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51.发明申请公开(公告)号：US20180367428A1
公开(公告)日：2018-12-20
申请号：US15626412
申请日：2017-06-19
Applicant: Cisco Technology, Inc.
Inventor： Andrea Di Pietro , Grégory Mermoud , Jean-Philippe Vasseur , Sukrit Dasgupta
CPC classification number: H04L43/0817 , G06F16/24578 , G06N3/0472 , G06N3/08 , G06N5/003 , G06N5/04 , G06N7/005 , G06N20/10 , G06N20/20 , H04L41/0213 , H04L41/0816 , H04L41/145 , H04L41/147 , H04L43/08 , H04L43/10 , H04L63/1408 , H04L63/1433
Abstract: In one embodiment, a device receives health status data indicative of a health status of a data source in a network that provides collected telemetry data from the network for analysis by a machine learning-based network analyzer. The device maintains a performance model for the data source that models the health of the data source. The device computes a trustworthiness index for the telemetry data provided by the data source based on the received health status data and the performance model for the data source. The device adjusts, based on the computed trustworthiness index for the telemetry data provided by the data source, one or more parameters used by the machine learning-based network analyzer to analyze the telemetry data provided by the data source.
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公开(公告)号：US20180359651A1
公开(公告)日：2018-12-13
申请号：US15620109
申请日：2017-06-12
Applicant: Cisco Technology, Inc.
Inventor： Javier Cruz Mota , Jean-Philippe Vasseur , Pierre-André Savalle , Grégory Mermoud
IPC: H04W24/08
Abstract: In one embodiment, a device receives observed access point (AP) features of one or more APs in a monitored network. The device clusters the observed AP features within a latent space to form AP feature clusters. The device applies labels to the AP feature clusters within the latent space. The device uses the applied labels to the AP feature clusters to describe future behaviors of the one or more APs in the monitored network.
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公开(公告)号：US20180278486A1
公开(公告)日：2018-09-27
申请号：US15464526
申请日：2017-03-21
Applicant: Cisco Technology, Inc.
Inventor： Grégory Mermoud , Jean-Philippe Vasseur
CPC classification number: H04L41/16 , G06N5/046 , G06N20/00 , H04L41/147 , H04L41/5009 , H04L41/5019
Abstract: In one embodiment, a device in a network receives data regarding a plurality of predefined health status rules that evaluate one or more observed conditions of the network. The device, using the data regarding the plurality of health status rules for the network, trains a machine learning-based classifier to generate predictions regarding outputs of the health status rules. The device adjusts the machine learning-based classifier based on feedback associated with the generated predictions. The device provides an indication of one or more of the predictions regarding the outputs of the health status rules to a user interface.
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公开(公告)号：US20180204129A1
公开(公告)日：2018-07-19
申请号：US15405455
申请日：2017-01-13
Applicant: Cisco Technology, Inc.
Inventor： Jean-Philippe Vasseur , Grégory Mermoud , Pierre-André Savalle , Javier Cruz Mota
CPC classification number: G06N7/005 , G06N20/00 , H04L12/1818 , H04L12/1822 , H04L12/1827 , H04L41/147 , H04L65/1003 , H04L65/403 , H04W84/12
Abstract: In one embodiment, a device in a network receives an indication of a connection between an endpoint node in the network and a conferencing service. The device retrieves network data associated with the indicated connection between the endpoint node and the conferencing service. The device uses a machine learning model to predict an experience metric for the endpoint node based on the network data associated with the indicated connection between the endpoint node and the conferencing service. The device causes the endpoint node to use a different connection to the conferencing service based on the predicted experience metric.
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公开(公告)号：US20180159755A1
公开(公告)日：2018-06-07
申请号：US15872359
申请日：2018-01-16
Applicant: Cisco Technology, Inc.
Inventor： Sukrit Dasgupta , Jean-Philippe Vasseur , Grégory Mermoud
IPC: H04L12/26
CPC classification number: H04L43/0894 , H04L43/0805 , H04L43/0852 , H04L43/103 , H04L43/16
Abstract: In one embodiment, a device in a network receives data indicative of traffic characteristics of traffic associated with a particular application. The device identifies one or more paths in the network via which the traffic associated with the particular application was sent, based on the traffic characteristics. The device determines a probing schedule based on the traffic characteristics. The probing schedule simulates the traffic associated with the particular application. The device sends probes along the one or more identified paths according to the determined probing schedule.
