Reference : An in-depth investigation of the performance characteristics of Hyperledger Fabric
Scientific journals : Article
Engineering, computing & technology : Computer science
Business & economic sciences : Production, distribution & supply chain management
Computational Sciences; Security, Reliability and Trust
http://hdl.handle.net/10993/52648
An in-depth investigation of the performance characteristics of Hyperledger Fabric
English
Guggenberger, Tobias mailto [FIM Research Center, University of Bayreuth]
Sedlmeir, Johannes mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > FINATRAX >]
Fridgen, Gilbert mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > FINATRAX >]
Luckow, André mailto [BMW Group, Munich]
Nov-2022
Computers and Industrial Engineering
Elsevier
173
Blockchain-based applications for enhancing cybersecurity in manufacturing and building supply chain resilience
Yes
International
0360-8352
1879-0550
Oxford
United Kingdom
[en] Benchmarking ; Blockchain ; Distributed Ledger ; Scalability ; Supply Chain ; Throughput
[en] Private permissioned blockchains are deployed in ever greater numbers to facilitate cross-organizational processes in various industries, particularly in supply chain management. One popular example of this trend is Hyperledger Fabric. Compared to public permissionless blockchains, it promises improved performance and provides certain features that address key requirements of enterprises. However, also permissioned blockchains are still not as scalable as centralized systems, and due to the scarcity of theoretical results and empirical data, their real-world performance cannot be predicted with the necessary precision. We intend to address this issue by conducting an in-depth performance analysis of Hyperledger Fabric. The paper presents a detailed compilation of various performance characteristics using an enhanced version of the Distributed Ledger Performance Scan (DLPS). Researchers and practitioners alike can use the various performance properties identified and discussed as guidelines to better configure and implement their Hyperledger Fabric network. Likewise, they are encouraged to use the DLPS framework to conduct their measurements.
Fonds National de la Recherche - FnR ; Paypal
FiReSpARX
Researchers ; Professionals
http://hdl.handle.net/10993/52648
10.1016/j.cie.2022.108716
https://www.sciencedirect.com/science/article/pii/S0360835222007045
This article is published under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
FnR ; FNR14783405 > Gilbert Fridgen > FiReSpARX > Fintech/Regtech In Space For Trustful Autonomous Robotic Interaction > 01/07/2021 > 30/06/2024 > 2020

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