ParBFT: An Optimised Byzantine Consensus Parallelism Scheme

Abstract

Byzantine fault-tolerance (BFT) consensus is a fundamental building block of distributed systems such as blockchains. However, implementations based on classic PBFT and most linear PBFT-variants still suffer from message communication complexity, restricting the scalability and performance of BFT algorithms when serving large-scale systems with growing numbers of peers. To tackle the scalability and performance challenges, we propose ParBFT, a new Byzantine consensus parallelism scheme combining classic BFT protocols and a novel Bilevel Mixed-Integer Linear Programming (BL-MILP)-based optimisation model. The core aim of ParBFT is to improve scalability via parallel consensus while providing enhanced safety (i.e. ensuring consistent total order across all correct replicas). Another core novelty is the integration of the BL-MILP model into ParBFT. The BL-MILP allows us to compute optimal numerical decisions for parallel committees (i.e. the optimal number of committees and peer allocation for each committee) and improve consensus performance while ensuring security. Finally, we test the performance of the proposed ParBFT on Microsoft Azure Cloud systems with 20 to 300 peers and find that ParBFT can achieve significant improvement compared to the state-of-the-art protocols.