Blockchain-Enhanced IoT Sensor Data Management for Engineering Monitoring

In engineering monitoring and the Internet of Things (IoT) sensor networks, ensuring data security and real-time performance is a critical challenge. Traditional centralized data management faces issues such as high risks of data tampering, insufficient privacy protection, and inconsistent data sharing among multiple parties, making it difficult to handle high-frequency updates and complex collaboration. To address these issues, this article proposes a blockchain-based improved consensus algorithm, Reputation-based Practical Byzantine Fault Tolerance (RPBFT), to enhance the management efficiency and security of IoT sensor data. RPBFT enables secure data storage and sharing through smart contracts and introduces a node behavior incentive mechanism and a simplified consensus protocol to reduce communication overhead and consensus latency. Experimental results show that RPBFT reduces consensus latency by approximately 30%, increases throughput by 70%, significantly reduces energy consumption, and exhibits strong resistance to attacks. The study demonstrates that RPBFT is suitable for resource-constrained IoT sensor networks and can enhance performance and security in larger-scale and more complex network environments. Furthermore, the proposed algorithm provides practical implications for improving data reliability and system efficiency in real-world engineering monitoring scenarios, such as structural health monitoring and environmental safety supervision.

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Publication Details

Journal
IEEE Sensors Journal
Published
2024-12-31
DOI
https://doi.org/10.1109/jsen.2024.3519542
Citations
4
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
2.11
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article

Blockchain-Enhanced IoT Sensor Data Management for Engineering Monitoring

Zhuo Wang, Qian Wang
4 citations
IEEE Sensors Journal
Big Data and Business Intelligence
2.11
article

Blockchain-Enhanced IoT Sensor Data Management for Engineering Monitoring

Zhuo Wang, Qian Wang
article en
4 citations

Abstract

In engineering monitoring and the Internet of Things (IoT) sensor networks, ensuring data security and real-time performance is a critical challenge. Traditional centralized data management faces issues such as high risks of data tampering, insufficient privacy protection, and inconsistent data sharing among multiple parties, making it difficult to handle high-frequency updates and complex collaboration. To address these issues, this article proposes a blockchain-based improved consensus algorithm, Reputation-based Practical Byzantine Fault Tolerance (RPBFT), to enhance the management efficiency and security of IoT sensor data. RPBFT enables secure data storage and sharing through smart contracts and introduces a node behavior incentive mechanism and a simplified consensus protocol to reduce communication overhead and consensus latency. Experimental results show that RPBFT reduces consensus latency by approximately 30%, increases throughput by 70%, significantly reduces energy consumption, and exhibits strong resistance to attacks. The study demonstrates that RPBFT is suitable for resource-constrained IoT sensor networks and can enhance performance and security in larger-scale and more complex network environments. Furthermore, the proposed algorithm provides practical implications for improving data reliability and system efficiency in real-world engineering monitoring scenarios, such as structural health monitoring and environmental safety supervision.

IEEE Sensors JournalVol. 25(4)
China Mobile (China) (CN), China Railway Fifth Survey and Design Institute Group (CN), China Railway Group (China) (CN), China Railway Design Corporation (China) (CN), Beijing Survey and Design Institute (China) (CN)
Openalex Percentile: Top 10%
Big Data and Business Intelligence
2.11
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Blockchain-Enhanced IoT Sensor Data Management for Engineering Monitoring — Zhuo Wang, Qian Wang · IEEE Sensors Journal (2024) | TGRS Research Map | TGRS