Patents by Inventor Paul Pedersen

Paul Pedersen 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).

  • Patent number: 12023449
    Abstract: A patient interface includes a mask body, an elbow, a connector and a conduit. Any one or more of the mask body, the elbow, the connector and the conduit includes a bias flow vent. The bias flow vent is configured to deform with the application of pressure but not fully collapse such that an orifice size defined by the bias flow vent can vary with the application of pressure.
    Type: Grant
    Filed: January 21, 2021
    Date of Patent: July 2, 2024
    Assignee: Fisher & Paykel Healthcare Limited
    Inventors: Brett John Huddart, Andrew Paul Maxwell Salmon, Matthew James Pedersen, Hamish Joshua Rose, Fadi Karim Moh'd Mashal, Thomas Mark Richardson, Simon Mittermeier, Max Leon Betteridge
  • Patent number: 11928731
    Abstract: A method for virtual floor trading implemented via an exchange system includes establishing a secure connection with a first market participant and transmitting, to a first to a computing device associated with a first market participant, data causing a graphical user interface (GUI) of the computing device to render a graphical representation of a virtual trading floor associated with the exchange system. The method also includes receiving a first order and transmitting, to a second computing device associated with a second market participant, data causing a GUI of the second computing device to render a second graphical representation of the virtual trading floor comprising a first virtual trader associated with the first market participant. The method includes receiving, from the second computing device, a second order, determining that the second order matches the first order, and executing a transaction based on the first order and the second order.
    Type: Grant
    Filed: April 9, 2021
    Date of Patent: March 12, 2024
    Assignee: Cboe Exchange, Inc.
    Inventors: Scott Paul Pedersen, Jordan Newmark
  • Patent number: 11863466
    Abstract: Examples herein include systems and methods for providing capacity forecasting for high-usage periods of a computing infrastructure. An example method can include segmenting a first portion of a data stream and generating a first core set for a forecasting model that predicts future usage of computing resources. The example method can further include segmenting a second portion of the data stream, generating a second core set, and using both core sets to forecast usage. The first core set can then be phased out after a predetermined time period has elapsed such that forecasting is based only on the second core set. The example method can further include defining at least two clusters of data and performing predictive analysis on that specific cluster. Cluster-specific results can be displayed on a GUI, which can also provide a user with options for increase or decrease computing resources based on the predictions.
    Type: Grant
    Filed: December 2, 2021
    Date of Patent: January 2, 2024
    Assignee: VMware, Inc.
    Inventors: Darren Brown, Paul Pedersen
  • Patent number: 11748230
    Abstract: Various examples are disclosed for transitioning usage forecasting in a computing environment. Usage of computing resources of a computing environment are forecasted using a first forecasting data model and usage measurements obtained from the computing resources. A use of the first forecasting data model in forecasting the usage is transitioned to a second forecasting data model without incurring downtime in the computing environment. After the transition, the usage of the computing resources of the computing environment is forecasted using the second forecasting data model and the usage measurements obtained from the computing resources. The second forecasting data model exponentially decays the usage measurements based on a respective time period at which the usage measurements were obtained.
    Type: Grant
    Filed: May 20, 2021
    Date of Patent: September 5, 2023
    Assignee: VMWARE, INC.
    Inventors: Keshav Mathur, Jinyi Lu, Paul Pedersen, Junyuan Lin, Darren Brown, Peng Gao, Leah Nutman, Xing Wang
  • Publication number: 20230179539
    Abstract: Examples herein include systems and methods for providing capacity forecasting for high-usage periods of a computing infrastructure. An example method can include segmenting a first portion of a data stream and generating a first core set for a forecasting model that predicts future usage of computing resources. The example method can further include segmenting a second portion of the data stream, generating a second core set, and using both core sets to forecast usage. The first core set can then be phased out after a predetermined time period has elapsed such that forecasting is based only on the second core set. The example method can further include defining at least two clusters of data and performing predictive analysis on that specific cluster. Cluster-specific results can be displayed on a GUI, which can also provide a user with options for increase or decrease computing resources based on the predictions.
