卡尔达诺权益证明池化行为的去中心化分析

Christina Ovezik, A. Kiayias
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引用次数: 1

摘要

区块链协议的主要区别在于其所谓的去中心化,可以解锁各种以前被认为不可能实现的信息技术应用。关键的承诺是,大量利益相关方的激励驱动参与可以导致分散的协议状态,在这种状态下,没有一个运营商可以成为“单点故障”。尽管有这样的承诺,但对区块链系统中的去中心化的系统分析很少,现有的零星理论和实证调查描绘了一幅相当负面的画面,因为在这种协议的“无许可”设置中,资源“池化行为”是不可能防止的,因为各方没有指定的身份。受此启发,本文采用基于智能体的建模方法,研究了权益证明系统背景下池化的纳什动力学。我们的重点是卡尔达诺区块链,因为它具有许多有吸引力的特征,有利于深入分析。我们旨在回答所采用的激励机制是否能够促进权力下放的问题。为此,我们提出了一个模拟引擎,使战略代理能够参与在系统的实际部署中经验观察到的许多操作。该引擎通过连续的代理行为来模拟“赌注池操作和委托游戏”,随着在模拟过程中有关其环境的更多信息变得明显,这些行为提高了它们的效用。我们研究了均衡状态的收敛性,并测量了这些状态下的各种去中心化指标,比如中本系数(Nakamoto coefficient),它询问存在多少独立实体,它们共同控制的资源超过了系统的资源。我们的研究结果举例说明了激励机制引导系统走向良好均衡的能力,也说明了这种均衡的去中心化特征如何受到机制中使用的参数的不同选择和参与者的利益分配的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Decentralization Analysis of Pooling Behavior in Cardano Proof of Stake
Blockchain protocols’ main differentiator is their purported decentralization that unlocks various information technology applications that were supposedly impossible beforehand. The key promise is that incentive-driven participation of a large set of interested parties can lead to decentralized protocol states where no single operator can be a “single point of failure.” Despite this promise, there is little systematic analysis of decentralization in blockchain systems and the sporadic theoretic and empirical investigations that exist paint a rather negative picture due to resource “pooling behaviors” that are impossible to prevent in the “permissionless” setting of such protocols where parties have no designated identities. Motivated by this, in this paper we study the Nash dynamics of pooling in the context of Proof of Stake systems, following an agent-based modeling approach. Our focus is the Cardano blockchain as it features a number of attractive characteristics making it conducive to an in-depth analysis. We aim to answer the question of whether the incentive mechanism employed is capable of promoting decentralization. To this end, we present a simulation engine that enables strategic agents to engage in a number of actions empirically observed in the real-world deployment of the system. The engine simulates the “stake pool operation and delegation game" via successive agent actions that improve their utility as more information about their environment becomes evident in the course of the simulation. We investigate convergence to equilibrium states, and we measure various decentralization metrics in these states, such as the Nakamoto coefficient, which asks how many independent entities exist that collectively command more than of the system’s resources. Our results exemplify the ability of the incentive mechanism to steer the system towards good equilibria and also illustrate how the decentralization features of such equilibria are affected by different choices of the parameters used in the mechanism and the distribution of stake to participants.
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