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公开(公告)号：US20200153616A1
公开(公告)日：2020-05-14
申请号：US16186662
申请日：2018-11-12
Applicant: Cisco Technology, Inc.
Inventor： Pierre-André Savalle , Jean-Philippe Vasseur , Alexandre Honoré , Grégory Mermoud
Abstract: In one embodiment, a network assurance service maintains a first set of telemetry data from the network anonymized using a first key regarding a plurality of network entities in a monitored network. The service receives a key rotation notification indicative of a key changeover from the first key to a second key for anonymization of a second set of telemetry data from the network. The service forms, during a key rotation time period associated with the key changeover, a mapped dataset by converting anonymized tokens in the second set of telemetry data into anonymized tokens in the first set of telemetry data. The service augments, during the key rotation time period, the first set of telemetry data with the mapped dataset. The service assesses, during the time period, performance of the network by applying a machine learning-based model to the first set of telemetry data augmented with the mapped dataset.
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公开(公告)号：US20200099590A1
公开(公告)日：2020-03-26
申请号：US16697344
申请日：2019-11-27
Applicant: Cisco Technology, Inc.
Abstract: In one embodiment, a network assurance service executing in a local network clusters measurements obtained from the local network regarding a plurality of devices in the local network into measurement clusters. The network assurance service computes aggregated metrics for each of the measurement clusters. The network assurance service sends a machine learning model computation request to a remote service outside of the local network that includes the aggregated metrics for each of the measurement clusters. The remote service uses the aggregated metrics to train a machine learning-based model to analyze the local network. The network assurance service receives the trained machine learning-based model to analyze performance of the local network. The network assurance service uses the receive machine learning-based model to analyze performance of the local network.
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公开(公告)号：US10601676B2
公开(公告)日：2020-03-24
申请号：US15705462
申请日：2017-09-15
Applicant: Cisco Technology, Inc.
Inventor： Pierre-André Savalle , Grégory Mermoud , Jean-Philippe Vasseur
Abstract: In one embodiment, a service identifies a performance issue exhibited by a first device in a first network. The service forms a set of one or more time series of one or more characteristics of the first device associated with the identified performance issue. The service generates a mapping between the set of one or more time series of one or more characteristics of the first device to one or more time series of one or more characteristics of a second device in a second network. The mapping comprises a relevancy score that quantifies a degree of similarity between the characteristics of the first and second devices. The service determines a likelihood of the second device exhibiting the performance issue based on the generated mapping and on the relevancy score. The service provides an indication of the determined likelihood to a user interface associated with the second network.
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公开(公告)号：US10540605B2
公开(公告)日：2020-01-21
申请号：US13946386
申请日：2013-07-19
Applicant: Cisco Technology, Inc.
Inventor： Grégory Mermoud , Jean-Philippe Vasseur , Sukrit Dasgupta
IPC: G06N20/00
Abstract: In one embodiment, techniques are shown and described relating to traffic-based inference of influence domains in a network by using learning machines. In particular, in one embodiment, a management device computes a time-based traffic matrix indicating traffic between pairs of transmitter and receiver nodes in a computer network, and also determines a time-based quality parameter for a particular node in the computer network. By correlating the time-based traffic matrix and time-based quality parameter for the particular node, the device may then determine an influence of particular traffic of the traffic matrix on the particular node.
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公开(公告)号：US10536344B2
公开(公告)日：2020-01-14
申请号：US15996645
申请日：2018-06-04
Applicant: Cisco Technology, Inc.
Abstract: In one embodiment, a network assurance service executing in a local network clusters measurements obtained from the local network regarding a plurality of devices in the local network into measurement clusters. The network assurance service computes aggregated metrics for each of the measurement clusters. The network assurance service sends a machine learning model computation request to a remote service outside of the local network that includes the aggregated metrics for each of the measurement clusters. The remote service uses the aggregated metrics to train a machine learning-based model to analyze the local network. The network assurance service receives the trained machine learning-based model to analyze performance of the local network. The network assurance service uses the receive machine learning-based model to analyze performance of the local network.
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Patent Agency Ranking
46.发明申请公开(公告)号：US20190363971A1
公开(公告)日：2019-11-28
申请号：US15988084
申请日：2018-05-24
Applicant: Cisco Technology, Inc.
