EG-DPoS:基于演化博弈的DPoS优化共识算法  

EG-DPoS:Optimized DPoS Consensus Algorithm Based on Evolutionary Game

作　　者：刘勇 邓小鸿 刘力汇 石亦燃 张丽 LIU Yong;DENG Xiaohong;LIU Lihui;SHI Yiran;ZHANG Li(School of Information Engineering,Jiangxi University of Science and Technology,Ganzhou,Jiangxi 341000,China;School of Information Engineering,Gannan University of Science and Technology,Ganzhou,Jiangxi 341000,China;Key Laboratory of Cloud Computing and Big Data,Ganzhou,Jiangxi 341000,China)

机构地区：[1]江西理工大学信息工程学院,江西赣州341000 [2]赣南科技学院信息工程学院,江西赣州341000 [3]赣州市云计算与大数据重点实验室,江西赣州341000

出　　处：《计算机科学与探索》2025年第5期1379-1394,共16页Journal of Frontiers of Computer Science and Technology

基　　金：国家自然科学基金(61762046,62166019);江西省自然科学基金(20224BAB202019)。

摘　　要：针对委托权益证明算法(DPoS)共识过程中,投票节点积极性不高、恶意节点贿赂拉票和代理节点按序出块易被攻击的问题,提出了一种基于演化博弈的DPoS优化共识算法(EG-DPoS)。引入信用机制构建节点投票激励模型,根据节点的投票情况给予信用值奖励,有效提高了节点的投票积极性;基于演化博弈的策略制定了一种行为奖惩机制,对投票选举阶段各节点的不同行为策略预设对应的收益函数并实施奖惩,以此来遏制恶意节点的贿赂合谋行为,保证了系统的稳定性和公平性;平衡代理节点选举过程中信用值和投票权重的比例系数,以减少高信用值节点造成的寡头现象,同时利用轮盘选择算法打乱代理节点的出块顺序,避免节点在出块过程中被攻击,提高了系统的安全性。仿真实验结果表明,与DPoS算法相比,EG-DPoS的平均时延降低了36.83%,平均吞吐量提高了19.44%,且参与投票的节点数与总节点数的比值提升约42%。这是由于EG-DPoS中存在投票激励机制和设定了固定的投票时间,以及在演化博弈策略的作用下,节点会随系统的运行表现得更加安全高效,使得代理节点的出块效率和共识效率更高,因此能在降低时延的同时提升吞吐量和投票节点的积极性,并且与其他典型DPoS改进算法相比,EGDPoS也具有明显的性能优势。Aiming at the problems of low enthusiasm among voting nodes,bribery from malicious nodes,and the vulnera-bility of sequential block generation by agent nodes in the delegated proof of stake(DPoS)consensus process,an opti-mized DPoS consensus algorithm based on evolutionary game theory(EG-DPoS)is proposed.The credit mechanism is introduced to construct the node voting incentive model,and the credit value reward is given according to the voting situa-tion of nodes,which effectively improves the voting enthusiasm of nodes.Based on the strategy of evolutionary game,a behavior reward and punishment mechanism is formulated,which presets the corresponding revenue functions for differ-ent behavior strategies of nodes in the voting and election stage and implements rewards and punishments,so as to curb the bribery and collusion behavior of malicious nodes and ensure the stability and fairness of the system.The proportional coefficient of credit value and voting weight in the process of agent node election is balanced to reduce the oligopoly phe-nomenon caused by nodes with high credit value,while the roulette selection algorithm is used to randomize the block generation order of agent nodes,to avoid nodes being attacked during block generation and improve the security of the system.Simulated results show that compared with DPoS algorithm,EG-DPoS algorithm reduces the average delay by 36.83%,increases the average throughput by 19.44%,and improves the ratio of voting nodes to total nodes by approxi-mately 42%.Due to the voting incentive mechanism within EG-DPoS and the fixed voting time,along with the influence of evolutionary game strategies,nodes will exhibit more secure and efficient behavior as the system operates.This leads to higher block generation and consensus efficiency for agent nodes,thereby reducing delay while improving throughput and the enthusiasm of voting nodes.Compared with other typical DPoS improved algorithms,EG-DPoS also has obvious performance advantages.

关 键 词：演化博弈 委托权益证明(DPoS) 共识算法 区块链 信用激励 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]