Skyplane: Optimizing Transfer Cost and Throughput Using Cloud-Aware Overlays

Paras Jain, Sam Kumar, Sarah Wooders, Shishir G. Patil, Joseph Gonzalez, I. Stoica
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引用次数: 9

Abstract

Cloud applications are increasingly distributing data across multiple regions and cloud providers. Unfortunately, wide-area bulk data transfers are often slow, bottlenecking applications. We demonstrate that it is possible to significantly improve inter-region cloud bulk transfer throughput by adapting network overlays to the cloud setting -- that is, by routing data through indirect paths at the application layer. However, directly applying network overlays in this setting can result in unacceptable increases in cloud egress prices. We present Skyplane, a system for bulk data transfer between cloud object stores that uses cloud-aware network overlays to optimally navigate the trade-off between price and performance. Skyplane's planner uses mixed-integer linear programming to determine the optimal overlay path and resource allocation for data transfer, subject to user-provided constraints on price or performance. Skyplane outperforms public cloud transfer services by up to $4.6\times$ for transfers within one cloud and by up to $5.0\times$ across clouds.
Skyplane:使用云感知覆盖优化传输成本和吞吐量
云应用程序越来越多地跨多个区域和云提供商分发数据。不幸的是,广域批量数据传输通常是缓慢的,是应用程序的瓶颈。我们证明,通过使网络覆盖适应云设置,即通过应用程序层的间接路径路由数据,可以显著提高区域间云批量传输吞吐量。但是,在此设置中直接应用网络覆盖可能会导致云出口价格的不可接受的增长。我们提出了Skyplane,一个用于云对象存储之间批量数据传输的系统,它使用云感知网络覆盖来优化价格和性能之间的权衡。Skyplane的规划器使用混合整数线性规划来确定数据传输的最佳覆盖路径和资源分配,并受用户提供的价格或性能约束。Skyplane在一个云中传输的性能比公共云传输服务高出4.6美元,跨云传输的性能高出5.0美元。
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