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A first look at inter-data center traffic characteristics via Yahoo! datasets

机译:通过Yahoo!首先了解数据中心间的流量特性。资料集

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Effectively managing multiple data centers and their traffic dynamics pose many challenges to their operators, as little is known about the characteristics of inter-data center (D2D) traffic. In this paper we present a first study of D2D traffic characteristics using the anonymized NetFlow datasets collected at the border routers of five major Yahoo! data centers. Our contributions are mainly two-fold: i) we develop novel heuristics to infer the Yahoo! IP addresses and localize their locations from the anonymized NetFlow datasets, and ii) we study and analyze both D2D and client traffic characteristics and the correlations between these two types of traffic. Our study reveals that Yahoo! uses a hierarchical way of deploying data centers, with several satellite data centers distributed in other countries and backbone data centers distributed in US locations. For Yahoo! US data centers, we separate the client-triggered D2D traffic and background D2D traffic from the aggregate D2D traffic using port based correlation, and study their respective characteristics. Our findings shed light on the interplay of multiple data centers and their traffic dynamics within a large content provider, and provide insights to data center designers and operators as well as researchers.
机译:由于对数据中心间(D2D)流量的特征了解甚少,因此有效管理多个数据中心及其流量动态给运营商带来了许多挑战。在本文中,我们使用在五个主要Yahoo!边界路由器收集的匿名NetFlow数据集,对D2D流量特性进行了首次研究。数据中心。我们的贡献主要有两个方面:i)我们开发新颖的启发法来推断Yahoo!。 IP地址并从匿名NetFlow数据集中定位其位置,并且ii)我们研究和分析D2D和客户端流量特征以及这两种流量之间的相关性。我们的研究表明,雅虎!使用分层的数据中心部署方式,几个卫星数据中心分布在其他国家,而骨干数据中心分布在美国。对于Yahoo!在美国数据中心,我们使用基于端口的相关性将客户端触发的D2D流量和后台D2D流量与D2D流量总量分离开来,并研究它们各自的特性。我们的发现揭示了多个数据中心在大型内容提供商中的相互作用及其流量动态,并为数据中心设计人员,运营商以及研究人员提供了见解。

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