Performance Analysis of the Raft Consensus Algorithm for Private Blockchains

TL;DR

This paper analyzes the performance of the Raft consensus algorithm in private blockchain networks with packet loss, providing an analytical model to predict network split probability and optimize parameters.

Contribution

It introduces a simple, accurate analytical model for network split probability in Raft under packet loss, validated by simulation results.

Findings

Network split probability depends on network size, packet loss rate, and election timeout.

The analytical model accurately predicts network split time and probability.

Simulation results confirm the model's validity.

Abstract

Consensus is one of the key problems in blockchains. There are many articles analyzing the performance of threat models for blockchains. But the network stability seems lack of attention, which in fact affects the blockchain performance. This paper studies the performance of a well adopted consensus algorithm, Raft, in networks with non-negligible packet loss rate. In particular, we propose a simple but accurate analytical model to analyze the distributed network split probability. At a given time, we explicitly present the network split probability as a function of the network size, the packet loss rate, and the election timeout period. To validate our analysis, we implement a Raft simulator and the simulation results coincide with the analytical results. With the proposed model, one can predict the network split time and probability in theory and optimize the parameters in Raft consensus algorithm.