IDEAS home Printed from https://ideas.repec.org/a/sae/intdis/v9y2013i2p345821.html
   My bibliography  Save this article

Adaptive Learning Based Scheduling in Multichannel Protocol for Energy-Efficient Data-Gathering Wireless Sensor Networks

Author

Listed:
  • Kieu-Ha Phung
  • Bart Lemmens
  • Mihail Mihaylov
  • Lan Tran
  • Kris Steenhaut

Abstract

Multichannel communication protocols have been developed to alleviate the effects of interference and consequently improve the network performance in wireless sensor networks requiring high bandwidth. In this paper, we propose a contention-free multichannel protocol to maximize network throughput while ensuring energy-efficient operation. Arguing that routing decisions influence to a large extent the network throughput, we formulate route selection and transmission scheduling as a joint problem and propose a Reinforcement Learning based scheduling algorithm to solve it in a distributed manner. The results of extensive simulation experiments show that the proposed solution not only provides a collision-free transmission schedule but also minimizes energy waste, which makes it appropriate for energy-constrained wireless sensor networks.

Suggested Citation

  • Kieu-Ha Phung & Bart Lemmens & Mihail Mihaylov & Lan Tran & Kris Steenhaut, 2013. "Adaptive Learning Based Scheduling in Multichannel Protocol for Energy-Efficient Data-Gathering Wireless Sensor Networks," International Journal of Distributed Sensor Networks, , vol. 9(2), pages 345821-3458, February.
  • Handle: RePEc:sae:intdis:v:9:y:2013:i:2:p:345821
    DOI: 10.1155/2013/345821
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1155/2013/345821
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2013/345821?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
    ---><---

    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:sae:intdis:v:9:y:2013:i:2:p:345821. 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: SAGE Publications (email available below). General contact details of provider: .

    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.