Patents by Inventor Jean Philippe Vasseur

Jean Philippe Vasseur has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Ensuring backup path performance for predictive routing in SD-WANs
    Patent number: 11063861
    Abstract: In one embodiment, a device predicts a failure of a first tunnel in a software-defined wide area network (SD-WAN). The device makes a prediction as to whether a second tunnel in the SD-WAN will satisfy a service level agreement (SLA) associated with traffic on the first tunnel. The device proactively reroutes the traffic from the first tunnel onto the second tunnel, based on the prediction as to whether that the second tunnel will satisfy the SLA of the traffic. The device monitors one or more quality of service (QoS) metrics for the rerouted traffic, to ensure that the second tunnel satisfies the SLA of the traffic.
    Type: Grant
    Filed: June 3, 2019
    Date of Patent: July 13, 2021
    Assignee: Cisco Technology, Inc.
    Inventors: Jean-Philippe Vasseur, Grégory Mermoud, Vinay Kumar Kolar, Sharon Shoshana Wulff
  • Forecasting network KPIs
    Patent number: 11063842
    Abstract: In one embodiment, a service receives input data from networking entities in a network. The input data comprises synchronous time series data, asynchronous event data, and an entity graph that that indicates relationships between the networking entities in the network. The service clusters the networking entities by type in a plurality of networking entity clusters. The service selects, based on a combination of the received input data, machine learning model data features. The service trains, using the selected machine learning model data features, a machine learning model to forecast a key performance indicator (KPI) for a particular one of the networking entity clusters.
    Type: Grant
    Filed: January 10, 2020
    Date of Patent: July 13, 2021
    Assignee: Cisco Technology, Inc.
    Inventors: Jean-Philippe Vasseur, Grégory Mermoud, Vinay Kumar Kolar, Pierre-Andre Savalle
  • Mixing rule-based and machine learning-based indicators in network assurance systems
    Patent number: 11063836
    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.
    Type: Grant
    Filed: March 21, 2017
    Date of Patent: July 13, 2021
    Assignee: Cisco Technology, Inc.
    Inventors: Grégory Mermoud, Jean-Philippe Vasseur
  • AGGREGATED SIGNAL FEEDBACK FOR SAAS EXPERIENCE IN MULTI-CLOUD SD-WAN DEPLOYMENTS
    Publication number: 20210211347
    Abstract: In one embodiment, an edge device located at an edge of a local network provides connectivity between the local network and a cloud-based software as a service (SaaS) provider via one or more interfaces. The edge device obtains telemetry data associated with the edge device for a plurality of metrics. The edge device makes a determination that one or more of the plurality of metrics is anomalous. The edge device sends, based on the determination, an indication of the determination to the SaaS provider. The SaaS provider uses the indication to determine a root cause of an application served by the SaaS provider experiencing degraded application performance.
    Type: Application
    Filed: March 18, 2020
    Publication date: July 8, 2021
    Inventors: Jean-Philippe Vasseur, Ramanathan Lakshmikanthan, Steven William Wood, Ramesh Durairaj
  • Using a midlay in a software defined networking (SDN) fabric for adjustable segmentation and slicing
    Patent number: 11057301
    Abstract: In one embodiment, a device configures a plurality of subinterfaces for each of a plurality of physical ports of a software defined network (SDN). The device allocates a fixed amount of bandwidth to each of the subinterfaces. The device forms a plurality of midlays for the SDN by assigning subsets of the plurality of subinterfaces to each of the midlays. The device assigns a network slice to one or more of the midlays, based on a bandwidth requirement of the network slice.
    Type: Grant
    Filed: March 21, 2019
    Date of Patent: July 6, 2021
    Assignee: Cisco Technology, Inc.
    Inventors: Pascal Thubert, Jean-Philippe Vasseur, Eric Levy-Abegnoli, Patrick Wetterwald
  • Deriving highly interpretable cognitive patterns for network assurance
    Patent number: 11049033
    Abstract: In one embodiment, a network assurance system that monitors a network labels time periods with positive labels, based on the network assurance system detecting problems in the network during the time periods. The network assurance system assigns tags to discrete portions of a feature space of measurements from the monitored network, based on whether a particular range of values in the feature space has a threshold probability of occurring during a positively-labeled time period. The network assurance system determines a set of the assigned tags that frequently co-occur with the positively-labeled time periods in which problems are detected in the network. The network assurance system causes performance of a mitigation action in the network based on the set of assigned tags that frequently co-occur with the positively-labeled time periods.
