A comprehensive hyperledger fabric performance evaluation based on resources capacity planning

• Published in: Cluster computing Vol. 27; no. 9; pp. 12395 - 12410
• Main Authors: Melo, Carlos, Gonçalves, Glauber, Silva, Francisco A., Soares, André
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.12.2024; Springer Nature B.V
• Subjects: Blockchain; Business metrics; Case studies; Computer Communication Networks; Computer Science; Configuration management; Costs; Cryptography; Cybersecurity; Data storage; Design of experiments; Feasibility studies; Infrastructure; Markov analysis; Operating Systems; Parameter identification; Peer to peer computing; Performance evaluation; Petri nets; Processor Architectures; Queuing; Response time; Sensitivity analysis; Simulation; Performance; Capacity; Blockchain; Petri net
• ISSN: 1386-7857; 1573-7543
• DOI: 10.1007/s10586-024-04591-4

Hyperledger Fabric is a platform for permissioned blockchain networks that enables secure and auditable distributed data storage for enterprise applications. There is a growing interest in applications based on this platform, but its use requires the configuration of different blockchain parameters. Various configurations impact the system’s non-functional qualities, especially performance and cost. In this article, we propose a Stochastic Petri Net to model the performance of the Hyperledger Fabric platform with different blockchain parameters, computer capacity, and transaction rates. We also present a set of case studies to demonstrate the feasibility of the proposed model. This model serves as a practical guide to help administrators of permissioned blockchain networks find the best performance for their applications. The proposed model allowed us to identify the block size that leads to a high mean response time (ranging from 1 to 25 seconds) caused by a change in the arrival rate.