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PhD Theses in network performance

Explore the world of network performance in PhD theses by Brighten Godfrey, Srikanth Kandula, Xiaowei Yang, Ming Zhang, Hitesh Ballani, Peter Bodik, Nate Foster, and Craig Labovitz. Discover crucial topics such as network function placement, resource allocation, flow prioritization, and virtual middle-boxes. Delve into the impact of ultra-low latency networks on applications and the role of failures in network resilience. Learn about testing production applications with failure monkeys and configuration checking for optimal system performance.

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PhD Theses in network performance

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  1. PhD Theses in network performance Brighten Godfrey Srikanth Kandula XiaoweiYang Ming Zhang Hitesh Ballani Peter Bodik Nate Foster Craig Labovitz

  2. For data analytics, what network functions are needed, where do you placethem? • (aka: Will Cisco survive?) • (aka: “OpenFlow makes Hadoop faster”) • * Resource allocation/ Flow prioritization/ Network Planning/ virtual middle-boxes

  3. What’s beyond a full bisection bandwidth core? * how big of a full bisection core network would you build or need? * the “edge” * failures

  4. Failures, as a first class citizen? • * No one failure should break the system • * Avoid obfuscating/ amplifying factors • - cascading failures • - load shedding • - TCP

  5. Will ultra-low latency networks change the game? • * One “computer” across many servers • ~ microseconds per hop • e.g., Bing, high frequency trading. Will a new class of apps benefit from ultra low latency? • In network, 2 level priority queues will solve the problem for low latency but not ultra low • Packet-level latency problem: mostly in host stacks? • Network control (e.g., TE) latency more of an issue

  6. Testing Production Applications • A “failure monkey” to “flight” applications end-to-end • * for configuration checking • * for grey failures? • * built-in support for audit

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