[Paper Review] High Throughput Cryptocurrency Routing in Payment Channel Networks

Vibhaalakshmi Sivaraman, Shaileshh Bojja Venkatakrishnan+6 more|arXiv (Cornell University)|Sep 13, 2018

Caching and Content Delivery38 references41 citations

TL;DR

Spider packetizes transactions and uses a multi-path congestion-control protocol to achieve high-throughput routing in payment channel networks, reducing required collateral and increasing throughput compared to state-of-the-art approaches.

ABSTRACT

Despite growing adoption of cryptocurrencies, making fast payments at scale remains a challenge. Payment channel networks (PCNs) such as the Lightning Network have emerged as a viable scaling solution. However, completing payments on PCNs is challenging: payments must be routed on paths with sufficient funds. As payments flow over a single channel (link) in the same direction, the channel eventually becomes depleted and cannot support further payments in that direction; hence, naive routing schemes like shortest-path routing can deplete key payment channels and paralyze the system. Today's PCNs also route payments atomically, worsening the problem. In this paper, we present Spider, a routing solution that "packetizes" transactions and uses a multi-path transport protocol to achieve high-throughput routing in PCNs. Packetization allows Spider to complete even large transactions on low-capacity payment channels over time, while the multi-path congestion control protocol ensures balanced utilization of channels and fairness across flows. Extensive simulations comparing Spider with state-of-the-art approaches shows that Spider requires less than 25% of the funds to successfully route over 95% of transactions on balanced traffic demands, and offloads 4x more transactions onto the PCN on imbalanced demands.

Motivation & Objective

• Motivate the need for scalable, fast payments in cryptocurrency through Payment Channel Networks (PCNs).
• Identify fundamental throughput and balance challenges that hinder current PCN routing.
• Propose a packet-switched architecture and a multi-path congestion-control protocol (Spider) to achieve balanced, high-throughput routing.
• Demonstrate through simulations and small-scale implementation that Spider improves throughput and offloads more traffic to PCNs.

Proposed method

• Introduce a packet-switched architecture for PCNs that splits transactions into transaction-units and forwards them over multiple paths and time.
• Develop Spider, a multi-path transport protocol that uses simple congestion signals to balance channel usage and maximize throughput.
• Formulate a fluid NUM-based model of PCN routing with balance and capacity constraints, and analyze circulations vs. DAG demands.
• Propose a practical protocol with router price signals and end-host path probes, inspired by MPTCP-style coupling of multiple paths.
• Validate via packet-level simulations and a small-scale implementation on the LND Lightning Network codebase.

Experimental results

Research questions

• RQ1 How do channel balance and capacity constraints limit throughput in PCNs under traditional routing?
• RQ2 Can packetization and multi-path congestion control significantly improve PCN throughput while maintaining fairness?
• RQ3 What structural demand patterns (circulation vs. DAG) affect maximum achievable throughput in PCNs?
• RQ4 How can decentralizedPrice-based routing achieve balanced utilization of channels in PCNs without excessive on-chain rebalancing?
• RQ5 How does Spider perform relative to state-of-the-art routing under circulation and DAG traffic patterns?

Key findings

• Spider requires less than 25% of the funds to route over 95% of the transactions on circulation demands.
• Spider offloads 7-8x as many transactions onto the PCN for every transaction on the blockchain on DAG demands, a 4x improvement over current approaches.
• Compared to state-of-the-art approaches, Spider completes 1.3-1.8x more of the largest 25% of transactions using a credit card transaction dataset under circulation demands.
• Spider’s network-wide approach achieves high throughput while maintaining fairness across flows.