🤖 AI Summary
This work addresses the throughput degradation of crash-fault tolerant (CFT) consensus protocols in wide-area networks caused by single-leader bottlenecks and network latency. The authors propose a novel multi-leader CFT consensus protocol based on a causally ordered directed acyclic graph (DAG), which, for the first time, decouples command dissemination from consensus logic. By integrating a multi-leader architecture with a deterministic delayed execution mechanism, the protocol enables automatic command scheduling and achieves commitment within two communication hops. Experimental results demonstrate that the proposed approach significantly improves throughput in wide-area deployments while maintaining low commit latency, offering a practical solution that combines high performance, strong resilience, and deployment feasibility.
📝 Abstract
This paper introduces Nemo-Nemo, a practical crash-fault tolerant (CFT) consensus protocol designed to outperform existing protocols in wide-area networks by bridging design principles from the CFT and Byzantine-fault tolerant (BFT) worlds. By structuring command propagation through a causally ordered DAG, Nemo-Nemo allows all consensus replicas to propose commands with a naturally self-regulating communication regime. By exploiting multi-leader architecture, Nemo-Nemo avoids the performance bottleneck inherent to single-leader protocols. By separating command dissemination from consensus logic, Nemo-Nemo handles challenging network conditions even when consensus commits are stalled. Moreover, leader proposals that miss a deadline are never dropped, but deterministically deferred and executed later, preserving throughput under transient network delays. And by enabling Nemo-Nemo to commit on a DAG in just two network hops, it matches the latency of existing CFT systems, while achieving significantly higher throughput. The result is a robust, deployable system: the first DAG-based CFT consensus protocol proven to exceed state-of-the-art wide-area network performance in both speed and resilience.