Path planning in payment channel networks with multi-party channels

Corcoran, Padraig ORCID: https://orcid.org/0000-0001-9731-3385 and Lewis, Rhydian ORCID: https://orcid.org/0000-0003-1046-811X 2024. Path planning in payment channel networks with multi-party channels. Distributed Ledger Technologies: Research and Practice 10.1145/3702248

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Abstract

Payment Channel Networks (PCNs) provide a means to improve the scaling of cryptocurrency payments by allowing peers to make payments between themselves in an efficient manner. To make a payment between two peers, the task of path planning must first be performed to determine a path in the PCN connecting the peers in question before the payment in question is performed using this path. To date, existing research has focused on the problem of performing path planning in PCNs that contain two-party channels. It has been hypothesised that the scaling of PCNs could be further improved by considering the inclusion of multi-party channels that contain more than two peers. However, the problem of performing path planning in PCNs that contain multi-party channels has not yet been considered. In this article, we address this gap in the research literature and propose a novel path planning method for PCNs containing multi-party channels. This method involves modelling the PCN with multi-party channels as a hypergraph, a type of graph where edges can contain two or more vertices, and using this model to solve the path planning problem in question. We prove that the proposed method is correct and computationally efficient. Furthermore, assuming path planning is performed using this method, we also present theoretical and experimental analyses that demonstrate the scaling benefits of using multi-party channels.

Item Type:	Article
Date Type:	Published Online
Status:	In Press
Schools:	Computer Science & Informatics Mathematics
Publisher:	Association for Computing Machinery (ACM)
Date of First Compliant Deposit:	29 October 2024
Date of Acceptance:	1 October 2024
Last Modified:	07 Nov 2024 07:45
URI:	https://orca.cardiff.ac.uk/id/eprint/172779

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