    Type: Application
    Filed: December 2, 2021
    Publication date: June 8, 2023
    Inventors: Darren Brown, Paul Pedersen
  • Patent number: 11640465
    Abstract: Computational methods and systems for detecting and troubleshooting anomalous behavior in distributed applications executing in a distributed computing system are described herein. Methods and systems discover nodes comprising the application. Anomaly detection monitors the metrics associated with the nodes for anomalous behavior in order to identify an approximate point in time when anomalous behavior begins to adversely impact performance of the application. Anomaly detection also monitors logs messages associated with the nodes to detect anomalous behavior recorded in the log messages. When anomalous behavior is detected in either the metrics and/or the log messages an alert identifying the anomalous behavior is generated. Troubleshooting guides an administrator and/or application owner to investigate the root cause of the anomalous behavior. Appropriate remedial measures may be determined based on the root cause and automatically or manually executed to correct the problem.
    Type: Grant
    Filed: November 13, 2019
    Date of Patent: May 2, 2023
    Assignee: VMware, Inc.
    Inventors: Darren Brown, Paul Pedersen, Keshav Mathur, Junyuan Lin, Nicholas Kushmerick, Jinyi Lu, Xing Wang, Peng Gao
  • Patent number: 11281520
    Abstract: Automated methods and systems described herein are directed to identifying potential root causes of a problem in a data center. Methods and systems receipt an alert or other notification of a problem occurring in a data center and a time when the problem was noticed. A search window is created based on the time and a stream of log messages generated in the search window is converted into a time dependent metric. An anomaly detection technique is applied to the metric to determine a start time of a problem. Logging events and key phrases in the log messages are identified in the search window and presented as potential root causes of the problem. The potential root cause may then be used by system administrators and/or tenants to diagnose the problem and execute remedial measures to correct the problem.
    Type: Grant
    Filed: June 5, 2020
    Date of Patent: March 22, 2022
    Assignee: VMware, Inc.
    Inventors: Jinyi Lu, Xing Wang, Shafi Khan, Apolak Borthakur, Paul Pedersen, Darren Brown, Gopal Harikumar
  • Publication number: 20210382770
    Abstract: Automated methods and systems described herein are directed to identifying potential root causes of a problem in a data center. Methods and systems receipt an alert or other notification of a problem occurring in a data center and a time when the problem was noticed. A search window is created based on the time and a stream of log messages generated in the search window is converted into a time dependent metric. An anomaly detection technique is applied to the metric to determine a start time of a problem. Logging events and key phrases in the log messages are identified in the search window and presented as potential root causes of the problem. The potential root cause may then be used by system administrators and/or tenants to diagnose the problem and execute remedial measures to correct the problem.
    Type: Application
    Filed: June 5, 2020
    Publication date: December 9, 2021
    Applicant: VMware, Inc.
    Inventors: Jinyi Lu, Xing Wang, Shafi Khan, Apolak Borthakur, Paul Pedersen, Darren Brown, Gopal Harikumar
  • Publication number: 20210271581
    Abstract: Various examples are disclosed for transitioning usage forecasting in a computing environment. Usage of computing resources of a computing environment are forecasted using a first forecasting data model and usage measurements obtained from the computing resources. A use of the first forecasting data model in forecasting the usage is transitioned to a second forecasting data model without incurring downtime in the computing environment. After the transition, the usage of the computing resources of the computing environment is forecasted using the second forecasting data model and the usage measurements obtained from the computing resources. The second forecasting data model exponentially decays the usage measurements based on a respective time period at which the usage measurements were obtained.
    Type: Application
    Filed: May 20, 2021
    Publication date: September 2, 2021
    Inventors: Keshav Mathur, Jinyi Lu, Paul Pedersen, Junyuan Lin, Darren Brown, Peng Gao, Leah Nutman, Xing Wang
  • Publication number: 20210212241
    Abstract: A system having a removable electronic component employs an abrasion-resistant thermally conductive film as a thermal interface between the removable electronic component and a heat sink. The abrasion-resistant film reduces thermal impedance between the removable electronic component and the heat sink when the removable electronic component is repeatedly installed and removed from a chamber in a host device. The abrasion-resistant film includes a polymer formed from a silicone-containing resin and an inorganic particulate filler; the film may also be interlocked with a corrosion protection layer at the heat sink. A method of forming a heat sink is provided that minimizes increases in thermal impedance.
    Type: Application
    Filed: March 18, 2021
    Publication date: July 8, 2021
    Inventors: Pradyumna Goli, Justin Kolbe, Reid J. Chesterfield, Paul A. Pedersen
  • Patent number: 11016870
    Abstract: Various examples are disclosed for forecasting resource usage and computing capacity utilizing an exponential decay. In some examples, a computing environment can obtain usage measurements from a data stream over a time interval, where the usage measurements describe utilization of computing resource. The computing environment can generate a weight function for individual ones of the usage measurements, where the weight function exponentially decays the usage measurements based on a respective time period at which the usage measurements were obtained. The computing environment can forecast a future capacity of the computing resources based on the usage measurements and the weight function assigned to the individual ones of the usage measurements. The computing environment can further upgrade a forecast engine to use the exponential decay without resetting the forecast engine or its memory.
