Low-Overhead Routing for Offchain Networks with High Resource Utilization
Xiaoxue Zhang, Shouqian Shi, Chen Qian · 2023
Off-chain networks have been designed and utilized to address the scalability challenge and throughput limitation of blockchains. Routing is a core problem. An ideal off-chain networks routing method needs to achieve 1) high scalability that can maintain low per-node memory and communication cost for large networks and 2) high resource utilization of channels. However, none of the existing off-chain routing methods achieve both requirements. In this work, we propose WebFlow, a distributed routing solution for off-chain networks, which only requires each user to maintain localized information and can be used for massive-scale networks with high resource utilization. We make use of two distributed data structures: multi-hop Delaunay triangulation (MDT) originally proposed for wireless networks and our innovation called distributed Voronoi diagram. We propose new protocols to generate a virtual Euclidean space in order to apply MDT to off-chain networks and use the distributed Voronoi diagram to enhance routing privacy. We conduct extensive simulations and prototype implementation to further evaluate WebFlow. The results using real and synthetic off-chain network topologies and transaction traces show that WebFlow can achieve extremely low per-node overhead and a high success rate compared to existing methods.