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Open Access

Energy-Efficient Sensory Data Collection Based on Spatiotemporal Correlation in IoT Networks

Jine Tang1, Shuang Wu2, Lingxiao Wei1, Weijing Liu3( ), Taishan Qin1, Zhangbing Zhou2, Junhua Gu1
School of Artificial Intelligence, Hebei University of Technology, Tianjin 300401, China
School of Information Engineering, China University of Geosciences, Beijing 100083, China
Tianjin Institute of Aerospace Mechanical and Electrical Equipment and Tianjin Key Laboratory of Aerospace Intelligent Equipment Technology, Tianjin 300301, China
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Abstract

The Internet of Things (IoT) is currently in a stage of rapid development. Hundreds of millions of sensing nodes and intelligent terminals undertake the tasks of sensing and transmitting data. Data collection is the key to realizing data analysis and intelligent application of IoT. The life cycle of IoT is limited by the energy of the IoT nodes in the network. A complex computing model will bring serious or even unbearable burdens to IoT nodes. In this study, we use the data prediction method to explore time correlation data and adjust the appropriate spatial sampling rate on the basis of the spatial correlation of sensory data to further reduce data. Specifically, the improved and optimized DNA-binding protein (DBP) data prediction method can increase the time interval of sensing data to further reduce energy consumption. Based on the spatial characteristics of the sensing data, substituting the data of similar nodes can reduce the sampling rate. The probabilistic wake-up strategy is also adopted to adjust the spatial correlation of the sensing data. On the basis of node priority, an optimized greedy algorithm is proposed to select the appropriate dominating node for eliminating redundant nodes and improving network energy utilization. Experiments have proven that our scheme reduces network energy consumption under the premise of ensuring data reliability.

Keywords

Internet of Thingsdata collectionspatiotemporal correlationenergy-saving

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International Journal of Crowd Science
Volume 6 Issue 1,
April 2022
Pages 34-43
DOI: 10.26599/IJCS.2022.9100007
Cite this article:
Tang J, Wu S, Wei L, et al. Energy-Efficient Sensory Data Collection Based on Spatiotemporal Correlation in IoT Networks. International Journal of Crowd Science, 2022, 6(1): 34-43. https://doi.org/10.26599/IJCS.2022.9100007

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Received: 03 January 2022
Revised: 05 March 2022
Accepted: 05 March 2022
Published: 15 April 2022
© The author(s) 2022

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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