可视化比特币的动态P2P网络拓扑和性能

Meryam Essaid, Se Jin Park, Hongtaek Ju
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引用次数: 10

摘要

在像比特币这样的大规模、动态和分布式P2P网络中,每秒发生数千次更新,使用传统的基于批量、离线数据的局部测量方法,或者基于发现一小部分节点周围的拓扑结构,然后将它们组合起来发现一个近似的网络拓扑结构,很难获得一个精确的拓扑结构,将网络结构表示为一个带有节点和链接的图。当将它们应用于基于区块链的网络时,所有这些都存在一些限制。在本文中,我们提出了一个拓扑发现系统,该系统使用定制版本的Page-Rank算法对比特币P2P链路进行实时数据收集和分析,该算法将传入节点信息组装起来进行更深入的图分析处理。拓扑发现系统可以让我们了解比特币网络的规模、比特币节点连接良好的网络稳定性,以及比特币节点的地理位置。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Visualising Bitcoin’s Dynamic P2P Network Topoogy and Performance
In massive, dynamic and distributed P2P networks like Bitcoin, where thousands of updates occur per second, it is hard to obtain an accurate topology representing the structure of the network as a graph with nodes and links by using the traditional local measurement approaches based on batches, offline data, or on the discovery of the topology around a small set of nodes and then combine them to discover an approximate network topology. All of which present some limitation when applying them on blockchain-based networks. In this paper, we propose a topology discovery system, which performs a real-time data collection and analysis for Bitcoin P2P links with the use of a customized version of the Page-Rank algorithm that assembles incoming nodes information for deeper graph analysis processing. The topology discovery system allows us to gain knowledge on the Bitcoin network size, the network stability in term of well-connected Bitcoin nodes, as well as some data regarding the Bitcoin nodes geolocation.
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