Optimizing All-to-All Data Transmission in WANs

Hao Hao Tan
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Abstract

All-to-all data transmission is a typical data transmission pattern in both consensus protocols and blockchain systems. Developing an optimization scheme that provides high throughput and low latency data transmission can significantly benefit the performance of those systems. This paper investigates the problem of optimizing all-to-all data transmission in a wide area network (WAN) using overlay multicast. We prove that in a hose network model, using shallow tree overlays with height up to two is sufficient for all-to-all data transmission to achieve the optimal throughput allowed by the available network resources. Upon this foundation, we build ShallowForest, a data plane optimization for consensus protocols and blockchain systems. The goal of ShallowForest is to improve consensus protocols’ resilience to skewed client load distribution. Experiments with skewed client load across replicas in the Amazon cloud demonstrate that ShallowForest can improve the commit throughput of the EPaxos consensus protocol by up to 100% with up to 60% reduction in commit latency.
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优化广域网中全对全数据传输
All-to-all数据传输是共识协议和区块链系统中典型的数据传输模式。开发一种提供高吞吐量和低延迟数据传输的优化方案可以显著提高这些系统的性能。本文研究了利用覆盖组播优化广域网中全对全数据传输的问题。我们证明了在软管网络模型中,使用高度高达2的浅树覆盖足以实现所有到所有数据传输,以实现可用网络资源允许的最佳吞吐量。在此基础上,我们构建了shalowforest,这是一个针对共识协议和区块链系统的数据平面优化。ShallowForest的目标是提高共识协议对倾斜客户端负载分布的弹性。在Amazon云中跨副本的倾斜客户端负载实验表明,ShallowForest可以将EPaxos共识协议的提交吞吐量提高100%,同时将提交延迟减少60%。
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