In a PoW-based blockchain network, mining pools (the solo miner could be regarded as a mining pool containing one miner) compete to successfully mine blocks to pursue rewards. Generally, the rewards include the fixed block subsidies and time-varying transaction fees. The transaction fees are offered by the senders whose transactions are packaged into blocks and is increasing with the block size. However, the larger size of a block brings the longer latency, resulting in a smaller probability of successfully mining. Therefore, finding the optimal block size to trade off these two factors is a complex and crucial problem for the mining pools. In this paper, we model a repeated mining competition dynamics in blockchain system as an evolutionary game to study the interactions among mining pools. In this game, each pool has two strategies: to follow the default size $\bar{B}$, i.e., the upper bound of a block size, or not follow. Because of the bounded rationality, each mining pool pursues its evolutionary stable block size (ESS) according to the mining pools' computing power and other factors by continuous learning and adjustments during the whole mining process. A study framework is built for the general evolutionary game, based on which we then theoretically explore the existence and stability of the ESSs for a case of two mining pools. Numerical experiments with real Bitcoin data are conducted to show the evolutionary decisions of mining pools and to demonstrate the theoretical findings in this paper.
翻译:在以PoW为基地的连锁网中,采矿池(独木矿工可被视为一个矿工组成的采矿池)竞相成功争取矿区奖励。一般而言,奖励包括固定的区块补贴和时间变化交易费。交易费由交易被包装成区块的汇款人提供,随着区块规模的增加而增加。但是,一个区块的面积越大,延缓时间越长,成功采矿的可能性就越小。因此,找到最佳的区块规模来交换这两个因素对采矿池来说是一个复杂和关键的问题。在本文中,我们以块链系统中反复出现的采矿竞争动态为模型,作为研究采矿池之间相互作用的进化游戏。在这个游戏中,每个矿群有两种战略:遵循默认数额$\bar{B}美元,即区块大小的上层,或没有遵循。由于受约束的合理性,每个矿池根据采矿池的计算能力和其他因素,通过在整个采矿场过程中不断学习和调整,不断学习和调整,来模拟矿区链系统中的采矿竞争动态动态动态动态动态动态动态。一个研究框架是,用来展示采矿业总进化的理论实验,其基础,用以展示。