    Type: Grant
    Filed: January 12, 2018
    Date of Patent: June 29, 2021
    Assignee: Cisco Technology, Inc.
    Inventors: Vinay Kumar Kolar, Vikram Kumaran, Abhishek Kumar, Santosh Ghanshyam Pandey, Jean-Philippe Vasseur, Grégory Mermoud
  • Coupling reactive routing with predictive routing in a network
    Patent number: 11044191
    Abstract: In one embodiment, a device in a network predicts failure of a network element in the network using a machine learning-based failure prediction model. The device updates, based on the predicted failure of the network element, a topology of the network to remove the network element from the topology of the network. The device recomputes a reactive routing table of the device using the updated topology of the network. The device notifies one or more other devices of the network of the predicted failure using a reactive routing protocol message.
    Type: Grant
    Filed: April 24, 2019
    Date of Patent: June 22, 2021
    Assignee: Cisco Technology, Inc.
    Inventor: Jean-Philippe Vasseur
  • ANOMALY DETECTION OF MODEL PERFORMANCE IN AN MLOPS PLATFORM
    Publication number: 20210184958
    Abstract: In one embodiment, a service tracks performance of a machine learning model over time. The machine learning model is used to monitor one or more computer networks based on data collected from the one or more computer networks. The service also tracks performance metrics associated with training of the machine learning model. The service determines that a degradation of the performance of the machine learning model is anomalous, based on the tracked performance of the machine learning model and performance metrics associated with training of the model. The service initiates a corrective measure for the degradation of the performance, in response to determining that the degradation of the performance is anomalous.
    Type: Application
    Filed: December 11, 2019
    Publication date: June 17, 2021
    Inventors: Vinay Kumar Kolar, Jean-Philippe Vasseur, Grégory Mermoud, Pierre-Andre Savalle
  • Repair walker agents in a network
    Patent number: 11036571
    Abstract: In one embodiment, a supervisory device in a network receives a help request from a first node in the network indicative of a problem in the network detected by the first node. The supervisory device identifies a second node in the network that is hosting a repair walker agent able to address the detected problem. The supervisory device determines a network path via which the second node is to send repair walker agent to the first node. The supervisory device instructs the second node to send the repair walker agent to the first node via the determined path.
    Type: Grant
    Filed: November 29, 2017
    Date of Patent: June 15, 2021
    Assignee: Cisco Technology, Inc.
    Inventors: Patrick Wetterwald, Pascal Thubert, Eric Levy-Abegnoli, Jean-Philippe Vasseur
  • Machine learning-based client selection and testing in a network assurance system
    Patent number: 11038775
    Abstract: In one embodiment, a network assurance service that monitors a network detects a network anomaly in the network using a machine learning-based anomaly detector. The network assurance service identifies a set of network conditions associated with the detected network anomaly. The network assurance service initiates a network test on one or more clients in the network that exhibit the identified network conditions. The network assurance service retrains the machine learning-based anomaly detector based on a result of the network test.
    Type: Grant
    Filed: August 10, 2018
    Date of Patent: June 15, 2021
    Assignee: Cisco Technology, Inc.
    Inventors: Santosh Ghanshyam Pandey, Jean-Philippe Vasseur, Sukrit Dasgupta
  • PREDICTING THE IMPACT OF NETWORK SOFTWARE UPGRADES ON MACHINE LEARNING MODEL PERFORMANCE
    Publication number: 20210173636
    Abstract: In one embodiment, a service receives software version data regarding versions of software executed by devices in a network. The service detects a version change in the version of software executed by one or more of the devices, based on the received software version data. The service makes a determination that a drop in data quality of input data for a machine learning model used to monitor the network is associated with the detected version change. The service reverts the one or more devices to a prior version of software, based on the determination that the drop in quality of the input data for the machine learning model used to monitor the network is associated with the detected version change.
