Patents by Inventor Sukrit Dasgupta

Sukrit Dasgupta 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).

  • Publication number: 20200052981
    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: Application
    Filed: August 10, 2018
    Publication date: February 13, 2020
    Inventors: Santosh Ghanshyam Pandey, Jean-Philippe Vasseur, Sukrit Dasgupta
  • Patent number: 10540605
    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.
    Type: Grant
    Filed: July 19, 2013
    Date of Patent: January 21, 2020
    Assignee: Cisco Technology, Inc.
    Inventors: Grégory Mermoud, Jean-Philippe Vasseur, Sukrit Dasgupta
  • Patent number: 10498752
    Abstract: In one embodiment, a node in a network detects an anomaly in the network based on a result of a machine learning-based anomaly detector analyzing network traffic. The node determines a packet capture policy for the anomaly by applying a machine learning-based classifier to the result of the anomaly detector. The node selects a set of packets from the analyzed traffic based on the packet capture policy. The node stores the selected set of packets for the detected anomaly.
    Type: Grant
    Filed: July 15, 2016
    Date of Patent: December 3, 2019
    Assignee: Cisco Technology, Inc.
    Inventors: Andrea Di Pietro, Jean-Philippe Vasseur, Sukrit Dasgupta
  • Publication number: 20190363951
    Abstract: In one embodiment, one or more reporting nodes are selected to report network metrics in a network. From a monitoring node in the network, a trigger message is sent to the one or more reporting nodes. The trigger message may trigger the one or more reporting nodes to report one or more network metrics local to the respective reporting node. In response to the trigger message, a report of the one or more network metrics is received at the monitoring node from one of the one or more reporting nodes.
    Type: Application
    Filed: August 6, 2019
    Publication date: November 28, 2019
    Inventors: Jean-Philippe Vasseur, Grégory Mermoud, Sukrit Dasgupta
  • Patent number: 10484255
    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.
    Type: Grant
    Filed: June 19, 2017
    Date of Patent: November 19, 2019
    Assignee: Cisco Technology, Inc.
    Inventors: Andrea Di Pietro, Grégory Mermoud, Jean-Philippe Vasseur, Sukrit Dasgupta
  • Patent number: 10484405
    Abstract: In one embodiment, a first device in a network identifies an anomalous traffic flow in the network. The first device reports the anomalous traffic flow to a supervisory device in the network. The first device determines a quarantine policy for the anomalous traffic flow. The first device determines an action policy for the anomalous traffic flow. The first device applies the quarantine and action policies to one or more packets of the anomalous traffic flow.
    Type: Grant
    Filed: January 23, 2015
    Date of Patent: November 19, 2019
    Assignee: Cisco Technology, Inc.
    Inventors: Sukrit Dasgupta, Jean-Philippe Vasseur
  • Patent number: 10484406
    Abstract: In one embodiment, a first device in a network maintains raw traffic flow information for the network. The first device provides a compressed summary of the raw traffic flow information to a second device in the network. The second device is configured to transform the compressed summary for presentation to a user interface. The first device detects an anomalous traffic flow based on an analysis of the raw traffic flow information using a machine learning-based anomaly detector. The first device provides at least a portion of the raw traffic flow information related to the anomalous traffic flow to the second device for presentation to the user interface.
    Type: Grant
    Filed: January 7, 2016
    Date of Patent: November 19, 2019
    Assignee: Cisco Technology, Inc.
    Inventors: Jean-Philippe Vasseur, Grégory Mermoud, Sukrit Dasgupta, Xav Laumonier
  • Patent number: 10425294
    Abstract: In one embodiment, one or more reporting nodes are selected to report network metrics in a network. From a monitoring node in the network, a trigger message is sent to the one or more reporting nodes. The trigger message may trigger the one or more reporting nodes to report one or more network metrics local to the respective reporting node. In response to the trigger message, a report of the one or more network metrics is received at the monitoring node from one of the one or more reporting nodes.
    Type: Grant
    Filed: January 27, 2014
    Date of Patent: September 24, 2019
    Assignee: Cisco Technology, Inc.
    Inventors: Jean-Philippe Vasseur, Grégory Mermoud, Sukrit Dasgupta
  • Patent number: 10389613
    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.
    Type: Grant
    Filed: January 16, 2018
    Date of Patent: August 20, 2019
    Assignee: Cisco Technology, Inc.
    Inventors: Sukrit Dasgupta, Jean-Philippe Vasseur, Grégory Mermoud
  • Patent number: 10277476
    Abstract: In one embodiment, a predictive model is constructed by mapping multiple network characteristics to multiple network performance metrics. Then, a network performance metric pertaining to a node in a network is predicted based on the constructed predictive model and one or more network characteristics relevant to the node. Also, a local parameter of the node is optimized based on the predicted network performance metric.
    Type: Grant
    Filed: January 27, 2014
    Date of Patent: April 30, 2019
    Assignee: Cisco Technology, Inc.
    Inventors: Grégory Mermoud, Jean-Philippe Vasseur, Sukrit Dasgupta
  • Patent number: 10218726
    Abstract: In one embodiment, a networking device in a network causes formation of device clusters of devices in the network. The devices in a particular cluster exhibit similar characteristics. The networking device receives feedback from a device identity service regarding the device clusters. The feedback is based in part on the device identity service probing the devices. The networking device adjusts the device clusters based on the feedback from the device identity service. The networking device performs anomaly detection in the network using the adjusted device clusters.
    Type: Grant
    Filed: June 13, 2016
    Date of Patent: February 26, 2019
    Assignee: Cisco Technology, Inc.
    Inventors: Jean-Philippe Vasseur, Grégory Mermoud, Pierre-André Savalle, Andrea Di Pietro, Sukrit Dasgupta
  • Patent number: 10182066
    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.
