It's not a lie if you don't get caught: simplifying reconfiguration in SMR through dirty logs

2026-02-10

AI Summary

This work addresses the tight coupling between reconfiguration mechanisms and consensus protocols in existing state machine replication (SMR) systems, which hinders independent component upgrades and incurs significant downtime. To overcome this limitation, the authors propose Gauss, a reconfiguration engine that decouples the internal consensus log from an externally exposed clean log through a dual-log architecture. This separation enables modular evolution of membership changes, fault-tolerance thresholds, and even the underlying consensus protocol itself. By isolating reconfiguration logic from consensus execution, Gauss substantially reduces system maintenance complexity and supports seamless, independent upgrades of individual components. Evaluation on the Rialto blockchain platform demonstrates that Gauss facilitates near-zero-downtime transitions between different consensus protocols, achieving highly available and adaptable SMR deployments.

Technology Category

• Multiagent Systems: Coordination and Collaboration
• Machine Learning: Hardware-aware ML
• Search and Optimization: Distributed Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Decentralized Web and Fediverse systems
• Security and Privacy: Blockchains and distributed ledgers
• Search and Retrieval-Augmented AI: Retrieval-Augmented Generation (RAG) and multi-modal RAG

Abstract

Production state-machine replication (SMR) implementations are complex, multi-layered architectures comprising data dissemination, ordering, execution, and reconfiguration components. Existing research consensus protocols rarely discuss reconfiguration. Those that do tightly couple membership changes to a specific algorithm. This prevents the independent upgrade of individual building blocks and forces expensive downtime when transitioning to new protocol implementations. Instead, modularity is essential for maintainability and system evolution in production deployments. We present Gauss, a reconfiguration engine designed to treat consensus protocols as interchangeable modules. By introducing a distinction between a consensus protocol's inner log and a sanitized outer log exposed to the RSM node, Gauss allows engineers to upgrade membership, failure thresholds, and the consensus protocol itself independently and with minimal global downtime. Our initial evaluation on the Rialo blockchain shows that this separation of concerns enables a seamless evolution of the SMR stack across a sequence of diverse protocol implementations.

Problem

• state-machine replication
• reconfiguration
• modularity
• consensus protocols
• system evolution

Innovation

• modular reconfiguration
• state-machine replication
• log sanitization
• consensus protocol interchangeability
• zero-downtime upgrades