EG-DPoS: Optimized DPoS Consensus Algorithm Based on Evolutionary Game
Aiming at the problems of low enthusiasm among voting nodes, bribery from malicious nodes, and the vulnerability of sequential block generation by agent nodes in the delegated proof of stake (DPoS) consensus process, an optimized DPoS consensus algorithm based on evolutionary game theory (EG-DPoS) i...
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| Format: | Article |
| Language: | zho |
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Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press
2025-05-01
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| Series: | Jisuanji kexue yu tansuo |
| Subjects: | |
| Online Access: | http://fcst.ceaj.org/fileup/1673-9418/PDF/2406101.pdf |
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| Summary: | Aiming at the problems of low enthusiasm among voting nodes, bribery from malicious nodes, and the vulnerability of sequential block generation by agent nodes in the delegated proof of stake (DPoS) consensus process, an optimized 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 situation 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 different 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 phenomenon 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 approximately 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. |
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| ISSN: | 1673-9418 |