Flamingo：基于DAG的共识协议中的负载均衡

中文摘要 AI 辅助

部署在不可信环境中的分布式数据管理系统依赖拜占庭容错（BFT）共识协议来容忍恶意故障。基于DAG的BFT协议通过让验证者并发传播交易并在多个工作节点上扩展执行来提高吞吐量。然而，工作负载或资源容量的不平衡仍可能显著降低性能。本文提出Flamingo，一种用于认证的基于DAG的BFT协议的负载均衡协议，它解决了排序层和执行层的不平衡问题。在排序层，Flamingo定期将客户账户从过载的验证者迁移出去，适应倾斜的提交和异构的验证者容量，同时在拜占庭故障下保持正确性，迁移仅通过已提交的日志生效。在执行层，Flamingo使用确定性、保序的调度器在多个执行工作节点间重新分配已提交的交易，平衡负载并最小化跨工作节点的数据移动，无需集中协调或昂贵的分布式提交。基于Narwhal和Tusk构建的原型表明，Flamingo在工作负载倾斜、验证者异构和热点迁移下恢复吞吐量和延迟，在系统均衡时增加的开销可忽略不计，并且需要两个层的负载均衡，因为仅解决一个层会将瓶颈转移到另一个层。

英文摘要

Distributed data management systems deployed in untrusted environments rely on Byzantine Fault-Tolerant (BFT) consensus protocols to tolerate malicious failures. DAG-based BFT protocols improve throughput by letting validators disseminate transactions concurrently and by scaling execution across multiple workers. However, imbalances in workload or resource capacity can still degrade performance significantly. This paper presents Flamingo, a load-balancing protocol for certified DAG-based BFT protocols that addresses imbalance at both the ordering and execution layers. At the ordering layer, Flamingo periodically migrates client accounts away from overloaded validators, adapting to skewed submissions and heterogeneous validator capacity while preserving correctness under Byzantine faults, with migrations taking effect only through the committed log. At the execution layer, Flamingo redistributes committed transactions across executor workers using a deterministic, order-preserving scheduler that balances load and minimizes cross-worker data movement, without centralized coordination or costly distributed commit. Built on top of Narwhal and Tusk, our prototype shows that Flamingo recovers throughput and latency under workload skew, validator heterogeneity, and shifting hotspots, adds negligible overhead when the system is balanced, and needs load balancing in both layers, since resolving only one shifts the bottleneck to the other.

发表机构

• University of Pennsylvania（宾夕法尼亚大学）
• Apple（苹果公司）
• Stony Brook University（石溪大学）

机构由 AI 辅助整理，请以论文原文为准。