Chaos Engineering For Understanding Consensus Algorithms Performance in Permissioned Blockchains

TL;DR

This paper explores how chaos engineering can be used to evaluate the performance and reliability of different consensus algorithms in permissioned blockchains under various failure scenarios.

Contribution

It introduces a novel application of chaos engineering to test and analyze the robustness of consensus algorithms in blockchain networks.

Findings

Chaos engineering reveals performance limitations of consensus algorithms under failures.

Different algorithms show varied throughput and latency in hostile environments.

Chaos testing helps identify reliability issues in blockchain platforms.

Abstract

A critical component of any blockchain or distributed ledger technology (DLT) platform is the consensus algorithm. Blockchain consensus algorithms are the primary vehicle for the nodes within a blockchain network to reach an agreement. In recent years, many blockchain consensus algorithms have been proposed mainly for private and permissioned blockchain networks. However, the performance of these algorithms and their reliability in hostile environments or the presence of byzantine and other network failures are not well understood. In addition, the testing and validation of blockchain applications come with many technical challenges. In this paper, we apply chaos engineering and testing to understand the performance of consensus algorithms in the presence of different loads, byzantine failure and other communication failure scenarios. We apply chaos engineering to evaluate the performance of three different consensus algorithms (PBFT, Clique, Raft) and their respective blockchain platforms. We measure the blockchain network's throughput, latency, and success rate while executing chaos and load tests. We develop lightweight blockchain applications to execute our test in a semi-production environment. Our results show that using chaos engineering helps understand how different consensus algorithms perform in a hostile or unreliable environment and the limitations of blockchain platforms. Our work demonstrates the benefits of using chaos engineering in testing complex distributed systems such as blockchain networks.