enhanced DSME.

Suggested Citation

  • Kwang-il Hwang & Sung-wook Nam, 2014. "Analysis and Enhancement of IEEE 802.15.4e DSME Beacon Scheduling Model," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-15, May.
  • Handle: RePEc:hin:jnljam:934610
    DOI: 10.1155/2014/934610
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/JAM/2014/934610.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/JAM/2014/934610.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2014/934610?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
    ---><---

    Citations

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


    Cited by:

    1. Umar Draz & Tariq Ali & Sana Yasin & Muhammad Hasanain Chaudary & Muhammad Ayaz & El-Hadi M. Aggoune & Isha Yasin, 2024. "Hybridization and Optimization of Bio and Nature-Inspired Metaheuristic Techniques of Beacon Nodes Scheduling for Localization in Underwater IoT Networks," Mathematics, MDPI, vol. 12(22), pages 1-29, November.

    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:hin:jnljam:934610. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.