Optimal Resource Utilization in Hyperledger Fabric: A Comprehensive SPN-Based Performance Evaluation Paradigm
Carlos Melo, Glauber Gonçalves, Francisco A. Silva, Leonel Feitosa, Iure Fé, André Soares, Eunmi Choi, Tuan Anh Nguyen, Dugki Min
TL;DR
The paper addresses pre-deployment performance optimization for Hyperledger Fabric by modeling the execute–order–validate workflow with a Stochastic Petri Net (SPN) that captures endorsement, ordering, and commit phases. It conducts four case studies and a sensitivity analysis to identify bottlenecks and key parameter sensitivities, revealing that block size and timeout critically shape mean response time and discard rates. The SPN framework provides actionable insights for capacity planning and configuration tuning to improve throughput and latency in enterprise blockchain deployments. These results have practical impact for administrators seeking cost-effective, performance-aware configurations of private permissioned blockchains.
Abstract
Hyperledger Fabric stands as a leading framework for permissioned blockchain systems, ensuring data security and auditability for enterprise applications. As applications on this platform grow, understanding its complex configuration concerning various blockchain parameters becomes vital. These configurations significantly affect the system's performance and cost. In this research, we introduce a Stochastic Petri Net (SPN) model to analyze Hyperledger Fabric's performance, considering variations in blockchain parameters, computational resources, and transaction rates. We provide case studies to validate the utility of our model, aiding blockchain administrators in determining optimal configurations for their applications. A key observation from our model highlights the block size's role in system response time. We noted an increased mean response time, between 1 to 25 seconds, due to variations in transaction arrival rates.