Theoretical Analysis on Block Time Distributions in Byzantine Fault-Tolerant Consensus Blockchains

Akihiro Fujihara
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Abstract

Some blockchain networks employ a distributed consensus algorithm featuring Byzantine fault tolerance. Notably, certain public chains, such as Cosmos and Tezos, which operate on a proof-of-stake mechanism, have adopted this algorithm. While it is commonly assumed that these blockchains maintain a nearly constant block creation time, empirical analysis reveals fluctuations in this interval; this phenomenon has received limited attention. In this paper, we propose a mathematical model to account for the processes of block propagation and validation within Byzantine fault-tolerant consensus blockchains, aiming to theoretically analyze the probability distribution of block time. First, we propose stochastic processes governing the broadcasting communications among validator nodes. Consequently, we theoretically demonstrate that the probability distribution of broadcast time among validator nodes adheres to the Gumbel distribution. This finding indicates that the distribution of block time typically arises from convolving multiple Gumbel distributions. Additionally, we derive an approximate formula for the block time distribution suitable for data analysis purposes. By fitting this approximation to real-world block time data, we demonstrate the consistent estimation of block time distribution parameters.
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拜占庭容错共识区块链的区块时间分布理论分析
一些区块链网络采用了具有拜占庭容错功能的分布式共识算法。值得注意的是,某些公有链采用了这种算法,如 Cosmos 和Tezos,它们采用的是权益证明机制。虽然人们通常认为这些区块链的区块创建时间几乎保持恒定,但实证分析表明,这个时间间隔会出现波动;这一现象受到的关注有限。在本文中,我们提出了一个数学模型来解释拜占庭容错共识区块链中的区块传播和验证过程,旨在从理论上分析区块时间的概率分布。首先,我们提出了验证器节点间广播通信的随机过程。因此,我们从理论上证明了验证器节点间广播时间的概率分布符合 Gumbel 分布。这一发现表明,块时间的分布通常是由多个冈贝尔分布卷积而成的。此外,我们还推导出了适用于数据分析的块时间分布近似公式。通过将该近似公式拟合到真实世界的块时间数据中,我们证明了对块时间分布参数的一致估计。
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