Splicer$^{+}$: Secure Hub Placement and Deadlock-Free Routing for Payment Channel Network Scalability

2025-01-08

AI Summary

Traditional payment channel hubs (PCHs) in payment channel networks (PCNs) suffer from load imbalance and limited scalability due to their neglect of heterogeneous payment request distributions. Method: This paper proposes a TEE-based multi-hub deployment and deadlock-free, globally aware routing framework. It introduces supermodular optimization into PCH location modeling, designs a dynamic rate-adaptive source routing protocol that jointly leverages global state and local demand, and provides a formal security proof within the Universal Composability (UC) framework. Contribution/Results: Experimental evaluation demonstrates that the proposed scheme achieves a 51.1% improvement in transaction success rate, an 181.5% increase in throughput, and significantly reduced end-to-end latency—outperforming all existing PCN approaches across key metrics.

Technology Category

• Planning, Routing, and Scheduling: Scheduling under Uncertainty
• Multiagent Systems: Mechanism Design
• Search and Optimization: Distributed Search

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Security and Privacy: Large-scale security measurements
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Payment channel hub (PCH) is a promising approach for payment channel networks (PCNs) to improve efficiency by deploying robust hubs to steadily process off-chain transactions. However, existing PCHs, often preplaced without considering payment request distribution across PCNs, can lead to load imbalance. PCNs' reliance on source routing, which makes decisions based solely on individual sender requests, can degrade performance by overlooking other requests, thus further impairing scalability. In this paper, we introduce Splicer$^{+}$, a highly scalable multi-PCH solution based on the trusted execution environment (TEE). We study tradeoffs in communication overhead between participants, transform the original NP-hard PCH placement problem by mixed-integer linear programming, and propose optimal/approximate solutions with load balancing for different PCN scales using supermodular techniques. Considering global PCN states and local directly connected sender requests, we design a deadlock-free routing protocol for PCHs. It dynamically adjusts the payment processing rate across multiple channels and, combined with TEE, ensures high-performance routing with confidential computation. We provide a formal security proof for the Splicer$^{+}$ protocol in the UC-framework. Extensive evaluations demonstrate the effectiveness of Splicer$^{+}$, with transaction success ratio ($uparrow$51.1%), throughput ($uparrow$181.5%), and latency outperforming state-of-the-art PCNs.

Problem

• Payment Channel Networks
• Workload Imbalance
• Transaction Processing

Innovation

• Payment Channel Hubs Optimization
• Deadlock-Free Payment Path Planning
• Secure Off-Chain Transactions