Consensus Node Group Selection and Adjustment Algorithm Based on Dual Random Selection Mechanism
Xiaojian Gu, Tianyu Kang, Anshun Zhou, Li Guo · 2023
The PBFT algorithm is a consensus algorithm that reduces communication complexity to a polynomial level, addressing the inefficiency of traditional Byzantine fault tolerance mechanisms. It is commonly adopted in the consensus layer of blockchain systems. However, as the number of system nodes increases, the algorithm faces the challenge of rapidly increasing communication complexity. One solution to this problem is to use deterministic algorithms to select smaller consensus groups. However, in an open network, this approach is susceptible to Distributed Denial of Service (DDoS) attacks against the main nodes, posing a risk of system unavailability. Another solution involves using Verifiable Random Functions (VRF) technology to select consensus group nodes. However, this approach often introduces additional time overhead. To combine the advantages of both solutions, this paper proposes an improved PBFT algorithm based on a Dual-Random-Selection mechanism (DRS-BFT). The algorithm uses an unbiased random selection function and a verifiable random function to select consensus group members and the primary node. In situations with a large number of nodes, the algorithm enhances consensus efficiency by selecting a consensus group, minimizing additional communication overhead, and ensuring system security. Security analysis demonstrates that the system, under the assumption of security requirements, can guarantee data integrity, consistency, and availability. It can also prevent targeted attacks against the primary node that could lead to system unavailability. To validate the system's functionality and performance, the paper designs and develops a prototype system and establishes an experimental environment. The experiments show that the algorithm dynamically adjusts the consensus group range through the Dual-Random-Selection mechanism to adapt to changes in network conditions. Additionally, compared to traditional PBFT, the algorithm exhibits superior performance.