While the practical Byzantine fault tolerance (PBFT) consensus algorithm provides excellent theoretical fault tolerance, its performance in practical blockchain applications is often constrained by high communication overhead, especially in scenarios with limited node resources and high mobility, such as Vehicular Ad hoc Networks (VANETs). To address these blockchain-specific limitations without sacrificing the fundamental safety guarantees against arbitrary Byzantine failures, this paper proposes a novel PBFT-optimized consensus algorithm based on a dynamic reputation tree (DRT-PBFT). First, to address the issue of limited storage resources, we propose a block synchronization method based on differentiated storage of reputation values. The lower-reputation nodes retain only “micro-blocks” that contain essential information of the complete block, while the higher-reputation nodes store and synchronize complete blocks, significantly reducing the storage overhead. Second, on the basis of the reputation values, we construct a tree communication topology from the leaf node layer in a bottom-up manner. Messages are transmitted from multiple child nodes to their parent node, resolving the problem of a single message source in the tree structure. Additionally, we optimize the consensus process, reducing the number of mutual communications between nodes to a linear level. Finally, to address the problem of malicious nodes in the tree structure, we introduce a dynamic reconstruction mechanism for the reputation tree. When child node messages are inconsistent, the parent node splits the child nodes to mitigate the influence of malicious nodes, enhancing both the security and scalability of the consensus process. The experimental results show that, compared with typical improved PBFT algorithms, the proposed algorithm improves the average throughput by 34.1% and reduces the average latency by 27.4%. Moreover, compared with the full replication block synchronization method, the differentiated storage method reduces the storage overhead by 26.3%, making it potentially more suitable for large-scale VANET scenarios.
Deng et al. (Mon,) studied this question.