A Range Query Method with Data Fusion in Two-Layer Wire-Less Sensor Networks

Wireless sensor networks play a crucial role in IoT applications. Traditional range query methods have limitations in multi-sensor data fusion and energy efficiency. This paper proposes a new range query method for two-layer wireless sensor networks. The method supports data fusion operations directly on storage nodes. Communication costs between sink nodes and storage nodes are significantly reduced. Reverse Z-O coding optimizes the encoding process by focusing only on the most valuable data. This approach shortens both encoding time and length. Data security is ensured using the Paillier homomorphic encryption algorithm. A comparison chain for the most valuable data is generated using Reverse Z-O coding and HMAC. Storage nodes can perform multi-sensor data fusion under encryption. Experiments were conducted on Raspberry Pi 2B+ and NVIDIA TX2 platforms. Performance was evaluated in terms of fusion efficiency, query dimensions, and data volume. The results demonstrate secure and efficient multi-sensor data fusion with lower energy consumption. The method outperforms existing approaches in reducing communication and computational costs.

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Publication Details

Journal
Symmetry
Published
2025-10-22
DOI
https://doi.org/10.3390/sym17111784
Primary Topic
Energy Efficient Wireless Sensor Networks
Type
article
Field-Weighted Citation Impact
0.00

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article

A Range Query Method with Data Fusion in Two-Layer Wire-Less Sensor Networks

Shouxue Chen, Yun Deng, Xiaohui Cheng
Symmetry
Energy Efficient Wireless Sensor Networks
article

A Range Query Method with Data Fusion in Two-Layer Wire-Less Sensor Networks

Shouxue Chen, Yun Deng, Xiaohui Cheng
article en

Abstract

Wireless sensor networks play a crucial role in IoT applications. Traditional range query methods have limitations in multi-sensor data fusion and energy efficiency. This paper proposes a new range query method for two-layer wireless sensor networks. The method supports data fusion operations directly on storage nodes. Communication costs between sink nodes and storage nodes are significantly reduced. Reverse Z-O coding optimizes the encoding process by focusing only on the most valuable data. This approach shortens both encoding time and length. Data security is ensured using the Paillier homomorphic encryption algorithm. A comparison chain for the most valuable data is generated using Reverse Z-O coding and HMAC. Storage nodes can perform multi-sensor data fusion under encryption. Experiments were conducted on Raspberry Pi 2B+ and NVIDIA TX2 platforms. Performance was evaluated in terms of fusion efficiency, query dimensions, and data volume. The results demonstrate secure and efficient multi-sensor data fusion with lower energy consumption. The method outperforms existing approaches in reducing communication and computational costs.

SymmetryVol. 17(11)
Guilin University of Technology (CN), Embedded Systems (United States) (US)
Natural Science Foundation of Guangxi Province
Openalex Percentile: Top 64%
Energy Efficient Wireless Sensor Networks
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