Game Theory based Incentive Mechanism Design and Analysis for the Public EVONChain

Abstract

Incentive mechanisms serve as the driving force behind blockchain operations, bearing significant implications for the practical applications of blockchain technology. However, existing incentive mechanisms predominantly focus on incentivization from a monetary perspective, with minimal incorporation of punitive measures, thus exhibiting limited efficacy in regulating system entities. Furthermore, the assurance of providing adequate incentives for the full nodes of the system cannot be guaranteed, potentially resulting in node attrition and posing threats to blockchain security. In this paper, we propose EVONIncentive, a hybrid incentive scheme based on game theory for the bi-tiered public blockchain called EVONChain. It adopts a hybrid incentive form of monetary and reputation, introducing fee selection mechanisms, compensation mechanisms, and supervisory penalty mechanisms to ensure the sustainability, fairness, and security of the Blockchain system. Two Stackelberg dynamic game models are constructed based on different issues, and through algorithm design and mathematical derivation, the optimal incentive allocation is obtained. Finally, through numerical simulation experiments, the specific values of relevant parameters such as mining rewards, transaction fee, and compensation are determined. A comparative experiment with the Ethereum 1.0 incentive mechanism is implemented. The results show that EVONIncentive has significant advantages over Ethereum 1.0 incentive mechanism in terms of system social welfare, user income gap, and fairness.