PBFT optimization algorithm based on community contributions

Community governance is the basic unit of social governance, and it is also an important direction for building a social governance pattern of co-construction, co-governance and sharing. Previous studies have solved the problems of data security, information traceability and participant enthusiasm in the process of community digital governance by building a community governance system based on blockchain technology and incentive mechanisms. The application of blockchain technology can solve the problems of low data security, difficulty in sharing and tracing and low enthusiasm on the part of multiple subjects regarding participation in community governance. The process of community governance involves the cooperation of multiple government departments and multiple social subjects. Under the blockchain architecture, the number of alliance chain nodes will reach 1000 with the expansion of community governance. The existing consensus algorithms for coalition chains are difficult to meet the high concurrent processing requirements under such large-scale nodes. An optimization algorithm has improved the consensus performance to a certain extent, but the existing systems still cannot meet the data needs of the community and are not suitable for community governance scenarios. Since the community governance process only involves the participation of relevant departments in users, all nodes in the network are not required to participate in the consensus under the blockchain architecture. Therefore, a practical Byzantine fault tolerance (PBFT) optimization algorithm based on community contribution (CSPBFT) is proposed here. First, consensus nodes are set according to different roles of participants in community activities, and participants are given different consensus permissions. Second, the consensus process is divided into different stages, and the amount of data processed by each consensus step is reduced. Finally, a two -level consensus network is designed to perform different consensus tasks, and reduce unnecessary communication between nodes to reduce the communication complexity of consensus among nodes. Compared with the PBFT algorithm, CSPBFT reduces the communication complexity from O(N2) to O(N2/C3). Finally, the simulation results show that, through rights management, network level setting and consensus phase division, when the number of nodes in the CSPBFT network is 100-400, the consensus throughput can reach 2000 TPS. When the node in the network is 1000, the instantaneous concurrency is guaranteed to be above 1000 TPS, which can meet the concurrent needs of the community governance scenario.