- Patent Title: Dynamically adjusting sample rates based on performance of a machine-learning based model for performing a network assurance function in a network assurance system
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Application No.: US15831482Application Date: 2017-12-05
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Publication No.: US10691082B2Publication Date: 2020-06-23
- Inventor: Andrea Di Pietro , Jean-Philippe Vasseur , Javier Cruz Mota
- 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 James M. Behmke; Jonathon P. Western
- Main IPC: G05B13/04
- IPC: G05B13/04 ; H04L12/26 ; H04L12/24

Abstract:
In one embodiment, a network assurance service receives data regarding a monitored network. The service analyzes the received data using a machine learning-based model, to perform a network assurance function for the monitored network. The service detects a lowered performance of the machine learning-based model when a performance metric of the machine learning-based model is below a threshold for the performance metric. When it is determined that the lowered performance of the machine-learning based model is correlated with the sample rate of the received data, the service adjusts the sample rate of the data.
Public/Granted literature
- US20190171169A1 DYNAMICALLY ADJUSTING SAMPLE RATES IN A MACHINE LEARNING-BASED NETWORK ASSURANCE SYSTEM Public/Granted day:2019-06-06
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