Scalable Exact Path Selection via Structure-Aware Search for Virtual Payment Channels

2026-08-23

AI Summary

研究通过结构感知搜索解决虚拟支付通道路径选择问题，提出基于四叉树搜索的精确求解器，显著减少计算量并提高效率。

Abstract

Virtual Payment Channels (VPCs) enable efficient off-chain transactions in Payment Channel Networks (PCNs), but their performance depends on selecting high-quality underlying paths. Existing approaches either rely on simplified metrics or incur high computational cost. We study VPC path selection under generalized monotone metrics and propose a structure-aware exact solver based on quadtree search. By exploiting monotonicity and distance plateau properties, our method prunes large regions of the capacity-constrained search space while preserving optimality, significantly reducing the number of shortest-path computations. We further instantiate the framework with a composite metric that integrates economic cost and security risk, enabling flexible trade-offs across application scenarios. Experiments on synthetic graphs and real-world Lightning Network topologies (up to 12,552 nodes) show 2--5 orders of magnitude speedup over prior work, with consistent sub-100ms latency.

Problem

• Virtual Payment Channels
• Path Selection
• Monotone Metrics
• Capacity-Constrained Search Space
• Economic Cost and Security Risk

Innovation

• structure-aware search
• quadtree search
• monotone metrics
• composite metric
• virtual payment channels