IDEAS home Printed from https://ideas.repec.org/a/sae/intdis/v13y2017i12p1550147717748909.html
   My bibliography  Save this article

Optimal sleep time controller based on traffic prediction and residual energy in duty-cycled wireless sensor networks

Author

Listed:
  • Haibo Luo
  • Minghua He
  • Zhiqiang Ruan
  • Xiaxia Zeng

Abstract

In duty-cycled wireless sensor networks, energy efficiency and packet latency are two most important metrics in the design of medium access control and routing algorithms. However, these two problems cannot be addressed well at the same time. In this article, we investigate the trade-off between energy consumption and latency and formulate them into a multi-objective optimization problem. By applying the single exponential smoothing method, we estimate the amount of data of next period and design two optimal sleep time controllers according to time scheduling model of network, so as to dynamically adjust the duty cycle of end node. Our controllers also consider the residual energy of end node. Finally, we propose two dynamic and adaptive medium access control algorithms for synchronous and asynchronous duty-cycled wireless sensor networks, respectively. We evaluate our protocols with different parameters and compare them with existing works. Performance results show that our proposed algorithms can balance power consumption among nodes and improve power efficiency while guaranteeing packet latency is minimized.

Suggested Citation

  • Haibo Luo & Minghua He & Zhiqiang Ruan & Xiaxia Zeng, 2017. "Optimal sleep time controller based on traffic prediction and residual energy in duty-cycled wireless sensor networks," International Journal of Distributed Sensor Networks, , vol. 13(12), pages 15501477177, December.
  • Handle: RePEc:sae:intdis:v:13:y:2017:i:12:p:1550147717748909
    DOI: 10.1177/1550147717748909
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1550147717748909
    Download Restriction: no

    File URL: https://libkey.io/10.1177/1550147717748909?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
    ---><---

    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:13:y:2017:i:12:p:1550147717748909. 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.