    Type: Application
    Filed: December 10, 2019
    Publication date: June 10, 2021
    Inventors: Vinay Kumar Kolar, Jean-Philippe Vasseur, Gregory Mermoud, Pierre-Andre Savalle
  • THRESHOLD SELECTION FOR KPI CANDIDACY IN ROOT CAUSE ANALYSIS OF NETWORK ISSUES
    Publication number: 20210176115
    Abstract: In one embodiment, a network assurance service that monitors a network maps time series of values of key performance indicator (KPIs) measured from the network to lists of unique values from the time series. The service sets a target alarm rate for anomaly detection alarms raised by the network assurance service. The service uses an optimization function to identify a set of thresholds for the KPIs. The optimization function is based on: a comparison between the target alarm rate and a fraction of network issues flagged by the service as outliers, KPI thresholds selected based on the lists of unique values from the time series, and a number of thresholds that the KPIs must cross for the service to raise an alarm. The service raises an anomaly detection alarm for the monitored network based on the identified set of thresholds for the KPIs.
    Type: Application
    Filed: November 25, 2020
    Publication date: June 10, 2021
    Inventors: Sajjit Thampy, Santosh Ghanshyam Pandey, Jean-Philippe Vasseur
  • NEGOTIATING MACHINE LEARNING MODEL INPUT FEATURES BASED ON COST IN CONSTRAINED NETWORKS
    Publication number: 20210176146
    Abstract: In one embodiment, a service receives a feature availability report indicative of which telemetry variables are available at a device in a network and resource costs associated with data features that the device could compute from the telemetry variables. The service selects at least a subset of the data features for input to a machine learning model, based on their associated resource costs and on their respective impacts on one or more performance metrics for the machine learning model. The service trains the machine learning model to evaluate the selected data features. The service sends the trained machine learning model to the device. The device computes the selected data features from the telemetry variables available at the device and uses the computed data features as input to the machine learning model.
    Type: Application
    Filed: December 10, 2019
    Publication date: June 10, 2021
    Inventors: Jean-Philippe Vasseur, Pascal Thubert, Eric Levy-Abegnoli, Patrick Wetterwald
  • Machine learning approach for dynamic adjustment of BFD timers in SD-WAN networks
    Patent number: 11032181
    Abstract: In one embodiment, a device obtains performance data regarding failures of a tunnel in a network. The device generates a failure profile for the tunnel by applying machine learning to the performance data regarding the failures of the tunnel. The device determines, based on the failure profile for the tunnel, whether the tunnel exhibits failure flapping behavior. The device adjusts one or more Bidirectional Forwarding Detection (BFD) probing timers used to detect failures of the tunnel, based on the determination as to whether the tunnel exhibits failure flapping behavior.
    Type: Grant
    Filed: June 7, 2019
    Date of Patent: June 8, 2021
    Assignee: Cisco Technology, Inc.
    Inventors: Jean-Philippe Vasseur, Vinay Kumar Kolar, Grégory Mermoud
  • Propagating an intelligent walker agent in a network to perform a computation
    Patent number: 11025702
    Abstract: In one embodiment, a device in a network receives a path computation agent configured to determine a path in the network that satisfies an objective function. The device executes the path computation agent to update state information regarding the network maintained by the path computation agent. The device selects a neighbor of the device in the network to execute the path computation agent based on the updated state information regarding the network. The device instructs the selected neighbor to execute the path computation agent with the updated state information regarding the network. The device unloads the path computation agent from the device after selecting the neighbor of the device to execute the path computation agent.
    Type: Grant
    Filed: September 27, 2019
    Date of Patent: June 1, 2021
    Assignee: Cisco Technology, Inc.
    Inventors: Eric Levy-Abegnoli, Pascal Thubert, Patrick Wetterwald, Jean-Philippe Vasseur
  • Cascade-based classification of network devices using multi-scale bags of network words
    Patent number: 11025486
    Abstract: In one embodiment, a device classification service extracts, for each of a plurality of time windows, one or more sets of traffic features of network traffic in a network from traffic telemetry data captured by the network. The service represents, for the time windows, the extracted one or more sets of traffic features as feature vectors. A feature vector for a time window indicates whether each of the traffic features was present in the network traffic during that window. The service trains, using a training dataset based on the feature vectors, a cascade of machine learning classifiers to label devices with device types. The service uses the classifiers to label a particular device in the network with a device type based on the traffic features of network traffic associated with that device. The service initiates enforcement of a network policy regarding the device based on its device type.
