Facing to Latency of Hyperledger Fabric for Blockchain-enabled IoT: Modeling and Analysis

TL;DR

This paper models and analyzes the latency in Hyperledger Fabric for IoT applications, providing a Gamma distribution-based latency model and insights on parameter impacts to optimize performance.

Contribution

It establishes a practical latency model for HLF-enabled IoT, validated by real implementation and goodness-of-fit tests, with analysis of key parameter effects.

Findings

Total latency follows a Gamma distribution.

Parameter values vary with different HLF environments.

Transaction rate, block size, and timeout significantly affect latency.

Abstract

Hyperledger Fabric (HLF), one of the most popular private blockchains, has recently received attention for blockchain-enabled Internet of Things (IoT). However, for IoT applications to handle time-sensitive data, the processing latency in HLF has emerged as a new challenge. In this article, therefore, we establish a practical HLF latency model for HLF-enabled IoT. We first discuss the structure and transaction flow of HLF-enabled IoT. After implementing real HLF, we capture the latencies that each transaction experiences and show that the total latency of HLF can be modeled as a Gamma distribution, which is validated by conducting a goodness-of-fit test (i.e., the Kolmogorov-Smirnov (KS) test). We also provide the parameter values of the modeled latency distribution for various HLF environments. Furthermore, we explore the impacts of three important HLF parameters including transaction generation rate, block size, and block-generation timeout on the HLF latency. As a result, this article provides design insights on minimizing the latency for HLF-enabled IoT.