论文标题
区块链系统的稳定性和可扩展性
Stability and Scalability of Blockchain Systems
论文作者
论文摘要
区块链范式提供了一种在对等网络（P2P）网络上传播和分布式共识的机制。尽管该范式在行业中广泛采用，但尚未根据其相对于同行数量的网络扩展进行仔细的分析。区块链系统（例如加密货币和物联网）的应用需要这种形式的网络缩放。 在本文中，我们为区块链系统提出了一个新的随机网络模型。我们确定了一个称为\ emph {one-endendness}的结构属性，我们在任何区块链系统中都可以看到，因为它与同行之间的分布式共识直接相关。我们表明，网络的随机稳定性足以满足区块链的单端性。我们进一步确定我们的模型属于一类网络模型，称为单调可分离模型。这使我们能够在稳定区域建立上限和下限。稳定性的界限取决于P2P网络通过其电导的连接性，并允许我们分析大型P2P网络上区块链系统的可扩展性。我们使用比特币网络中的合成数据和真实数据来验证我们的理论见解。
The blockchain paradigm provides a mechanism for content dissemination and distributed consensus on Peer-to-Peer (P2P) networks. While this paradigm has been widely adopted in industry, it has not been carefully analyzed in terms of its network scaling with respect to the number of peers. Applications for blockchain systems, such as cryptocurrencies and IoT, require this form of network scaling. In this paper, we propose a new stochastic network model for a blockchain system. We identify a structural property called \emph{one-endedness}, which we show to be desirable in any blockchain system as it is directly related to distributed consensus among the peers. We show that the stochastic stability of the network is sufficient for the one-endedness of a blockchain. We further establish that our model belongs to a class of network models, called monotone separable models. This allows us to establish upper and lower bounds on the stability region. The bounds on stability depend on the connectivity of the P2P network through its conductance and allow us to analyze the scalability of blockchain systems on large P2P networks. We verify our theoretical insights using both synthetic data and real data from the Bitcoin network.
