| Title |
Quantitative analysis of centralization in the bitcoin lightning network through centrality metrics |
| Authors |
Atmanavičiūtė, Laura ; Vanagas, Tomas ; Masteika, Saulius |
| DOI |
10.1109/ACCESS.2025.3614085 |
| Full Text |
|
| Is Part of |
IEEE Access.. Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE). 2025, vol. 13, p. 168761-168781.. eISSN 2169-3536 |
| Keywords [eng] |
bitcoin ; lightning ; peer-to-peer computing ; measurement ; blockchains ; statistical analysis ; scalability ; routing ; market research ; indexes |
| Abstract [eng] |
The Bitcoin Lightning Network, a Layer-2 more scalable solution for the Bitcoin blockchain, has emerged to address the scalability challenges faced by the Bitcoin network. However, the centralization of the Lightning Network has been a growing concern, as the concentration of highly active nodes within it could compromise the decentralized nature of the Bitcoin ecosystem. In this research paper, we conduct a quantitative analysis of centralization in the Lightning Network using various centrality metrics, such as Gini coefficient, Nakamoto coefficient, Herfindahl-Hirschman Index, Theil Index and Shannon entropy. The proposed methodology includes data collection, clustering nodes into entities and setting up the experimental environment. The quantitative analysis of centralization in the BLN reveals complex results, with the Gini coefficient for node capacity distribution increasing from 0.85 to 0.97 over eight yearly timestamps, indicating growing inequality. Meanwhile, the Nakamoto coefficient fluctuated, suggesting that while control over network resources is uneven, it may still be more decentralized than previously thought. |
| Published |
Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE) |
| Type |
Journal article |
| Language |
English |
| Publication date |
2025 |
| CC license |
|
