Node Classification and Geographical Analysis of the Lightning Cryptocurrency Network

Philipp Zabka, Klaus-Tycho Förster, S. Schmid, Christian Decker
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引用次数: 5

Abstract

Off-chain networks provide an attractive solution to the scalability challenges faced by cryptocurrencies such as Bitcoin. While first interesting networks are emerging, we currently have relatively limited insights into the structure and distribution of these networks. Such knowledge, however is useful, when reasoning about possible performance improvements or the security of the network. For example, information about the different node types and implementations in the network can help when planning the distribution of critical software updates. This paper reports on a large measurement study of Lightning, a leading off-chain network, considering recorded network messages over a period of more than two years. In particular, we present an approach and classification of the node types (LND, C-Lightning and Eclair) in the network, and find that we can determine the implementation of 99.9% of nodes in our data set. We also report on geographical aspects of the Lightning network, showing that proximity is less relevant, and that the Lightning network is particularly predominant in metropolitan areas. As a contribution to the research community, we will release our experimental data together with this paper.
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闪电加密货币网络节点分类与地理分析
链下网络为比特币等加密货币面临的可扩展性挑战提供了一个有吸引力的解决方案。虽然第一个有趣的网络正在出现,但我们目前对这些网络的结构和分布的了解相对有限。然而,在推断可能的性能改进或网络安全性时,这些知识是有用的。例如,关于网络中不同节点类型和实现的信息可以帮助规划关键软件更新的分发。本文报告了对领先的链下网络闪电的大型测量研究,考虑了两年多来记录的网络信息。特别是,我们提出了网络中节点类型(LND, C-Lightning和Eclair)的方法和分类,并发现我们可以确定数据集中99.9%的节点的实现。我们还报告了闪电网络的地理方面,表明距离不太相关,闪电网络在大都市地区尤其占主导地位。作为对研究界的贡献,我们将与本文一起发布我们的实验数据。
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Certification of an Exact Worst-Case Self-Stabilization Time Early Classification Approaches for Sensors Generated Multivariate Time Series with Different Challenges Proceedings of the 22nd International Conference on Distributed Computing and Networking Node Classification and Geographical Analysis of the Lightning Cryptocurrency Network Secure Conflict-free Replicated Data Types
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