Transactional Dynamics in Hyperledger Fabric: A Stochastic Modeling and Performance Evaluation of Permissioned Blockchains

TL;DR

This paper models transaction flows in Hyperledger Fabric using stochastic methods, providing insights into performance factors and guiding optimization for resource efficiency in permissioned blockchains.

Contribution

It introduces a stochastic Petri Net model for analyzing Hyperledger Fabric, enabling performance evaluation and optimization insights for permissioned blockchain networks.

Findings

Block size impacts throughput and response times significantly.

Sensitivity analysis identifies key factors affecting performance.

Model achieves 95% confidence interval for response times.

Abstract

Blockchain, often integrated with distributed systems and security enhancements, has significant potential in various industries. However, environmental concerns and the efficiency of consortia-controlled permissioned networks remain critical issues. We use a Stochastic Petri Net model to analyze transaction flows in Hyperledger Fabric networks, achieving a 95% confidence interval for response times. This model enables administrators to assess the impact of system changes on resource utilization. Sensitivity analysis reveals major factors influencing response times and throughput. Our case studies demonstrate that block size can alter throughput and response times by up to 200%, underscoring the need for performance optimization with resource efficiency.