  Payment channel networks (PCNs) have been designed and utilized to address
the scalability challenge and throughput limitation of blockchains. Routing is
a core problem of PCNs. An ideal PCN routing method needs to achieve 1) high
scalability that can maintain low per-node memory and communication cost for
large PCNs, 2) high resource utilization of payment channels, and 3) the
privacy of users. However, none of the existing PCN systems consider all these
requirements. In this work, we propose WebFlow, a distributed routing solution
for PCNs, 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 PCNs 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 PCN topologies and transaction traces show that WebFlow can achieve
extremely low per-node overhead and a high success rate compared to existing
methods.
