BDBFT:A Consensus Protocol Based on Reputation Prediction Model for IoT Scenario

Blockchain technology has the advantages of strong data security and high trustworthiness in IoT scenarios,but the consensus algorithm in blockchain technology has the disadvantages of high energy consumption,high computational cost,and low scalability,and the deployment of blockchain system in IoT applications faces the problems of low storage capacity,low energy consumption,and low computational capacity of IoT nodes.Based on practical Byzantine fault tolerant algorithm(PBFT),this paper proposes a consensus protocol based on reputation prediction model(BDBFT) in IoT scenario.Firstly,nodes are grouped according to the geographic location classification criteria of the grouping policy to select consensus nodes and reduce the communication delay of intra-group communication.Secondly,a fine-grained reputation prediction model based on Dirichlet distribution is introduced to dynamically update the model according to the reputation information in the lifecycle of each round of view,and nodes with high prediction probability based on the historical and current reputation information are voted as the consensus nodes.The simulation experiment results show that compared with PBFT algorithm and LRBFT algorithm,BDBFT algorithm effectively reduces the probability of Byzantine nodes participating in the consensus,and has obvious performance improvement in four aspects:time delay,throughput,communication overhead and security.