公开(公告)号：US11823079B2

公开(公告)日：2023-11-21

申请号：US17938895

申请日：2022-10-07

Applicant: Juniper Networks, Inc.

Inventor： Shruti Jadon ,  Mithun Chakaravarrti Dharmaraj ,  Anita Kar ,  Harshit Naresh Chitalia

IPC: G06F15/16 ,  G06N5/04 ,  G06N20/00 ,  H04L43/04

CPC classification number: G06N5/04 ,  G06N20/00 ,  H04L43/04

Abstract: This disclosure describes techniques that include using an automatically trained machine learning system to generate a prediction. In one example, this disclosure describes a method comprising: based on a request for the prediction: training each respective machine learning (ML) model in a plurality of ML models to generate a respective training-phase prediction in a plurality of training-phase predictions; automatically determining a selected ML model in the plurality of ML models based on evaluation metrics for the plurality of ML; and applying the selected ML model to generate the prediction based on data collected from a network that includes a plurality of network devices.

公开(公告)号：US20230031889A1

公开(公告)日：2023-02-02

申请号：US17938895

申请日：2022-10-07

Applicant: Juniper Networks, Inc.

Inventor： Shruti Jadon ,  Mithun Chakaravarrti Dharmaraj ,  Anita Kar ,  Harshit Naresh Chitalia

IPC: G06N5/04 ,  G06N20/00 ,  H04L43/04

Abstract: This disclosure describes techniques that include using an automatically trained machine learning system to generate a prediction. In one example, this disclosure describes a method comprising: based on a request for the prediction: training each respective machine learning (ML) model in a plurality of ML models to generate a respective training-phase prediction in a plurality of training-phase predictions; automatically determining a selected ML model in the plurality of ML models based on evaluation metrics for the plurality of ML; and applying the selected ML model to generate the prediction based on data collected from a network that includes a plurality of network devices.

公开(公告)号：US11501190B2

公开(公告)日：2022-11-15

申请号：US16920113

申请日：2020-07-02

Applicant: Juniper Networks, Inc.

Inventor： Shruti Jadon ,  Mithun Chakaravarrti Dhamaraj ,  Anita Kar ,  Harshit Naresh Chitalia

IPC: G06F15/16 ,  G06N5/04 ,  G06N20/00 ,  H04L43/04

Abstract: This disclosure describes techniques that include using an automatically trained machine learning system to generate a prediction. In one example, this disclosure describes a method comprising: based on a request for the prediction: training each respective machine learning (ML) model in a plurality of ML models to generate a respective training-phase prediction in a plurality of training-phase predictions; automatically determining a selected ML model in the plurality of ML models based on evaluation metrics for the plurality of ML; and applying the selected ML model to generate the prediction based on data collected from a network that includes a plurality of network devices.

公开(公告)号：US20220004897A1

公开(公告)日：2022-01-06

申请号：US16920113

申请日：2020-07-02

Applicant: Juniper Networks, Inc.

Inventor： Shruti Jadon ,  Mithun Chakaravarrti Dhamaraj ,  Anita Kar ,  Harshit Naresh Chitalia

IPC: G06N5/04 ,  G06N20/00 ,  H04L12/26

Abstract: This disclosure describes techniques that include using an automatically trained machine learning system to generate a prediction. In one example, this disclosure describes a method comprising: based on a request for the prediction: training each respective machine learning (ML) model in a plurality of ML models to generate a respective training-phase prediction in a plurality of training-phase predictions; automatically determining a selected ML model in the plurality of ML models based on evaluation metrics for the plurality of ML; and applying the selected ML model to generate the prediction based on data collected from a network that includes a plurality of network devices.

公开(公告)号：US12039355B2

公开(公告)日：2024-07-16

申请号：US16947930

申请日：2020-08-24

Applicant: Juniper Networks, Inc.

Inventor： Gauresh Dilip Vanjare ,  Shruti Jadon ,  Tarun Banka ,  Venny Kranthi Teja Kommarthi ,  Aditi Ghotikar ,  Harshit Naresh Chitalia ,  Keval Nimeshkumar Shah ,  Mithun Chakaravarrti Dharmaraj ,  Rajenkumar Patel ,  Yixiao Wei

IPC: G06F9/455 ,  G06F9/50

CPC classification number: G06F9/45558 ,  G06F9/5077 ,  G06F2009/4557 ,  G06F2009/45591 ,  G06F2009/45595 ,  G06F2209/503 ,  G06F2209/505

Abstract: A telemetry service can receive telemetry collection requirements that are expressed as an “intent” that defines how telemetry is to be collected. A telemetry intent compiler can receive the telemetry intent and translate the high level intent into abstract telemetry configuration parameters that provide a generic description of desired telemetry data. The telemetry service can determine, from the telemetry intent, a set of devices from which to collect telemetry data. For each device, the telemetry service can determine capabilities of the device with respect to telemetry data collection. The capabilities may include a telemetry protocol supported by the device. The telemetry service can create a protocol specific device configuration based on the abstract telemetry configuration parameters and the telemetry protocol supported by the device. Devices in a network system that support a particular telemetry protocol can be allocated to instances of a telemetry collector that supports the telemetry protocol.

公开(公告)号：US20240176878A1

公开(公告)日：2024-05-30

申请号：US18459036

申请日：2023-08-30

Applicant: Juniper Networks, Inc.

Inventor： Ajit Krishna Patankar ,  Kihwan Han ,  Prasad Miriyala ,  Mansi Joshi ,  Shruti Jadon ,  Deepak Kumar Naik ,  Maria Charles Maria Selvam

IPC: G06F21/55

CPC classification number: G06F21/554 ,  G06F2221/034

Abstract: An example system for performing root cause analysis for a plurality of network devices includes one or more processors implemented in circuitry and configured to: receive telemetry data from the plurality of network devices; apply an artificial intelligence (AI) anomaly detection model, trained on historical telemetry data to detect anomalies in the historical telemetry data, to the received telemetry data to detect one or more anomalies in the received telemetry data; and apply an AI root cause analysis mode, trained on historical data, to the anomalies to determine a root cause of an issue causing the one or more anomalies.

公开(公告)号：US20220058042A1

公开(公告)日：2022-02-24

申请号：US16947930

申请日：2020-08-24

Applicant: Juniper Networks, Inc.

Inventor： Gauresh Dilip Vanjare ,  Shruti Jadon ,  Tarun Banka ,  Venny Kranthi Teja Kommarthi ,  Aditi Ghotikar ,  Harshit Naresh Chitalia ,  Keval Nimeshkumar Shah ,  Mithun Chakaravarrti Dharmaraj ,  Rajenkumar Patel ,  Yixiao Wei

IPC: G06F9/455 ,  G06F9/50 ,  G06F11/07 ,  G06K9/62 ,  H04L12/24

Abstract: A telemetry service can receive telemetry collection requirements that are expressed as an “intent” that defines how telemetry is to be collected. A telemetry intent compiler can receive the telemetry intent and translate the high level intent into abstract telemetry configuration parameters that provide a generic description of desired telemetry data. The telemetry service can determine, from the telemetry intent, a set of devices from which to collect telemetry data. For each device, the telemetry service can determine capabilities of the device with respect to telemetry data collection. The capabilities may include a telemetry protocol supported by the device. The telemetry service can create a protocol specific device configuration based on the abstract telemetry configuration parameters and the telemetry protocol supported by the device. Devices in a network system that support a particular telemetry protocol can be allocated to instances of a telemetry collector that supports the telemetry protocol.