TRBFT: An Efficient Blockchain Consensus for Edge-Computing-Enabled IoT Systems
Jiali Zheng, Yuxi Zhang · IEEE Internet of Things Journal · 2025
With the continuous expansion of the Internet of Things (IoT), and despite reductions in communication latency enabled by edge computing, the decentralized nature of node structures poses significant security challenges. Blockchain is considered a critical technology for enhancing IoT security. However, traditional consensus exhibits limitations in efficiency and security when facing the exponential growth of IoT nodes necessitating further optimization and innovation. This article proposes the threshold signature and reputation-enhanced Byzantine fault tolerance (TRBFT) algorithm. First, we integrate IoT with edge computing architectures, conduct a comprehensive evaluation of node reputation based on behavioral quality and contribution to consensus, and periodically update and categorize nodes into different sets with varying permissions. Second, the algorithm ensures that the selection of primary nodes strikes a balance between reliability and randomness, while employing a segmented screening scheme that progressively restricts the participating nodes in consensus, aiming to enhance accuracy. Subsequently, the communication structure is improved by incorporating threshold signature with reputation weight, which reduces communication complexity. Ultimately, simulation results demonstrate that TRBFT reduces the average consensus delay by 71.1% and increases the average throughput by 3.95 times compared to the advanced consensus HotStuff. In scenarios with faulty nodes, TRBFT increases the chain growth rate by 65.12% and decreases the block interval by 54.26% relative to HotStuff. The findings show the superior scalability and fault tolerance of TRBFT, making it better suited for large-scale IoT scenarios integrated with edge computing.