Graph-Based Testing of Blockchain Topologies

The underlying peer-to-peer (P2P) network topology of a blockchain is a critical determinant of its core properties, including performance, security, decentralization, and scalability. Graph models provide a powerful and principled framework for representing, analyzing, and testing these complex network structures. This review surveys a broad corpus of peer-reviewed literature and technical reports from 2015 to 2026, focusing on the application of graph models to blockchain topology testing. The surveyed studies encompass active and passive measurement techniques (e.g., TxProbe, TopoShot), large-scale simulation frameworks (e.g., Lilith, Diablo, Kollaps), and advanced analytical approaches like Graph Neural Networks (GNNs). Principal findings reveal that P2P overlay networks often exhibit scale-free characteristics with heavy-tailed degree distributions, raising concerns about centralization. Network topology directly impacts performance metrics like propagation latency, which correlates with fork rates and consensus instability. The review concludes that while significant progress has been made, a lack of standardization in benchmarking hinders cross-study comparability, necessitating standardized testing rubrics and more sophisticated temporal graph models.