论文标题
在动态网络中快速分布式共识的分层模型
A Hierarchical Model for Fast Distributed Consensus in Dynamic Networks
论文作者
论文摘要
我们提出了两种针对动态网络的新共识算法。第一个快速筏是筏共识算法的一种变体，可减少典型操作中的消息回合的数量。快速筏是快速节奏的分布式系统的理想选择，其中会员资格会随着时间而变化，并且站点必须迅速达成共识。第二个C-RAFT针对分布式系统，该系统将站点分组为群集，并在群集内进行快速通信，并且簇之间的通信较慢。 C-RAFT使用快速筏作为构建块，并定义了共识的分层模型，以改善全球分布式系统中的吞吐量。我们证明了每种算法的安全性和livesice性能。最后，我们介绍了AWS中两种算法的实验评估。
We present two new consensus algorithms for dynamic networks. The first, Fast Raft, is a variation on the Raft consensus algorithm that reduces the number of message rounds in typical operation. Fast Raft is ideal for fast-paced distributed systems where membership changes over time and where sites must reach consensus quickly. The second, C-Raft, is targeted for distributed systems where sites are grouped into clusters, with fast communication within clusters and slower communication between clusters. C-Raft uses Fast Raft as a building block and defines a hierarchical model of consensus to improve upon throughput in globally distributed systems. We prove the safety and liveness properties of each algorithm. Finally, we present an experimental evaluation of both algorithms in AWS.
