Adaptive Clustering Hierarchical PBFT Algorithm for Secure and Efficient Blockchain-Based IoT Edge Computing
Jiali Zheng, Jincheng Xie, Yanting Su · IEEE Sensors Journal · 2024
With the rapid development of the Internet of Things (IoT), the importance of data transmission security and efficiency has become increasingly significant. Traditional consensus mechanisms, particularly, the practical Byzantine fault-tolerance (PBFT) algorithm, face notable challenges in the context of blockchain-based edge computing due to scalability issues. Specifically, as the number of nodes increases, PBFT experiences high communication complexity, which leads to significant performance degradation. To tackle this challenge, this article proposes a novel consensus algorithm named adaptive clustering hierarchical-PBFT (ACH-PBFT) that employs a hierarchical cluster structure and node fault-tolerance check to enhance the security and efficiency of blockchain-based edge computing in the IoT. ACH-PBFT adaptively selects an appropriate primary node and forms multiple subnode clusters, facilitating a more scalable consensus process. The system reduces the probability of malicious nodes becoming primary nodes through mutual verification between the primary node cluster and the subcluster consensus. Experimental results indicate that the ACH-PBFT algorithm achieves a 19.83% increase in execution speed, a 23.67% improvement in throughput, and an average reduction of 23.05% in communication overhead compared with a similar double-layer PBFT algorithm lacking hierarchical clustering. In the experiments testing against malicious nodes, the ACH-PBFT algorithm exhibited an average increase of 24.73% in the probability of successfully achieving consensus. Overall, this research provides a practical and effective solution for implementing secure and efficient blockchain-based IoT edge computing using a multilayer architecture to achieve flexible deployment and efficient resource utilization in edge computing environments.