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Energy-efficient load balancing in wireless sensor network: An application of multinomial regression analysis

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  • Ruwaida M Zuhairy
  • Mohammed GH Al Zamil

Abstract

Wireless sensor networks have become integral components of modern and smart environments. The main challenge for such important data-acquisition tools is the limited amount of available energy. In integrated networks in which cloud systems act as a self-regulatory controller, distributing the computational load among available partitions with rich energy will positively influence the lifetime of the whole network. This article investigates the application of a modified version of multinomial logistic regression model that incorporates spatiotemporal aspects of data collected from smart environments. The contribution of this research is to propose an energy-efficient load balancing strategy based on the proposed prediction model for the purpose of enhancing the lifetime of wireless infrastructure. Our proposed algorithm grows linearly in terms of time complexity. Extensive experiments have been performed to measure the prediction error rate and the energy consumption. The results showed that the proposed model significantly reduces the error rate and distinctly maximizes the lifetime of wireless sensor networks.

Suggested Citation

  • Ruwaida M Zuhairy & Mohammed GH Al Zamil, 2018. "Energy-efficient load balancing in wireless sensor network: An application of multinomial regression analysis," International Journal of Distributed Sensor Networks, , vol. 14(3), pages 15501477187, March.
    • Handle: RePEc:sae:intdis:v:14:y:2018:i:3:p:1550147718764641
    DOI: 10.1177/1550147718764641
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    References listed on IDEAS

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    1. Mohammed GH. AL Zamil & Samer Samarah, 2015. "Dynamic rough-based clustering for vehicular ad-hoc networks," International Journal of Information and Decision Sciences, Inderscience Enterprises Ltd, vol. 7(3), pages 265-285.
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    Cited by:

    1. Jagrati Kulshrestha & Manas Kumar Mishra, 2021. "Energy balanced data gathering approaches, issues and research directions," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 76(2), pages 299-327, February.

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