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Computer Science > Distributed, Parallel, and Cluster Computing

arXiv:2401.11868 (cs)
[Submitted on 22 Jan 2024]

Title:Self-Balancing Semi-Hierarchical PCNs for CBDCs

Authors:Marco Benedetti, Francesco De Sclavis, Marco Favorito, Giuseppe Galano, Sara Giammusso, Antonio Muci, Matteo Nardelli
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Abstract:We introduce a family of PCNs (Payment Channel Networks) characterized by a semi-hierarchical topology and a custom set of channel rebalancing strategies. This family exhibits two interesting benefits, if used as a platform for large-scale, instant, retail payment systems, such as CBDCs: Technically, the solution offers state-of-the-art guarantees of fault-tolerance and integrity, while providing a latency and throughput comparable to centralized systems; from a business perspective, the solution perfectly suits the 3-tier architecture of the current banking ecosystem (central banks / commercial banks / retail users), assigning a pivotal and peculiar role to the members of each tier. Furthermore, the cryptographic privacy of payments for retail users -- typical of PCNs such as the public Lightning Network -- is largely (possibly fully) retained. We study the system by simulating a scaled-down version of a hypothetical European CBDC, exploring the trade-offs among liquidity locked by market operators, payment success rate, throughput, latency, and load on the underpinning blockchain.
Subjects: Distributed, Parallel, and Cluster Computing (cs.DC)
Report number: CFC.CRYPTO.CS/2024/1
Cite as: arXiv:2401.11868 [cs.DC]
  (or arXiv:2401.11868v1 [cs.DC] for this version)
  https://doi.org/10.48550/arXiv.2401.11868
Related DOI: https://doi.org/10.1109/PerComWorkshops59983.2024.10503409

Submission history

From: Matteo Nardelli [view email]
[v1] Mon, 22 Jan 2024 11:50:02 UTC (3,618 KB)
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