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Network Traffic Characteristics of Data Centers in the Wild

机译:野外数据中心的网络流量特性

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Although there is tremendous interest in designing improved networks for data centers, very little is known about the network-level traffic characteristics of current data centers. In this paper, we conduct an empirical study of the network traffic in 10 data centers belonging to three different types of organizations, including university, enterprise, and cloud data centers. Our definition of cloud data centers includes not only data centers employed by large online service providers offering Internet-facing applications, but also data centers used to host data-intensive (MapReduce style) applications. We collect and analyze SNMP statistics, topology, and packet-level traces. We examine the range of applications deployed in these data centers and their placement, the flow-level and packet-level transmission properties of these applications, and their impact on network utilization, link utilization, congestion, and packet drops. We describe the implications of the observed traffic patterns for data center internal traffic engineering as well as for recently-proposed architectures for data center networks.
机译:尽管为数据中心设计改进的网络引起了极大的兴趣,但对当前数据中心的网络级流量特性知之甚少。在本文中,我们对属于三个不同类型组织的10个数据中心的网络流量进行了实证研究,包括大学,企业和云数据中心。我们对云数据中心的定义不仅包括提供面向Internet的应用程序的大型在线服务提供商使用的数据中心,还包括用于托管数据密集型(MapReduce样式)应用程序的数据中心。我们收集并分析SNMP统计信息,拓扑和数据包级跟踪。我们检查了在这些数据中心中部署的应用程序范围及其位置,这些应用程序的流级别和数据包级别传输属性,以及它们对网络利用率,链路利用率,拥塞和数据包丢弃的影响。我们描述了观察到的流量模式对数据中心内部流量工程以及最近提出的数据中心网络体系结构的影响。

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