文件名称:
Why (and How) Networks Should Run Themselves
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文件大小: 178kb
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上传时间: 2017-12-13
详细说明： The proliferation of networked devices, systems, and appli- cations that we depend on every day makes managing net- works more important than ever. The increasing security, availability, and performance demands of these applications suggest that these increasing ly difficult network management problems be solved in real time, across a complex web of interacting protocols and systems. Alas, just as the impor- tance of network management has increased, the network has grown so complex that it is seemingly unmanageable. In this new era, network management requires a fundamentally new approach. Instead of optimizations based on closed-form analysis of individual protocols, network operators need data- driven, machine-learning-based models of end-to-end and application performance based on high-level policy goals and a holistic view of the underlying components. Instead of anomaly detection algorithms that operate on offline analysis of network traces, operators need classification and detec- tion algorithms that can make real-time, closed-loop deci- sions. Networks should learn to drive themselves. This paper explores this concept, discussing how we might attain this ambitious goal by more closely coupling measurement with real-time control and by relying on learning for inference and prediction about a networked application or system, as opposed to closed-form analysis of individual protocols. ...展开收缩
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