Invention Grant
- Patent Title: Machine learning driven data collection of high-frequency network telemetry for failure prediction
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Application No.: US16402384Application Date: 2019-05-03
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Publication No.: US11258673B2Publication Date: 2022-02-22
- Inventor: Jean-Philippe Vasseur , Grégory Mermoud , Vinay Kumar Kolar
- Applicant: Cisco Technology, Inc.
- Applicant Address: US CA San Jose
- Assignee: Cisco Technology, Inc.
- Current Assignee: Cisco Technology, Inc.
- Current Assignee Address: US CA San Jose
- Agency: Behmke Innovation Group LLC
- Agent Kenneth J. Heywood; James J. Wong
- Main IPC: H04L12/24
- IPC: H04L12/24 ; G06N20/00 ; H04L29/08

Abstract:
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.
Public/Granted literature
- US20200351173A1 MACHINE LEARNING DRIVEN DATA COLLECTION OF HIGH-FREQUENCY NETWORK TELEMETRY FOR FAILURE PREDICTION Public/Granted day:2020-11-05
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