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[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.
Disciplines :
Computer science Production, distribution & supply chain management
Author, co-author :
Guggenberger, Tobias; FIM Research Center, University of Bayreuth
SEDLMEIR, Johannes ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > FINATRAX
FRIDGEN, Gilbert ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > FINATRAX
Luckow, André; BMW Group, Munich
External co-authors :
yes
Language :
English
Title :
An in-depth investigation of the performance characteristics of Hyperledger Fabric
Publication date :
November 2022
Journal title :
Computers and Industrial Engineering
ISSN :
0360-8352
eISSN :
1879-0550
Publisher :
Elsevier, Oxford, United Kingdom
Special issue title :
Blockchain-based applications for enhancing cybersecurity in manufacturing and building supply chain resilience
Volume :
173
Peer reviewed :
Peer Reviewed verified by ORBi
Focus Area :
Computational Sciences Security, Reliability and Trust
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