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Research of energy efficient clustering algorithm for multilayer wireless heterogeneous sensor networks prediction research

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Abstract

In designing wireless sensor networks of image transmitting, it is important to reduce energy dissipation and prolong network lifetime. This paper presents the research on existing clustering algorithm applied in heterogeneous sensor networks and then puts forward an energy-efficient prediction clustering algorithm, which is adaptive to sensor networks with energy and objects heterogeneous. This algorithm enables the nodes to select the cluster head according to factors such as energy and communication cost, thus the nodes with higher residual energy have higher probability to become a cluster head than those with lower residual energy, so that the network energy can be dissipated uniformly. In order to reduce energy consumption when broadcasting in clustering phase and prolong network lifetime, an energy consumption prediction model is established for regular data acquisition nodes. Simulation results and the application in image clustering show that compared with current clustering algorithms, this algorithm can achieve longer sensor network lifetime, higher energy efficiency, and superior network monitoring quality.

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Acknowledgments

The research was founded within the project No. 61310306022. entitled: ‘Key technology of a new generation of wireless mobile communication system’ supported by National Science Foundation.

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Authors and Affiliations

  1. School of Electrical Engineering, Southwest Petroleum University, Chengdu, 610500, China

    Dai Yun-Zhong & Luo Ren-Ze

  2. School of Electrical Engineering, Southwest Jiaotong University, Chengdu, 610031, China

    Dai Yun-Zhong

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  1. Dai Yun-Zhong
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  2. Luo Ren-Ze
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Correspondence to Dai Yun-Zhong.

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Yun-Zhong, D., Ren-Ze, L. Research of energy efficient clustering algorithm for multilayer wireless heterogeneous sensor networks prediction research. Multimed Tools Appl 76, 19345–19361 (2017). https://doi.org/10.1007/s11042-015-2880-2

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  • DOI: https://doi.org/10.1007/s11042-015-2880-2

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