HYDRA: Breaking the Global Ordering Barrier in Multi-BFT Consensus

2025-11-08

AI Summary

Existing multi-Byzantine fault-tolerant (Multi-BFT) consensus protocols rely on a global ordering layer to serialize cross-instance blocks, resulting in poor scalability, widespread fault propagation, and complex deployment. This paper proposes the first global-ordering-free Multi-BFT framework, introducing an object-centric execution model that integrates fine-grained transaction partitioning, parallel BFT across multiple instances, lightweight lock-based coordination, and proactive deadlock recovery—ensuring strong consistency while significantly enhancing concurrency. Experimental evaluation demonstrates that, under both LAN and WAN settings with 128 replicas, our framework achieves 1.3×–2.8× higher throughput than state-of-the-art approaches including State Machine Replication and HotStuff-Multi. Moreover, it exhibits superior robustness against high-latency nodes.

Technology Category

• Data Mining & Knowledge Management: Scalability, Parallel & Distributed Systems
• Multiagent Systems: Other Foundations of Multi Agent Systems
• Machine Learning: Scalability of ML Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Security and Privacy: Large-scale security measurements
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines

Abstract

Multi-Byzantine Fault Tolerant (Multi-BFT) consensus, which runs multiple BFT instances in parallel, has recently emerged as a promising approach to overcome the leader bottleneck in classical BFT protocols. However, existing designs rely on a global ordering layer to serialize blocks across instances, an intuitive yet costly mechanism that constrains scalability, amplifies failure propagation, and complicates deployment. In this paper, we challenge this conventional wisdom. We present HYDRA, the first Multi-BFT consensus framework that eliminates global ordering altogether. HYDRA introduces an object-centric execution model that partitions transactions by their accessed objects, enabling concurrent yet deterministic execution across instances. To ensure consistency, HYDRA combines lightweight lock-based coordination with a deadlock resolution mechanism, achieving both scalability and correctness. We implement HYDRA and evaluate it on up to 128 replicas in both LAN and WAN environments. Experimental results show HYDRA outperforms several state-of-the-art Multi-BFT protocols in the presence of a straggler. These results demonstrate strong consistency and high performance by removing global ordering, opening a new direction toward scalable Multi-BFT consensus design.

Problem

• Eliminating global ordering in Multi-BFT consensus
• Enabling concurrent deterministic execution across instances
• Achieving scalability and consistency without serialization

Innovation

• Eliminates global ordering in Multi-BFT consensus
• Uses object-centric execution for transaction partitioning
• Combines lock-based coordination with deadlock resolution