DAG-Sword: A Simulator of Large-Scale Network Topologies for DAG-Oriented Proof-of-Work Blockchains

dc.contributor.author Perešíni, Martin
dc.contributor.author Hladký, Tomáš
dc.contributor.author Malinka, Kamil
dc.contributor.author Homoliak, Ivan
dc.date.accessioned 2023-12-26T18:48:25Z
dc.date.available 2023-12-26T18:48:25Z
dc.date.issued 2024-01-03
dc.identifier.isbn 978-0-9981331-7-1
dc.identifier.other 3c16f75b-4c90-4f5f-9b4e-8330736ad39c
dc.identifier.uri https://hdl.handle.net/10125/107101
dc.language.iso eng
dc.relation.ispartof Proceedings of the 57th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Blockchain Cases and Innovations
dc.title DAG-Sword: A Simulator of Large-Scale Network Topologies for DAG-Oriented Proof-of-Work Blockchains
dc.type Conference Paper
dc.type.dcmi Text
dcterms.abstract The blockchain brought interesting properties for many practical applications. However, some properties, such as the transaction processing throughput remained limited, especially in Proof-of-Work blockchains. Therefore, several promising directions, such as sharding designs and DAG-based protocols emerged. In this paper, we focus on DAG-based consensus protocols and present a discrete-event simulator for them. Our simulator can simulate realistic blockchain networks created from data of a Bitcoin network, while its network configuration and topology can be customized. The simulated network consists of honest and malicious miners. Malicious miners do not make any attack on consensus itself. Instead, they use a different transaction selection strategy than honest miners (who select transactions randomly) with the intention to earn unfairly more profits than honest miners at the cost of downgrading the protocol performance by duplicate transactions. As a consequence, this harms the performance of some DAG-based protocols (e.g., PHANTOM and GHOSTDAG) in terms of transaction processing throughput, which we demonstrate in our experiments and extend the results of the related work that contains a small-scale network of 10 nodes by the results obtained on a large-scale network with 7000 nodes. Next, we empirically compare different algorithms for the mempool structure, and we propose a composite mempool structure that is memory-efficient and thus convenient for simulations of resource-demanding large-scale networks.
dcterms.extent 10 pages
prism.startingpage 5960
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