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TRAFFIC-BASED INFERENCE OF INFLUENCE DOMAINS IN A NETWORK BY USING LEARNING MACHINES

机译:基于学习器的网络中交通影响域推理

摘要

In one embodiment, techniques are shown and described relating to traffic-based inference of influence domains in a network by using learning machines. In particular, in one embodiment, a management device computes a time-based traffic matrix indicating traffic between pairs of transmitter and receiver nodes in a computer network, and also determines a time-based quality parameter for a particular node in the computer network. By correlating the time-based traffic matrix and time-based quality parameter for the particular node, the device may then determine an influence of particular traffic of the traffic matrix on the particular node.
机译:在一个实施例中,示出和描述了与通过使用学习机在网络中影响域的基于流量的推断有关的技术。特别地,在一个实施例中,管理设备计算指示计算机网络中的发送器和接收器节点对之间的业务的基于时间的业务矩阵,并且还为计算机网络中的特定节点确定基于时间的质量参数。通过将特定节点的基于时间的流量矩阵和基于时间的质量参数相关联,设备可以确定流量矩阵的特定流量对特定节点的影响。

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