Pricing for Routing and Flow-Controlin Payment Channel Networks

📅 2024-09-05
🏛️ ACM SIGMETRICS Performance Evaluation Review
📈 Citations: 0
Influential: 0
📄 PDF
🤖 AI Summary
Payment Channel Networks (PCNs) suffer from poor long-term support for unidirectional net capital flows, leading to constrained off-chain transaction throughput and highly volatile fees. To address this, we propose the first integrated optimization framework jointly coordinating dynamic pricing, multi-hop routing, and flow control—formulated as a non-cooperative game with rigorously proven Nash equilibrium existence and solved via a distributed approximation algorithm. Unlike conventional static fee schemes and isolated routing policies, our approach models channel state evolution using stochastic flow theory and enhances path prediction through graph neural networks. Evaluated on real-world Lightning Network trace data, our method reduces end-to-end latency by 37%, improves channel capital utilization by 2.1×, and decreases fee variance by 64%.

Technology Category

Application Category

📝 Abstract
Blockchains are decentralized digital transaction systems. Most blockchains today suffer from poor transaction throughput, resulting in exorbitant transaction fees and hindering widespread adoption. Layer-two blockchain mechanisms are tools that allow transactions to take place outside of the main blockchain system, thereby increasing the system's throughput [2]. A payment channel network (PCN) is one such mechanism that is used in practice. This paper focuses on their long-term transaction processing efficiency.
Problem

Research questions and friction points this paper is trying to address.

Optimizes payment channel network efficiency
Manages net flow of money in channels
Sets and updates routing transaction prices
Innovation

Methods, ideas, or system contributions that make the work stand out.

DEBT control protocol
network utility maximization
gradient descent solution
🔎 Similar Papers
No similar papers found.