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Patent Agency Ranking
56.发明授权公开(公告)号：US09860140B2
公开(公告)日：2018-01-02
申请号：US13941063
申请日：2013-07-12
Applicant: Cisco Technology, Inc.
Inventor： Jean-Philippe Vasseur , Grégory Mermoud , Sukrit Dasgupta
CPC classification number: H04L43/02 , H04L41/16 , H04L43/103 , Y04S40/168
Abstract: In one embodiment, techniques are shown and described relating to dynamically adjusting a set of monitored network properties using distributed learning machine feedback. In particular, in one embodiment, a learning machine (or distributed learning machines) determines a plurality of monitored network properties in a computer network. From this, a subset of relevant network properties of the plurality of network properties may be determined, such that a corresponding subset of irrelevant network properties based on the subset of relevant network properties may also be determined. Accordingly, the computer network may be informed of the irrelevant network properties to reduce a rate of monitoring the irrelevant network properties.
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公开(公告)号：US09838409B2
公开(公告)日：2017-12-05
申请号：US14878145
申请日：2015-10-08
Applicant: Cisco Technology, Inc.
Inventor： Fabien Flacher , Grégory Mermoud , Jean-Philippe Vasseur , Sukrit Dasgupta
CPC classification number: H04L63/1425 , H04L63/1458
Abstract: In one embodiment, a device in a network analyzes data indicative of a behavior of a network using a supervised anomaly detection model. The device determines whether the supervised anomaly detection model detected an anomaly in the network from the analyzed data. The device trains an unsupervised anomaly detection model, based on a determination that no anomalies were detected by the supervised anomaly detection model.
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公开(公告)号：US20170279834A1
公开(公告)日：2017-09-28
申请号：US15211093
申请日：2016-07-15
Applicant: Cisco Technology, Inc.
Inventor： Jean-Philippe Vasseur , Grégory Mermoud , Javier Cruz Mota , Laurent Sartran , Sébastien Gay
CPC classification number: H04L63/1425 , G06N3/006 , G06N20/00 , H04L41/147 , H04L43/024 , H04L43/062 , H04L43/14 , H04L63/02 , H04L63/145 , H04L63/1458 , H04L2463/144
Abstract: In one embodiment, a device in a network receives feedback regarding an anomaly reporting mechanism used by the device to report network anomalies detected by a plurality of distributed learning agents to a user interface. The device determines an anomaly assessment rate at which a user of the user interface is expected to assess reported anomalies based in part on the feedback. The device receives an anomaly notification regarding a particular anomaly detected by a particular one of the distributed learning agents. The device reports, via the anomaly reporting mechanism, the particular anomaly to the user interface based on the determined anomaly assessment rate.
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公开(公告)号：US20170279827A1
公开(公告)日：2017-09-28
申请号：US15163347
申请日：2016-05-24
Applicant: Cisco Technology, Inc.
Inventor： Pierre-André Savalle , Laurent Sartran , Jean-Philippe Vasseur , Grégory Mermoud
CPC classification number: H04L63/1425 , H04L63/1416 , H04L67/02 , H04L67/22 , H04L69/22
Abstract: In one embodiment, a device in a network identifies a new interaction between two or more nodes in the network. The device forms a feature vector using contextual information associated with the new interaction between the two or more nodes. The device causes generation of an anomaly detection model for new node interactions using the feature vector. The device uses the anomaly detection model to determine whether a particular node interaction in the network is anomalous.
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60.发明授权公开(公告)号：US09734457B2
公开(公告)日：2017-08-15
申请号：US14163638
申请日：2014-01-24
Applicant: Cisco Technology, Inc.
Inventor： Jean-Philippe Vasseur , Grégory Mermoud , Sukrit Dasgupta
IPC: G06F15/18 , G06N99/00 , H04L12/24 , H04L29/08 , H04L12/851 , H04L12/753 , G06Q10/06 , H04L12/18
CPC classification number: G06N99/005 , G06Q10/0631 , G06Q10/06375 , H04L12/185 , H04L41/145 , H04L41/147 , H04L41/16 , H04L45/48 , H04L47/2483 , H04L67/26
Abstract: In one embodiment, a learning data processor determines a plurality of machine learning features in a computer network to collect. Upon receiving data corresponding to the plurality of features, the learning data processor may aggregate the data, and pushes the aggregated data for select features to interested learning machines associated with the computer network.
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