    Type: Grant
    Filed: May 22, 2019
    Date of Patent: May 25, 2021
    Assignee: VMWARE, INC.
    Inventors: Keshav Mathur, Jinyi Lu, Paul Pedersen, Junyuan Lin, Darren Brown, Peng Gao, Leah Nutman, Xing Wang
  • Publication number: 20210141900
    Abstract: Computational methods and systems for detecting and troubleshooting anomalous behavior in distributed applications executing in a distributed computing system are described herein. Methods and systems discover nodes comprising the application. Anomaly detection monitors the metrics associated with the nodes for anomalous behavior in order to identify an approximate point in time when anomalous behavior begins to adversely impact performance of the application. Anomaly detection also monitors logs messages associated with the nodes to detect anomalous behavior recorded in the log messages. When anomalous behavior is detected in either the metrics and/or the log messages an alert identifying the anomalous behavior is generated. Troubleshooting guides an administrator and/or application owner to investigate the root cause of the anomalous behavior. Appropriate remedial measures may be determined based on the root cause and automatically or manually executed to correct the problem.
    Type: Application
    Filed: November 13, 2019
    Publication date: May 13, 2021
    Applicant: VMware, Inc.
    Inventors: Darren Brown, Paul Pedersen, Keshav Mathur, Junyuan Lin, Nicholas Kushmerick, Jinyi Lu, Xing Wang, Peng Gao
  • Publication number: 20210144164
    Abstract: Computational methods and systems to detect anomalous behaving resources and objects of a distributed computing system are described. Multiple streams of metric data representing usage of various resources of the distributed computing system are sent to a management system of the distributed computing system. The management system updates a performance model based on newly received metric values of the streams of metric data. The updated performance model is used to detect changes in one or more of the streams of metric data. The changes may be an indication of anomalous behavior at resources and objects associated with the streams of metric data. An anomaly listener is notified of anomalous behavior by the resource or object when a change in one or more of the streams of metric data is detected.
    Type: Application
    Filed: November 13, 2019
    Publication date: May 13, 2021
    Applicant: VMware, Inc.
    Inventors: Keshav Mathur, Jinyi Lu, Xing Wang, Darren Brown, Peng Gao, Junyuan Lin, Paul Pedersen
  • Patent number: 10956230
    Abstract: Various examples are disclosed for workload placement using forecast data. Forecast data for workloads and providers during a predefined period of time in the future is considered when identifying stressed providers and the feasibility of a workload move. Workloads with demand spikes at different future times can be matched by stacking current demand and forecast demand by timestamps. The possibility of stress can be reduced by making moves preemptively and considering forecast demand when evaluating the feasibility of a workload move.
    Type: Grant
    Filed: October 1, 2018
    Date of Patent: March 23, 2021
    Assignee: VMware, Inc.
    Inventors: Parikshit Santhana Gopalan Gopalan, Sandy Lau, Wei Li, Leah Nutman, Paul Pedersen, Yu Sun
  • Publication number: 20200371896
    Abstract: Various examples are disclosed for forecasting resource usage and computing capacity utilizing an exponential decay. In some examples, a computing environment can obtain usage measurements from a data stream over a time interval, where the usage measurements describe utilization of computing resource. The computing environment can generate a weight function for individual ones of the usage measurements, where the weight function exponentially decays the usage measurements based on a respective time period at which the usage measurements were obtained. The computing environment can forecast a future capacity of the computing resources based on the usage measurements and the weight function assigned to the individual ones of the usage measurements. The computing environment can further upgrade a forecast engine to use the exponential decay without resetting the forecast engine or its memory.
    Type: Application
    Filed: May 22, 2019
    Publication date: November 26, 2020
    Inventors: Keshav Mathur, Jinyi Lu, Paul Pedersen, Junyuan Lin, Darren Brown, Peng Gao, Leah Nutman, Xing Wang
  • Patent number: 10810052
    Abstract: Computational methods and systems that proactively manage usage of computational resources of a distributed computing system are described. A sequence of metric data representing usage of a resource is detrended to obtain a sequence of non-trendy metric data. Stochastic process models, a pulse wave model and a seasonal model of the sequence of non-trendy metric data are computed. When a forecast request is received, a sequence of forecasted metric data is computed over a forecast interval based on the estimated trend and one of the pulse wave or seasonal model that matches the periodicity of the sequence of non-trendy metric data. Alternatively, the sequence of forecasted metric data is computed based on the estimated trend and the stochastic process model with a smallest accumulated residual error. Usage of the resource by virtual objects of the distributed computing system may be adjusted based on the sequence of forecasted metric data.
