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Camdoop: exploiting in-network aggregation for big data applications
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OSA: an optical switching architecture for data center networks with unprecedented flexibility
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Mirror mirror on the ceiling: flexible wireless links for data centers
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Hey, you darned counters!: get off my ASIC!
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Using CPU as a traffic co-processing unit in commodity switches
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Finishing flows quickly with preemptive scheduling
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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 data centers today. In this paper, we conduct an empirical study of the network traffic in 10 data centers belonging to three different categories, including university, enterprise campus, 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 and link utilizations, 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.