使用netstitcher进行数据中心间批量传输

Nikolaos Laoutaris, Michael Sirivianos, Xiaoyuan Yang, P. Rodriguez
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引用次数: 301

摘要

拥有多个站点的大型数据中心运营商根据每个站点覆盖的地理区域的峰值需求来规划其关键资源。特定区域的需求遵循强烈的日模式,峰谷比高,导致一天的平均利用率较低。在本文中,我们将展示如何在多个数据中心和骨干网之间挽救未利用的带宽,并将其用于非实时应用程序,例如备份、大容量更新的传播和数据迁移。实现上述目标并非易事,因为剩余带宽出现在不同的时间、不同的持续时间和世界上不同的地方。为此,我们设计、实现并验证了NetStitcher,这是一个使用存储节点网络将未使用的带宽拼接在一起的系统,无论何时何地都可以使用。它收集有关剩余资源的信息,使用存储转发算法来调度数据传输,并适应资源波动。我们使用测试平台和真实CDN上的实时部署将NetStitcher与其他批量传输机制进行了比较。我们的测试平台评估表明,NetStitcher优于所有其他机制,可以节省多达五倍的额外数据中心带宽,因此使其成为数据中心提供商的有价值的工具。我们的实时CDN部署表明,我们的解决方案可以以比原始的端到端或存储转发方案低得多的成本执行大型数据传输。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Inter-datacenter bulk transfers with netstitcher
Large datacenter operators with sites at multiple locations dimension their key resources according to the peak demand of the geographic area that each site covers. The demand of specific areas follows strong diurnal patterns with high peak to valley ratios that result in poor average utilization across a day. In this paper, we show how to rescue unutilized bandwidth across multiple datacenters and backbone networks and use it for non-real-time applications, such as backups, propagation of bulky updates, and migration of data. Achieving the above is non-trivial since leftover bandwidth appears at different times, for different durations, and at different places in the world. For this purpose, we have designed, implemented, and validated NetStitcher, a system that employs a network of storage nodes to stitch together unutilized bandwidth, whenever and wherever it exists. It gathers information about leftover resources, uses a store-and-forward algorithm to schedule data transfers, and adapts to resource fluctuations. We have compared NetStitcher with other bulk transfer mechanisms using both a testbed and a live deployment on a real CDN. Our testbed evaluation shows that NetStitcher outperforms all other mechanisms and can rescue up to five times additional datacenter bandwidth thus making it a valuable tool for datacenter providers. Our live CDN deployment demonstrates that our solution can perform large data transfers at a much lower cost than naive end-to-end or store-and-forward schemes.
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