CRNG-PBFT: An Efficient PBFT Algorithm Based on Comprehensive Reputation and Node Grouping for Data Sharing in Digital Twins

Data sharing helps the digital twin builders obtain the necessary data to construct a virtual replica of the physical entity. The consortium blockchain is one of the effective ways to solve the lack of trust among these participants, but the traditional PBFT cannot distinguish abnormal nodes and has poor scalability. We propose an efficient PBFT algorithm based on comprehensive reputation and node grouping for data sharing in digital twins. First, we design a comprehensive reputation evaluation mechanism to distinguish normal and abnormal nodes according to their behavior in the processes of data sharing and consensus. Secondly, a node grouping algorithm is proposed, in which nodes with high reputation form a committee, while other nodes are randomly assigned to different groups. Finally, we design consensus processes separately for the group and committee. Each transaction is recorded in the consortium blockchain when the group and committee have reached a consensus on it in sequence. Experimental results show that the CRNG-PBFT algorithm can effectively identify abnormal nodes, reduce transaction delay, and improve throughput.