公开(公告)号：US11283679B2

公开(公告)日：2022-03-22

申请号：US17020384

申请日：2020-09-14

Applicant: Cisco Technology, Inc.

Inventor： Thomas Michel-Ange Feltin ,  Wenqin Shao ,  Parisa Foroughi ,  Frank Brockners

IPC: H04L12/24 ,  G06N3/08 ,  G06F17/40 ,  G06F17/18 ,  H04L41/083 ,  H04L41/0823

Abstract: Techniques and mechanisms for automatically identifying counters/features of a network component that are related to a state change (or event) for the network component or for the network itself. For example, using data obtained from the network component around a time of the state change, delta-averages for the counters/features around the time of the state change may be determined. The delta-averages may be utilized to determine which counters/features are most descriptive for a particular state change. Determining which counters/features are most descriptive may also include determining which counters/features are most relevant, i.e., counters/features that contribute most to preserving the manifold structure of the original data or counters/features with the highest or lowest correlation with the other counters/features in the data set. Thus, the techniques described herein provide for an approach to distill which counters/features contribute the most to a particular state change from a data driven perspective.

公开(公告)号：US20210092009A1

公开(公告)日：2021-03-25

申请号：US17020384

申请日：2020-09-14

Applicant: Cisco Technology, Inc.

Inventor： Thomas Michel-Ange Feltin ,  Wenqin Shao ,  Parisa Foroughi ,  Frank Brockners

IPC: H04L12/24 ,  G06F17/18 ,  G06F17/40 ,  G06N3/08

Abstract: Techniques and mechanisms for automatically identifying counters/features of a network component that are related to a state change (or event) for the network component or for the network itself. For example, using data obtained from the network component around a time of the state change, delta-averages for the counters/features around the time of the state change may be determined. The delta-averages may be utilized to determine which counters/features are most descriptive for a particular state change. Determining which counters/features are most descriptive may also include determining which counters/features are most relevant, i.e., counters/features that contribute most to preserving the manifold structure of the original data or counters/features with the highest or lowest correlation with the other counters/features in the data set. Thus, the techniques described herein provide for an approach to distill which counters/features contribute the most to a particular state change from a data driven perspective.

公开(公告)号：US11115280B2

公开(公告)日：2021-09-07

申请号：US16789723

申请日：2020-02-13

Applicant: Cisco Technology, Inc.

Inventor： Wenqin Shao ,  Frank Brockners ,  Parisa Foroughi ,  Thomas Michel-Ange Feltin

IPC: H04L12/24

Abstract: Techniques and mechanisms for automatically identifying counters/features of a network component that are related to a state change (or event) for the network component or for the network itself. For example, using data obtained from the network component around a time of the state change, delta averages for the features around the time of the state change may be determined. The delta averages may be utilized to determine which counters/features are most descriptive for a particular state change. The counter/features that are the most descriptive for a particular state change is as important as the change detection itself. This is especially true since in a case of an event/state change occurring, a large amount of counters/features may react to the state change or event. Thus, the techniques described herein provide for an approach to distill which counters/features contribute the most to a particular state change from a data driven perspective.

公开(公告)号：US20210092010A1

公开(公告)日：2021-03-25

申请号：US16789723

申请日：2020-02-13

Applicant: Cisco Technology, Inc.

Inventor： Wenqin Shao ,  Frank Brockners ,  Parisa Foroughi ,  Thomas Michel-Ange Feltin

IPC: H04L12/24

Abstract: Techniques and mechanisms for automatically identifying counters/features of a network component that are related to a state change (or event) for the network component or for the network itself. For example, using data obtained from the network component around a time of the state change, delta averages for the features around the time of the state change may be determined. The delta averages may be utilized to determine which counters/features are most descriptive for a particular state change. The counter/features that are the most descriptive for a particular state change is as important as the change detection itself. This is especially true since in a case of an event/state change occurring, a large amount of counters/features may react to the state change or event. Thus, the techniques described herein provide for an approach to distill which counters/features contribute the most to a particular state change from a data driven perspective.