Performance Modeling and Analysis of Hotstuff for Blockchain Consensus

Abstract

Byzantine Fault-Tolerant (BFT) protocols are classical algorithms that offer a faster and more energy-efficient consensus mechanism compared to Proof-of-Work (PoW), which is typically used by cryptocurrencies such as Bitcoin. Synchronous BFT systems are hard to implement and vulnerable to attacks that aim to disrupt the synchrony of the system. Practical BFT (PBFT), which is a partially synchronous protocol, is a high-performance consensus algorithm that provides strong safety in the presence of a bounded number of faulty participants. Hotstuff is one such partially synchronous BFT State Machine Replication (SMR) protocol that aims to address the aforementioned issues. PBFT is becoming a popular choice for blockchain consensus, especially in permissioned systems (e.g. Ripple, Stellar, etc). However, it is not well understood how Hotstuff, and PBFT consensus in general, behave under varying conditions that are commonly found in blockchain networks. In this paper, we present a theoretical model for the Hotstuff consensus mechanism which accurately predicts blockchain-related metrics such as the transaction throughput and expected confirmation time using important networking parameters such as the number of replicas, link latency, and packet loss. Furthermore, we validate our model through extensive simulations carried out using OMNeT++. Our results show that Hotstuff performance degrades drastically when the number of replicas increases. We observe that with a maximum number of tolerable faulty nodes, when the number of validators is increased to 127, throughput tends to zero. As well, packet loss ratio and transaction processing time are two other factors that significantly affect the performance of Hotstuff.