Committee Configuration Optimization for Parallel Byzantine Consensus in a Trusted Execution Environment

2026-03-15

AI Summary

This work addresses the trade-off between scalability and security in existing committee-based sharded parallel Byzantine Fault Tolerance (BFT) protocols, where random committee assignment further limits performance. The paper introduces, for the first time, an optimization-driven committee configuration approach for trusted parallel BFT systems, formulating a mixed-integer programming model that jointly considers node failure rates and communication latency to minimize transaction latency under both normal operation and trusted hardware failure scenarios. By integrating Trusted Execution Environments (TEEs), committee sharding, and parallel BFT mechanisms, the proposed method achieves significant performance gains: experiments on Microsoft Azure virtual machines demonstrate throughput improvements of 15% and 21% over baseline protocols in normal and fallback modes, respectively, while maintaining strong security, scalability, and efficiency.

Technology Category

• Data Mining & Knowledge Management: Scalability, Parallel & Distributed Systems
• Machine Learning: Hardware-aware ML
• Search and Optimization: Distributed Search

Application Category

• Security and Privacy: Large-scale security measurements
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Responsible Web: Data and user privacy-enhancing technologies for the Web

Abstract

Parallel Byzantine Fault Tolerant (BFT) protocols based on committee-based sharding improve scalability but weaken safety since smaller node groups are responsible for consensus. Recent approaches integrate trusted execution environments (TEEs) into parallel BFT frameworks to enhance safety. While the scalability and safety issues are addressed by trusted parallel BFT, existing committee configuration methods often rely on randomized assignment, which can degrade performance. This paper proposes a committee configuration optimization (CCO) model based on mixed integer programming to improve transaction performance for trusted parallel BFT. The model considers communication delays and node failure rates to determine an optimal committee configuration that minimizes transaction latency under both normal operations and scenarios of trusted hardware failures. We integrate CCO into a trusted parallel BFT protocol and evaluate the performance on Microsoft virtual machines. Experimental results demonstrate 15% and 21% improved transaction throughput under normal operations and fallback process, respectively, highlighting the benefits of optimization-driven committee configuration in trusted parallel BFT systems.

Problem

• Committee Configuration
• Parallel Byzantine Consensus
• Trusted Execution Environment
• Transaction Latency
• Scalability

Innovation

• Committee Configuration Optimization
• Trusted Execution Environment
• Parallel Byzantine Fault Tolerance
• Mixed Integer Programming
• Scalable Consensus