    Type: Grant
    Filed: October 19, 2018
    Date of Patent: June 1, 2021
    Assignee: Cisco Technology, Inc.
    Inventors: Pierre-André Savalle, Jean-Philippe Vasseur, Grégory Mermoud
  • EVENT-TRIGGERED MACHINE LEARNING FOR RARE EVENT FORECASTING IN A SOFTWARE DEFINED WIDE AREA NETWORK (SD-WAN)
    Publication number: 20210160148
    Abstract: In one embodiment, a service detects that an event of a particular event type has occurred in a software-defined wide area network (SD-WAN). The service activates, in response to detecting the occurrence of the event, a machine learning model to assess telemetry data regarding a first tunnel in the SD-WAN. The service predicts a failure of the first tunnel, based on the assessment of the telemetry data regarding the first tunnel by the machine learning model. The service proactively reroutes at least a subset of traffic on the first tunnel onto a second tunnel in the SD-WAN, in advance of the predicted failure of the first tunnel.
    Type: Application
    Filed: November 25, 2019
    Publication date: May 27, 2021
    Inventors: Vinay Kumar Kolar, Jean-Philippe Vasseur, Grégory Mermoud, Pierre-Andre Savalle
  • ASSESSING DATA FIDELITY IN A MACHINE LEARNING-BASED NETWORK ASSURANCE SYSTEM
    Publication number: 20210158106
    Abstract: In one embodiment, a service computes a data fidelity metric for network telemetry data used by a machine learning model to monitor a computer network. The service detects unacceptable performance of the machine learning model. The service determines a correlation between the data fidelity metric and the unacceptable performance of the machine learning model. The service adjusts generation of the network telemetry data for input to the machine learning model, based on the determined correlation between the data fidelity metric and the unacceptable performance of the machine learning model.
    Type: Application
    Filed: November 22, 2019
    Publication date: May 27, 2021
    Inventors: Jean-Philippe Vasseur, Vinay Kumar Kolar, Andrea Di Pietro, Grégory Mermoud, Pierre-Andre Savalle
  • INTERPRETABLE PEER GROUPING FOR COMPARING KPIs ACROSS NETWORK ENTITIES
    Publication number: 20210158260
    Abstract: In one embodiment, a network assurance service that monitors a network receives key performance indicators (KPIs) for a plurality of network entities in the network. The service applies clustering to the KPIs, to form KPI clusters. The service designates the network entities associated with the particular KPI cluster as belonging to a peer group, based in part on an assessment that the network entities associated with the particular KPI cluster share one or more attributes. The service uses a machine learning model to identify one of the network entities in the peer group as anomalous among the network entities in the peer group.
    Type: Application
    Filed: November 25, 2019
    Publication date: May 27, 2021
    Inventors: Vinay Kumar Kolar, Jean-Philippe Vasseur, Vikram Kumaran, Grégory Mermoud, Pierre-Andre Savalle
  • Learning packet capture policies to enrich context for device classification systems
    Patent number: 11018943
    Abstract: In various embodiments, a device classification service receives, from a networking device in a network, an indication that deep packet inspection (DPI) trace data is not available for an endpoint device in the network because the endpoint device does not match any DPI policies of the networking device. The service configures a first DPI policy on the networking device that causes it to capture a DPI trace of traffic associated with the endpoint device. The service receives, via a user interface, an indication that a subset of attributes of the endpoint device in the DPI trace is relevant to labeling the endpoint device with a device type. The service replaces the first DPI policy on the networking device with a second DPI policy that causes it to report only the subset of attributes of endpoint devices to the device classification service for endpoint devices that match the second DPI policy.
    Type: Grant
    Filed: May 20, 2020
    Date of Patent: May 25, 2021
    Assignee: Cisco Technology, Inc.
    Inventors: Jean-Philippe Vasseur, David Tedaldi, Grégory Mermoud, Pierre-André Savalle