公开(公告)号：US11979298B1

公开(公告)日：2024-05-07

申请号：US18209803

申请日：2023-06-14

Applicant: Cisco Technology, Inc.

Inventor： Grégory Mermoud ,  Jean-Philippe Vasseur ,  Romain Kakko-Chiloff ,  Pierre-André Savalle

IPC: G06F16/9035 ,  G06F16/28 ,  H04L41/16 ,  H04L41/5009 ,  H04L51/02

CPC classification number: H04L41/5009 ,  H04L41/16 ,  H04L51/02

Abstract: In one embodiment, a device trains, using feedback from a reference cohort of users of an online application, a prediction model to predict a quality of experience metric for the online application based on network telemetry. The device uses the prediction model to predict quality of experience metrics for different cohorts of users of the online application. The device makes one or more comparisons between performance metrics for the prediction model for the different cohorts of users, based on the quality of experience metrics predicted for the different cohorts of users. The device retrains, based on the one or more comparisons, the prediction model using feedback from the reference cohort and a particular cohort from among the different cohorts of users.

公开(公告)号：US12021691B1

公开(公告)日：2024-06-25

申请号：US18107596

申请日：2023-02-09

Applicant: Cisco Technology, Inc.

Inventor： Grégory Mermoud ,  Jean-Philippe Vasseur ,  Grégoire Magendie ,  Romain Kakko-Chiloff

IPC: H04L12/00 ,  G06N5/022 ,  H04L41/08 ,  H04L67/306

CPC classification number: H04L41/0883 ,  G06N5/022 ,  H04L67/306

Abstract: In one embodiment, a recommendation service of a device provides a recommended action to a client of an online application predicted to improve a quality of experience metric for the online application. The device receives feedback from the client indicative of the recommended action not being implemented by a user of the client. The device determines, based on the feedback, a reason for the recommended action not being implemented. The device updates the recommendation service based on the reason for the recommended action not being implemented.

公开(公告)号：US11985069B2

公开(公告)日：2024-05-14

申请号：US17877987

申请日：2022-07-31

Applicant: Cisco Technology, Inc.

Inventor： Romain Kakko-Chiloff ,  Mukund Yelahanka Raghuprasad ,  Vinay Kumar Kolar ,  Jean-Philippe Vasseur

IPC: H04L41/16 ,  H04L41/147 ,  H04L47/2425

CPC classification number: H04L47/2425 ,  H04L41/147 ,  H04L41/16

Abstract: In one embodiment, a device provides, to a user interface, a timeseries for display of a probability over time of a network path violating a service level agreement (SLA) associated with an online application. The device receives, from the user interface, a plurality of thresholds for the timeseries that define periods of time during which application experience of the online application is believed to be degraded. The device trains, based on the plurality of thresholds, a machine learning model to predict when the application experience of the online application will be degraded. The device causes a predictive routing engine to reroute traffic of the online application based on a prediction by the machine learning model that the application experience of the online application will be degraded.

公开(公告)号：US20240039856A1

公开(公告)日：2024-02-01

申请号：US17877987

申请日：2022-07-31

Applicant: Cisco Technology, Inc.

Inventor： Romain Kakko-Chiloff ,  Mukund YELAHANKA RAGHUPRASAD ,  Vinay Kumar KOLAR ,  Jean-Philippe VASSEUR

IPC: H04L47/2425 ,  H04L41/147 ,  H04L41/16

CPC classification number: H04L47/2425 ,  H04L41/147 ,  H04L41/16

Abstract: In one embodiment, a device provides, to a user interface, a timeseries for display of a probability over time of a network path violating a service level agreement (SLA) associated with an online application. The device receives, from the user interface, a plurality of thresholds for the timeseries that define periods of time during which application experience of the online application is believed to be degraded. The device trains, based on the plurality of thresholds, a machine learning model to predict when the application experience of the online application will be degraded. The device causes a predictive routing engine to reroute traffic of the online application based on a prediction by the machine learning model that the application experience of the online application will be degraded.