Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/BLOC.2019.8751305 | 2019 IEEE International Conference on Blockchain and Cryptocurrency (ICBC) |
Keywords | DocType | ISBN |
Bitcoin,network Topology,PageRank Algorithm,Nodes geolocation | Conference | 978-1-7281-1329-6 |
Citations | PageRank | References |
1 | 0.39 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Meryam Essaid | 1 | 2 | 3.12 |
| Se Jin Park | 2 | 5 | 4.22 |
| Hong-Taek Ju | 3 | 184 | 33.74 |