A Comprehensive Hyperledger Fabric Performance Evaluation based on Resources Capacity Planning

TL;DR

This paper models Hyperledger Fabric's performance using a Stochastic Petri Net to guide resource capacity planning, helping optimize configurations for better performance and cost-efficiency.

Contribution

It introduces a novel performance modeling approach for Hyperledger Fabric based on stochastic Petri nets, incorporating various blockchain parameters and resource capacities.

Findings

Identified block size impacts mean response time significantly.

Model helps determine optimal resource configurations.

Response times ranged from 1 to 25 seconds depending on parameters.

Abstract

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.