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http://dx.doi.org/10.9717/kmms.2020.24.1.067

A Residual Power Estimation Scheme Using Machine Learning in Wireless Sensor Networks  

Bae, Shi-Kyu (Dept. of Computer Engineering, DongYang University)
Publication Information
Journal of Korea Multimedia Society / v.24, no.1, 2021 , pp. 67-74 More about this Journal
Abstract
As IoT(Internet Of Things) devices like a smart sensor have constrained power sources, a power strategy is critical in WSN(Wireless Sensor Networks). Therefore, it is necessary to figure out the residual power of each sensor node for managing power strategies in WSN, which, however, requires additional data transmission, leading to more power consumption. In this paper, a residual power estimation method was proposed, which uses ignorantly small amount of power consumption in the resource-constrained wireless networks including WSN. A residual power prediction is possible with the least data transmission by using Machine Learning method with some training data in this proposal. The performance of the proposed scheme was evaluated by machine learning method, simulation, and analysis.
Keywords
Wireless Sensor Network; Power Consumption; Residual Power; Machine Learning; Multiple Linear Regression;
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Times Cited By KSCI : 1  (Citation Analysis)
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