Ethna: Analyzing the Underlying Peer-to-Peer Network of the Ethereum Blockchain
Not on the map. Why?
Abstract (arXiv)
The peer-to-peer (P2P) network of blockchain used to transport its transactions and blocks has a high impact on the efficiency and security of the system. The P2P network topologies of popular blockchains such as Bitcoin and Ethereum, therefore, deserve our highest attention. The current Ethereum blockchain explorers (e.g., Etherscan) focus on the tracking of block and transaction records but omit the characterization of the underlying P2P network. This work presents the Ethereum Network Analyzer (Ethna), a tool that probes and analyzes the P2P network of the Ethereum blockchain. Unlike Bitcoin that adopts an unstructured P2P network, Ethereum relies on the Kademlia DHT to manage its P2P network. Therefore, the existing analytical methods for Bitcoin-like P2P networks are not applicable to Ethereum. Ethna implements a novel method that accurately measures the degrees of Ethereum nodes. Furthermore, it incorporates an algorithm that derives the latency metrics of message propagation in the Ethereum P2P network. We ran Ethna on the Ethereum Mainnet and conducted extensive experiments to analyze the topological features of its P2P network. Our analysis shows that the Ethereum P2P network possesses a certain effect of small-world networks, and the degrees of nodes follow a power-law distribution that characterizes scale-free networks.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Oct 2020.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 1; 2022: 0; 2023: 0; 2024: 0; 2025: 1; 2026: 1.
3 papers.
- 2021A Marketplace for Trading AI Models based on Blockchain and Incentives for IoT Datacited by 8
- 2025Analysing semantic data storage in Distributed Ledger Technologies for Data Spacescited by 0
- 2026Robust Smart Contract Vulnerability Detection via Contrastive Learning-Enhanced Granular-ball Trainingcited by 0
- 2026Robust Smart Contract Vulnerability Detection via Contrastive Learning-Enhanced Granular-ball Training29 Mar 2026
- 2025Analysing semantic data storage in Distributed Ledger Technologies for Data Spaces3 Jul 2025
- 2021A Marketplace for Trading AI Models based on Blockchain and Incentives for IoT Data6 Dec 2021