首页> 外国专利> MACHINE LEARNING DRIVEN DATA COLLECTION OF HIGH-FREQUENCY NETWORK TELEMETRY FOR FAILURE PREDICTION

MACHINE LEARNING DRIVEN DATA COLLECTION OF HIGH-FREQUENCY NETWORK TELEMETRY FOR FAILURE PREDICTION

机译:高频网络遥测的机器学习驱动数据收集以进行故障预测

摘要

In one embodiment, a supervisory service for one or more networks receives telemetry data samples from a plurality of networking devices in the one or more networks. The service trains a failure prediction model to predict failures in the one or more networks, using a training dataset comprising the received telemetry data samples. The service assesses performance of the failure prediction model. The service trains, based on the assessed performance of the failure prediction model, a machine learning-based classification model to determine whether a networking device should send a particular telemetry data sample to the service. The service sends the machine learning-based classifier to one or more of the plurality of networking devices, to control which telemetry data samples the one or more networking devices send to the supervisory service.
机译:在一实施例中,用于一个或多个网络的管理服务从一个或多个网络中的多个联网设备接收遥测数据样本。该服务使用包含接收到的遥测数据样本的训练数据集训练一个故障预测模型,以预测一个或多个网络中的故障。该服务评估故障预测模型的性能。该服务基于故障预测模型的评估性能来训练基于机器学习的分类模型,以确定网络设备是否应向服务发送特定的遥测数据样本。服务将基于机器学习的分类器发送到多个联网设备中的一个或多个,以控制一个或多个联网设备发送给监管服务的遥测数据样本。

著录项

相似文献

  • 专利
  • 外文文献
  • 中文文献
获取专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号