    Type: Grant
    Filed: July 26, 2018
    Date of Patent: October 20, 2020
    Assignee: VMware, Inc.
    Inventors: Darren Brown, Junyuan Lin, Paul Pedersen, Keshav Mathur, Peng Gao, Xing Wang, Leah Nutman
  • Patent number: 10776166
    Abstract: Computational methods and systems that proactively manage usage of computational resources of a distributed computing system are described. A sequence of metric data representing usage of a resource is detrended to obtain a sequence of non-trendy metric data. Stochastic process models, a pulse wave model and a seasonal model of the sequence of non-trendy metric data are computed. When a forecast request is received, a sequence of forecasted metric data is computed over a forecast interval based on the estimated trend and one of the pulse wave or seasonal model that matches the periodicity of the sequence of non-trendy metric data. Alternatively, the sequence of forecasted metric data is computed based on the estimated trend and the stochastic process model with a smallest accumulated residual error. Usage of the resource by virtual objects of the distributed computing system may be adjusted based on the sequence of forecasted metric data.
    Type: Grant
    Filed: April 12, 2018
    Date of Patent: September 15, 2020
    Assignee: VMware, Inc.
    Inventors: Darren Brown, Junyuan Lin, Paul Pedersen, Keshav Mathur, Leah Nutman, Peng Gao, Xing Wang
  • Publication number: 20200104189
    Abstract: Various examples are disclosed for workload placement using forecast data. Forecast data for workloads and providers during a predefined period of time in the future is considered when identifying stressed providers and the feasibility of a workload move. Workloads with demand spikes at different future times can be matched by stacking current demand and forecast demand by timestamps. The possibility of stress can be reduced by making moves preemptively and considering forecast demand when evaluating the feasibility of a workload move.
    Type: Application
    Filed: October 1, 2018
    Publication date: April 2, 2020
    Inventors: Parikshit Santhana Gopalan Gopalan, Sandy Lau, Wei Li, Leah Nutman, Paul Pedersen, Yu Sun
  • Patent number: 10592169
    Abstract: The current document is directed to methods and systems that collect metric data within computing facilities, including large data centers and cloud-computing facilities. In a described implementation, input metric data is compressed by replacing each metric data point with a one-bit, two-bit, four-bit, or eight-bit compressed data value. During a first time window following reception of a metric data point, the metric data point remains available in uncompressed form to facilitate data analysis and monitoring functionalities that use uncompressed metric data. During a second time window, the metric data point is compressed and stored in memory, where the compressed data point remains available for data analysis and monitoring functionalities that use compressed metric data for detection of peaks, periodic patterns, and other characteristics. Finally, the compressed data point is archived in mass storage, where it remains available to data-analysis and management functionalities for a lengthy time period.
    Type: Grant
    Filed: November 27, 2017
    Date of Patent: March 17, 2020
    Assignee: VMware, Inc.
    Inventors: Paul Pedersen, Darren Brown, Wei Li, Leah Nutman, Sergio Nakai
  • Publication number: 20190317829
    Abstract: Computational methods and systems that proactively manage usage of computational resources of a distributed computing system are described. A sequence of metric data representing usage of a resource is detrended to obtain a sequence of non-trendy metric data. Stochastic process models, a pulse wave model and a seasonal model of the sequence of non-trendy metric data are computed. When a forecast request is received, a sequence of forecasted metric data is computed over a forecast interval based on the estimated trend and one of the pulse wave or seasonal model that matches the periodicity of the sequence of non-trendy metric data. Alternatively, the sequence of forecasted metric data is computed based on the estimated trend and the stochastic process model with a smallest accumulated residual error. Usage of the resource by virtual objects of the distributed computing system may be adjusted based on the sequence of forecasted metric data.
    Type: Application
    Filed: July 26, 2018
    Publication date: October 17, 2019
    Applicant: VMware, Inc.
    Inventors: Darren Brown, Junyuan Lin, Paul Pedersen, Keshav Mathur, Peng Gao, Xing Wang, Leah Nutman