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Hybrid electro-optical intra-data center networks tailored for different traffic classes

机译:针对不同流量类别量身定制的混合型电光内部数据中心网络

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摘要

This work presents a novel approach in intradata center network design and performance evaluation, based on a tailored, long-range dependence data traffic generation model for different application classes. We examine how an intra-data center network can be efficiently evaluated and optimized by applying accurate models for machine-generated data and using assumptions on current and future commercially available data center hardware. Moreover, we show that by migrating such a Fat-Tree network to its hybrid, electro-optical counterpart by employing optical circuit switching for selected, intense traffic connections, significant capital and operational expenditure cost savings can be obtained.
机译:这项工作基于针对不同应用程序类别的量身定制的远程相关数据流量生成模型,提出了一种在数据中心内部网络设计和性能评估中的新颖方法。我们研究了如何通过对机器生成的数据应用准确的模型以及对当前和将来的商用数据中心硬件的假设,来有效地评估和优化数据中心内部网络。此外,我们表明,通过将光学树状开关用于选定的密集交通连接,将此类Fat-Tree网络迁移到其混合电光对等方,可以节省大量的资金和运营支出。

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