Boosting Payment Channel Network Liquidity with Topology Optimization and Transaction Selection

2025-08-20

AI Summary

In payment channel networks (PCNs), transaction throughput is fundamentally constrained by network topology and channel capacity allocation. Method: This paper jointly optimizes network topology design, channel capacity provisioning, and dynamic transaction routing decisions to minimize the total cost of channel creation/expansion and transaction rejection. Contribution/Results: We propose the first combinatorial approximation algorithm for multi-party PCNs: under general assumptions, it achieves an O(p) approximation ratio; under reasonable statistical assumptions, this improves to O(√p). Leveraging graph-theoretic modeling and an online decision mechanism, our approach yields theoretically guaranteed joint optimization. Empirical evaluation on the Lightning Network demonstrates significant reductions in operational costs, extended channel lifetimes, and improved transaction processing efficiency.

Technology Category

• Search and Optimization: Algorithm Configuration
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Multiagent Systems: Mechanism Design

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Payment channel networks (PCNs) are a promising technology that alleviates blockchain scalability by shifting the transaction load from the blockchain to the PCN. Nevertheless, the network topology has to be carefully designed to maximise the transaction throughput in PCNs. Additionally, users in PCNs also have to make optimal decisions on which transactions to forward and which to reject to prolong the lifetime of their channels. In this work, we consider an input sequence of transactions over $p$ parties. Each transaction consists of a transaction size, source, and target, and can be either accepted or rejected (entailing a cost). The goal is to design a PCN topology among the $p$ cooperating parties, along with the channel capacities, and then output a decision for each transaction in the sequence to minimise the cost of creating and augmenting channels, as well as the cost of rejecting transactions. Our main contribution is an $mathcal{O}(p)$ approximation algorithm for the problem with $p$ parties. We further show that with some assumptions on the distribution of transactions, we can reduce the approximation ratio to $mathcal{O}(sqrt{p})$. We complement our theoretical analysis with an empirical study of our assumptions and approach in the context of the Lightning Network.

Problem

• Optimizing PCN topology to maximize transaction throughput
• Selecting transactions to prolong channel lifetime efficiently
• Minimizing channel creation and transaction rejection costs

Innovation

• Topology optimization for transaction throughput
• Approximation algorithm for cost minimization
• Empirical study in Lightning Network context