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    MACHINE LEARNING-BASED APPROACH TO NETWORK PLANNING USING OBSERVED PATTERNS
    71.
    发明申请
    MACHINE LEARNING-BASED APPROACH TO NETWORK PLANNING USING OBSERVED PATTERNS 有权

    公开(公告)号：US20210120438A1

    公开(公告)日：2021-04-22

    申请号：US17130688

    申请日：2020-12-22

    Applicant: Cisco Technology, Inc.

    Inventor： Santosh Ghanshyam Pandey ,  Jean-Philippe Vasseur ,  Vinay Kumar Kolar

    IPC: H04W24/04 ,  G06N3/08 ,  H04L12/24 ,  H04W24/02 ,  H04W36/08

    Abstract: In one embodiment, a network assurance service that monitors a wireless network identifies a set of wireless network anomalies detected in the wireless network that are associated with a set of one or more network measurements. The network assurance service classifies the set of wireless anomalies as radio-related or backend-related. The network assurance service, when the set of wireless anomalies are classified as radio-related, determines that the wireless anomalies are recurring for a particular wireless access point in the network. The network assurance service initiates a change to the wireless network in part to move clients in the wireless network from the particular wireless access point to another wireless access point in the network.

    MACHINE LEARNING DRIVEN DATA COLLECTION OF HIGH-FREQUENCY NETWORK TELEMETRY FOR FAILURE PREDICTION
    73.
    发明申请
    MACHINE LEARNING DRIVEN DATA COLLECTION OF HIGH-FREQUENCY NETWORK TELEMETRY FOR FAILURE PREDICTION 审中-公开

    公开(公告)号：US20200351173A1

    公开(公告)日：2020-11-05

    申请号：US16402384

    申请日：2019-05-03

    Applicant: Cisco Technology, Inc.

    Inventor： Jean-Philippe Vasseur ,  Grégory Mermoud ,  Vinay Kumar Kolar

    IPC: H04L12/24 ,  H04L29/08 ,  G06N20/00

    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.

    REDRAWING ROAMING BOUNDARIES IN A WIRELESS NETWORK
    76.
    发明申请
    REDRAWING ROAMING BOUNDARIES IN A WIRELESS NETWORK 审中-公开

    公开(公告)号：US20190110185A1

    公开(公告)日：2019-04-11

    申请号：US15726543

    申请日：2017-10-06

    Applicant: Cisco Technology, Inc.

    Inventor： Vinay Kumar Kolar ,  Jean-Philippe Vasseur ,  Santosh Pandey

    IPC: H04W8/08 ,  H04W64/00

    Abstract: In one embodiment, a service maintains a mobility path graph that represents roaming transitions between wireless access points in a network by client devices in the network. The service associates metrics regarding roaming delays to mobility paths in the mobility path graph. The service identifies a roaming boundary change that is predicted to reduce roaming delays between two or more wireless access points in the network, in part by assessing the metrics regarding roaming delays associated with the mobility paths in the mobility path graph. The service provides an indication of the identified roaming boundary change to a user interface.

    Actively learning PoPs to probe and probing frequency to maximize application experience predictions
    79.
    发明授权
    Actively learning PoPs to probe and probing frequency to maximize application experience predictions 有权

    公开(公告)号：US11909618B2

    公开(公告)日：2024-02-20

    申请号：US17714483

    申请日：2022-04-06

    Applicant: Cisco Technology, Inc.

    Inventor： Vinay Kumar Kolar ,  Jean-Philippe Vasseur ,  Michal Wladyslaw Garcarz

    IPC: H04L43/12 ,  H04L47/2475

    CPC classification number: H04L43/12 ,  H04L47/2475

    Abstract: In one embodiment, a device computes, for each of a set of points of presence (PoPs) via which traffic for an online application can be sent from a location, application experience metrics predicted for the application over time. The device assigns, for each of the set of PoPs, weights to different time periods, based on measures of uncertainty associated with the predicted application experience metrics. The device generates, based on the weights assigned to the different time periods for each of the set of PoPs, schedules for probing network paths connecting the location to the online application via those PoPs. The device causes the network paths to be probed in accordance with their schedules. Results of this probing are used to select a particular PoP from among the set of PoPs via which traffic for the online application should be sent from the location during a certain time period.

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