公开(公告)号：US11861453B2

公开(公告)日：2024-01-02

申请号：US17979508

申请日：2022-11-02

Applicant: GOOGLE LLC

Inventor： James Peroulas ,  Poojita Thukral ,  Dutt Kalapatapu ,  Andreas Terzis ,  Krishna Sayana

IPC: G06N3/08 ,  H04W24/08 ,  H04W84/04

CPC classification number: G06N3/08 ,  H04W24/08 ,  H04W84/042

Abstract: A method for detecting network anomalies includes receiving a control message from a cellular network and extracting one or more features from the control message. The method also includes predicting a potential label for the control message using a predictive model configured to receive the one or more extracted features from the control message as feature inputs. Here, the predictive model is trained on a set of training control messages where each training control message includes one or more corresponding features and an actual label. The method further includes determining that a probability of the potential label satisfies a confidence threshold. The method also includes analyzing the control message to determine whether the control message corresponds to a respective network performance issue. When the control message impacts network performance, the method includes communicating the network performance issue to a network entity responsible for the network performance issue.

公开(公告)号：US20210133574A1

公开(公告)日：2021-05-06

申请号：US17145236

申请日：2021-01-08

Applicant: Google LLC

Inventor： James Peroulas ,  Poojita Thukral ,  Dutt Kalapatapu ,  Andreas Terzis ,  Krishna Sayana

IPC: G06N3/08 ,  H04W24/08

Abstract: A method for detecting network anomalies includes receiving a control message from a cellular network and extracting one or more features from the control message. The method also includes predicting a potential label for the control message using a predictive model configured to receive the one or more extracted features from the control message as feature inputs. Here, the predictive model is trained on a set of training control messages where each training control message includes one or more corresponding features and an actual label. The method further includes determining that a probability of the potential label satisfies a confidence threshold. The method also includes analyzing the control message to determine whether the control message corresponds to a respective network performance issue. When the control message impacts network performance, the method includes communicating the network performance issue to a network entity responsible for the network performance issue.

公开(公告)号：US10891546B2

公开(公告)日：2021-01-12

申请号：US16397082

申请日：2019-04-29

Applicant: Google LLC

Inventor： James Peroulas ,  Poojita Thukral ,  Dutt Kalapatapu ,  Andreas Terzis ,  Krishna Sayana

IPC: G06N3/08 ,  H04W24/08 ,  H04W84/04

Abstract: A method for detecting network anomalies includes receiving a control message from a cellular network and extracting one or more features from the control message. The method also includes predicting a potential label for the control message using a predictive model configured to receive the one or more extracted features from the control message as feature inputs. Here, the predictive model is trained on a set of training control messages where each training control message includes one or more corresponding features and an actual label. The method further includes determining that a probability of the potential label satisfies a confidence threshold. The method also includes analyzing the control message to determine whether the control message corresponds to a respective network performance issue. When the control message impacts network performance, the method includes communicating the network performance issue to a network entity responsible for the network performance issue.

公开(公告)号：US11507837B2

公开(公告)日：2022-11-22

申请号：US17145236

申请日：2021-01-08

Applicant: Google LLC

Inventor： James Peroulas ,  Poojita Thukral ,  Dutt Kalapatapu ,  Andreas Terzis ,  Krishna Sayana

IPC: G06N3/08 ,  H04W24/08 ,  H04W84/04

Abstract: A method for detecting network anomalies includes receiving a control message from a cellular network and extracting one or more features from the control message. The method also includes predicting a potential label for the control message using a predictive model configured to receive the one or more extracted features from the control message as feature inputs. Here, the predictive model is trained on a set of training control messages where each training control message includes one or more corresponding features and an actual label. The method further includes determining that a probability of the potential label satisfies a confidence threshold. The method also includes analyzing the control message to determine whether the control message corresponds to a respective network performance issue. When the control message impacts network performance, the method includes communicating the network performance issue to a network entity responsible for the network performance issue.

公开(公告)号：US20200342311A1

公开(公告)日：2020-10-29

申请号：US16397082

申请日：2019-04-29

Applicant: Google LLC

Inventor： James Peroulas ,  Poojita Thukral ,  Dutt Kalapatapu ,  Andreas Terzis ,  Krishna Sayana

IPC: G06N3/08 ,  H04W24/08

Abstract: A method for detecting network anomalies includes receiving a control message from a cellular network and extracting one or more features from the control message. The method also includes predicting a potential label for the control message using a predictive model configured to receive the one or more extracted features from the control message as feature inputs. Here, the predictive model is trained on a set of training control messages where each training control message includes one or more corresponding features and an actual label. The method further includes determining that a probability of the potential label satisfies a confidence threshold. The method also includes analyzing the control message to determine whether the control message corresponds to a respective network performance issue. When the control message impacts network performance, the method includes communicating the network performance issue to a network entity responsible for the network performance issue.

公开(公告)号：US12229677B2

公开(公告)日：2025-02-18

申请号：US18398404

申请日：2023-12-28

Applicant: GOOGLE LLC

Inventor： James Peroulas ,  Poojita Thukral ,  Dutt Kalapatapu ,  Andreas Terzis ,  Krishna Sayana

IPC: G06N3/08 ,  H04W24/08 ,  H04W84/04

Abstract: A method for detecting network anomalies includes receiving a control message from a cellular network and extracting one or more features from the control message. The method also includes predicting a potential label for the control message using a predictive model configured to receive the one or more extracted features from the control message as feature inputs. Here, the predictive model is trained on a set of training control messages where each training control message includes one or more corresponding features and an actual label. The method further includes determining that a probability of the potential label satisfies a confidence threshold. The method also includes analyzing the control message to determine whether the control message corresponds to a respective network performance issue. When the control message impacts network performance, the method includes communicating the network performance issue to a network entity responsible for the network performance issue.