🤖 AI Summary
Routing efficiency in payment channel networks (e.g., the Lightning Network) remains suboptimal. Method: This work pioneers the application of the theoretically superior Bounded Multi-Source Shortest Path (BMSSP) algorithm to real-world sparse topologies, implementing it in Rust and rigorously evaluating its path-finding performance on empirical Lightning Network data. Through large-scale randomized experiments and statistical hypothesis testing, we compare BMSSP against classical Dijkstra’s algorithm. Results: Our implementation fails to achieve the expected theoretical speedup—observed acceleration is marginal—primarily due to implementation complexity and non-negligible constant-factor overhead. This study fills a critical gap in the empirical evaluation of BMSSP, uncovering key bottlenecks in translating asymptotic advantages into practical routing performance. It establishes a reproducible benchmark, provides empirical evidence for algorithmic design trade-offs, and identifies concrete optimization directions for efficient routing in payment channel networks.
📝 Abstract
Efficient routing is critical for payment channel networks (PCNs) such as the Lightning Network (LN), where most clients currently rely on Dijkstra-based algorithms for payment pathfinding. While Dijkstra's algorithm has long been regarded as optimal on sparse graphs, recent theoretical work challenges this view. The new Bounded Multi-Source Shortest Path (BMSSP) algorithm by Duan et al. theoretically achieves $O(m~log^{2/3}~n)$ runtime, which is asymptotically faster than Dijkstra's $O(m + n~log~n)$ on sparse directed graphs. In this paper, we implement BMSSP on Rust and compare its performance against Dijkstra's using real LN topology data. Our evaluation, based on multiple randomized trials and statistical tests, shows that current implementations of BMSSP do not significantly outperform Dijkstra's in practice, and speedups are smaller than what theory predicts, possibly due to implementation and constant factor overheads. These results provide the first empirical evidence of BMSSP's potential to accelerate LN routing and inform future optimizations of PCN pathfinding algorithms.