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Characterizing Performance Limits in Payment Channel Networks

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With their instant transaction confirmation and high scalability, payment channel networks (PCNs), running off-chain and in parallel with blockchain systems, have recently attracted a substantial amount of research attention. It… Click to show full abstract

With their instant transaction confirmation and high scalability, payment channel networks (PCNs), running off-chain and in parallel with blockchain systems, have recently attracted a substantial amount of research attention. It has been shown that there exists a significant gap between the theoretically optimal performance and the performance achievable given the stringent privacy requirements in practice. However, it remains unclear what the fundamental performance limits and key factors involved are, which turns out to be a challenging problem due to the unique characteristics in PCNs. In this paper, we, for the first time, develop a mathematical model capturing the PCN performance, and examine the impact from a number of factors including channel capacity and transactions. We are articularly interested in obtaining the gap between the theoretically optimal performance and the performance achievable in practice, which characterizes the design space in PCNs for scheduling transactions. Specifically, we derive how different transactions and channel capacities affect the PCN performance and the performance gap. Our analytical characterization of PCNs offers an in-depth understanding on their fundamental trade-off, and provides important insights on the design of PCNs.

Keywords: channel networks; performance limits; payment channel; channel; performance

Journal Title: IEEE Transactions on Knowledge and Data Engineering
Year Published: 2023

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