LAUSR

Today, Raft’s distributed cluster scale is growing rapidly and cluster throughput is declining. The Raft consensus algorithm needs to be continuously optimized to adapt to a complex and changeable application environment. To solve the above problems, we propose a federal reconstruction Committee Raft consensus algorithm FRCR. Based on the Federation reconstruction technology, the algorithm trains, updates and evaluates the model of the characteristic data set of the Raft node, runs the model to get the nodes with better performance, constructs the committee mechanism, and improves the quality and speed of the election. We also design a semi asynchronous buffer mechanism and a strategy to resist malicious node attacks to solve the inconsistency and security problems of federation aggregation. Finally, seven aspects of FRCR are tested and analyzed to verify the effectiveness of FRCR in the consensus cluster.