Inventor： Grégory Mermoud , Jean-Philippe Vasseur , Andrea Di Pietro
IPC: H04L12/751 , H04L12/46 , H04L12/26 , H04L12/24
Abstract: In one embodiment, a network assurance service that monitors a plurality of networks subdivides telemetry data regarding devices located in the networks into subsets, wherein each subset is associated with a device type, time period, metric type, and network. The service summarizes each subset by computing distribution percentiles of metric values in the subset. The service identifies an outlier subset by comparing distribution percentiles that summarize the subsets. The service reports insight data regarding the outlier subset to a user interface. The service adjusts the subsets based in part on feedback regarding the insight data from the user interface.
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公开(公告)号：US20190356553A1
公开(公告)日：2019-11-21
申请号：US15983615
申请日：2018-05-18
Applicant: Cisco Technology, Inc.
Inventor： Grégory Mermoud , Jean-Philippe Vasseur , David Tedaldi
Abstract: In one embodiment, a network assurance service that monitors a network detects an anomaly in the network by applying an anomaly detector to telemetry data collected from the network. The service sends first data to a user interface that causes the interface to present the detected anomaly and one or more candidate root cause metrics from the telemetry data associated with the detected anomaly. The service receives feedback regarding the candidate root cause metric(s) and learns a root cause of the anomaly as one or more thresholds of the candidate root cause metric(s), based in part on the received feedback regarding the candidate root cause metric(s). The service sends second data to the user interface that causes the user interface to present at least one of the candidate root cause metric(s) as a candidate root cause of a subsequent detected anomaly, based on the learned threshold(s).
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48.发明申请公开(公告)号：US20190356533A1
公开(公告)日：2019-11-21
申请号：US15983437
申请日：2018-05-18
Applicant: Cisco Technology, Inc.
Inventor： Jean-Philippe Vasseur , Grégory Mermoud , Santosh Ghanshyam Pandey , Vikram Kumaran
Abstract: In one embodiment, a network assurance service associates a target key performance indicator (tKPI) measured from a network with a plurality of causation key performance indicators (cKPIs) measured from the network that may indicate a root cause of a tKPI anomaly. The network assurance service applies a machine learning-based anomaly detector to the tKPI over time, to generate tKPI anomaly scores. The network assurance service calculates, for each of cKPIs, a mean and standard deviation of that cKPI using a plurality of different time windows associated with the tKPI anomaly scores. The network assurance service uses the calculated means and standard deviations of the cKPIs in the different time windows to calculate cross-correlation scores between the tKPI anomaly scores and the cKPIs. The network assurance service selects one or more of the cKPIs as the root cause of the tKPI anomaly based on their calculated cross-correlation scores.
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公开(公告)号：US10404728B2
公开(公告)日：2019-09-03
申请号：US15263487
申请日：2016-09-13
Applicant: Cisco Technology, Inc.
Inventor： Laurent Sartran , Sébastien Gay , Pierre-André Savalle , Grégory Mermoud , Jean-Philippe Vasseur
Abstract: In one embodiment, a device in a network receives traffic records indicative of network traffic between different sets of host address pairs. The device identifies one or more address grouping constraints for the sets of host address pairs. The device determines address groups for the host addresses in the sets of host address pairs based on the one or more address grouping constraints. The device provides an indication of the address groups to an anomaly detector.
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公开(公告)号：US10212044B2
公开(公告)日：2019-02-19
申请号：US15466969
申请日：2017-03-23
Applicant: Cisco Technology, Inc.
Inventor： Grégory Mermoud , Pierre-André Savalle , Jean-Philippe Vasseur , Javier Cruz Mota
Abstract: In one embodiment, a device in a network maintains a machine learning-based recursive model that models a time series of observations regarding a monitored entity in the network. The device applies sparse dictionary learning to the recursive model, to find a decomposition of a particular state vector of the recursive model. The decomposition of the particular state vector comprises a plurality of basis vectors. The device determines a mapping between at least one of the plurality of basis vectors for the particular state vector and one or more human-readable interpretations of the basis vectors. The device provides a label for the particular state vector to a user interface. The label is based on the mapping between the at least one of the plurality of basis vectors for the particular state vector and the one or more human-readable interpretations of the basis vectors.
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