    Type: Grant
    Filed: November 2, 2017
    Date of Patent: January 15, 2019
    Assignee: Cisco Technology, Inc.
    Inventors: Fabien Flacher, Grégory Mermoud, Jean-Philippe Vasseur, Sukrit Dasgupta
  • Publication number: 20180367428
    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.
    Type: Application
    Filed: June 19, 2017
    Publication date: December 20, 2018
    Inventors: Andrea Di Pietro, Grégory Mermoud, Jean-Philippe Vasseur, Sukrit Dasgupta
  • Publication number: 20180357560
    Abstract: In one embodiment, a device identifies a new data source of characteristics data for a monitored network. The device initiates a quarantine period for the characteristic data from the new data source. The characteristic data from the new data source is quarantined from input to a machine learning-based analyzer during the quarantine period. The device models the characteristic data from the new data source during the quarantine period, to determine whether the characteristic data from the new data source is reliable for input to the machine learning-based analyzer. After the quarantine period, the device provides the characteristic data from the new data source to the machine learning-based analyzer based on a determination that the characteristic data from the new data source is reliable.
    Type: Application
    Filed: June 12, 2017
    Publication date: December 13, 2018
    Inventors: Andrea Di Pietro, Grégory Mermoud, Sukrit Dasgupta, Jean-Philippe Vasseur
  • Patent number: 10103970
    Abstract: Statistical and historical values of performance metrics are actively used to influence routing decisions for optimum topologies in a constrained network. Traffic service level is constantly monitored and compared with a service level agreement. If deviation exists between the monitored traffic service level and the terms of the service level agreement, stability metrics are used to maintain paths through the network that meet the terms of the traffic service level agreement or that improve the traffic flow through the network. Backup parent selection for a node in the network is performed based on previous performance of backup parents for the node.
    Type: Grant
    Filed: May 4, 2016
    Date of Patent: October 16, 2018
    Assignee: CISCO TECHNOLOGY, INC.
    Inventors: Sukrit Dasgupta, Jean-Philippe Vasseur, Grégory Mermoud
  • Patent number: 10075360
    Abstract: In one embodiment, a learning machine may be used to select observer nodes in a LLN such that the liveness of one or more nodes of interest may be monitored indirectly. In particular, a management device may receive network data on one or more network traffic parameters of a computer network. The management device may then determine, based on the network data, a candidate list of potential observer nodes to monitor activity or inactivity of one or more subject nodes. The management device may then dynamically select, using a machine learning model, a set of optimized observer nodes from the candidate list of potential observer nodes.
    Type: Grant
    Filed: January 27, 2014
    Date of Patent: September 11, 2018
    Assignee: Cisco Technology, Inc.
    Inventors: Jean-Philippe Vasseur, Grégory Mermoud, Jonathan W. Hui, Sukrit Dasgupta
  • Patent number: 10062036
    Abstract: In one embodiment, a network device receives metrics regarding a path in the network. A predictive model is generated using the received metrics and is operable to predict available bandwidth along the path for a particular type of traffic. A determination is made as to whether a confidence score for the predictive model is below a confidence threshold associated with the particular type of traffic. The device obtains additional data regarding the path based on a determination that the confidence score is below the confidence threshold. The predictive model is updated using the additional data regarding the path.
    Type: Grant
    Filed: May 16, 2014
    Date of Patent: August 28, 2018
    Assignee: Cisco Technology, Inc.
    Inventors: Grégory Mermoud, Jean-Philippe Vasseur, Sukrit Dasgupta
  • Patent number: 10044741
    Abstract: In one embodiment, a first device in a network receives traffic flow data from a plurality of devices in the network. The traffic flow data from at least one of the plurality of devices comprises raw packets of a traffic flow. The first device selects a set of reporting devices from among the plurality of devices based on the received traffic flow data. The first device provides traffic flow reporting instructions to the selected set of reporting devices. The traffic flow reporting instructions cause each reporting device to provide sampled traffic flow data to an anomaly detection device.
    Type: Grant
    Filed: June 26, 2017
    Date of Patent: August 7, 2018
    Assignee: Cisco Technology, Inc.
    Inventors: Jean-Philippe Vasseur, Sukrit Dasgupta, Thomas Reuther
  • Patent number: 10009364
    Abstract: In one embodiment, a first device in a network identifies a first traffic flow between two endpoints that traverses the first device in a first direction. The first device receives information from a second device in the network regarding a second traffic flow between the two endpoints that traverses the second device in a second direction that is opposite that of the first direction. The first device merges characteristics of the first traffic flow captured by the first device with characteristics of the second traffic flow captured by the second device and included in the information received from the second device, to form an input feature set. The first device detects an anomaly in the network by analyzing the input feature set using a machine learning-based anomaly detector.
    Type: Grant
    Filed: July 18, 2016
    Date of Patent: June 26, 2018
    Assignee: Cisco Technology, Inc.
    Inventors: Sukrit Dasgupta, Jean-Philippe Vasseur, Andrea Di Pietro
  • Patent number: 10003473
    Abstract: In one embodiment, a time period is identified in which probe packets are to be sent along a path in a network based on predicted user traffic along the path. The probe packets are then sent during the identified time period along the path. Conditions of the network path are monitored during the time period. The rate at which the packets are sent during the time period is dynamically adjusted based on the monitored conditions. Results of the monitored conditions are collected, to determine an available bandwidth limit along the path.
    Type: Grant
    Filed: September 22, 2017
    Date of Patent: June 19, 2018
    Assignee: Cisco Technology, Inc.
    Inventors: Jean-Philippe Vasseur, Sukrit Dasgupta