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71.发明申请公开(公告)号：US20190303810A1
公开(公告)日：2019-10-03
申请号：US15938988
申请日：2018-03-28
Applicant: Oracle International Corporation
Inventor： Kenny C. Gross , Andrew I. Vakhutinsky , DeJun Li , Bradley R. Williams , Sungpack Hong
Abstract: The disclosed embodiments relate to a system that facilitates deployment of utility repair crews to nodes in a utility network. During operation, the system determines a node criticality for each node in the utility network based on a network-reliability analysis, which considers interconnections among the nodes in the utility network. The system also determines a node failure probability for each node in the utility network based on historical weather data, historical node failure data and weather forecast information for the upcoming weather event. The system uses the determined node criticalities and the determined node failure probabilities to determine a deployment plan for deploying repair crews to nodes in the utility network in preparation for the upcoming weather event. The system then presents the deployment plan to a person who uses the deployment plan to deploy repair crews to be available to service nodes in the utility network.
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公开(公告)号：US10310459B2
公开(公告)日：2019-06-04
申请号：US15715692
申请日：2017-09-26
Applicant: Oracle International Corporation
Inventor： Kenny C. Gross , Mengying Li , Benjamin P. Franklin, Jr.
Abstract: During operation, the system receives a set of input signals containing electrical usage data from a set of smart meters, wherein each smart meter gathers electrical usage data from a customer of the utility system. Next, the system uses the set of input signals to train an inferential model, which learns correlations among the set of input signals, and uses the inferential model to produce a set of inferential signals, wherein an inferential signal is produced for each input signal in the set of input signals. The system then uses a Fourier-based technique to decompose each inferential signal into deterministic and stochastic components, and uses the deterministic and stochastic components to generate a set of synthesized signals, which are statistically indistinguishable from the inferential signals. Finally, the system projects the set of synthesized signals into the future to produce a forecast for the electricity demand.
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73.发明申请公开(公告)号：US20190163719A1
公开(公告)日：2019-05-30
申请号：US15826461
申请日：2017-11-29
Applicant: Oracle International Corporation
Inventor： Kenny C. Gross , Mengying Li , Tahereh Masoumi
Abstract: We present a system that performs prognostic surveillance operations based on sensor signals from a power plant and critical assets in the transmission and distribution grid. The system obtains signals comprising time-series data obtained from sensors during operation of the power plant and associated transmission grid. The system uses an inferential model trained on previously received signals to generate estimated values for the signals. The system then performs a pairwise differencing operation between actual values and the estimated values for the signals to produce residuals. The system subsequently performs a sequential probability ratio test (SPRT) on the residuals to detect incipient anomalies that arise during operation of the power plant and associated transmission grid. While performing the SPRT, the system dynamically updates SPRT parameters to compensate for non-Gaussian artifacts that arise in the sensor data due to changing operating conditions. When an anomaly is detected, the system generates a notification.
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公开(公告)号：US20180260560A1
公开(公告)日：2018-09-13
申请号：US15457523
申请日：2017-03-13
Applicant: Oracle International Corporation
Inventor： Kenny C. Gross , Eric S. Chan , Dieter Gawlick
Abstract: The disclosed embodiments relate to a system for analyzing telemetry data. During operation, the system obtains telemetry data gathered from sensors during operation of a monitored system. Next, the system applies a univariate model to the telemetry data to identify an operational phase for the monitored system, wherein the univariate model analyzes an individual signal in the telemetry data without reference to other signals in the telemetry data. The system then selects a phase-specific multivariate model based on the identified operational phase, wherein the phase-specific multivariate model was previously trained based on telemetry data gathered while the system was operating in the identified operational phase. Finally, the system uses the phase-specific multivariate model to monitor the telemetry data to detect incipient anomalies associated with the operation of the monitored system.
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公开(公告)号：US20180059745A1
公开(公告)日：2018-03-01
申请号：US15247264
申请日：2016-08-25
Applicant: Oracle International Corporation
Inventor： Kenny C. Gross , Kalyanaraman Vaidyanathan , Sanjeev Sondur
CPC classification number: G06F1/206 , H05K7/20836 , Y02D10/16
Abstract: The disclosed embodiments relate to a system that controls cooling in a computer system. During operation, this system monitors a temperature of one or more components in the computer system. Next, the system determines a thermal-headroom margin for each of the one or more components in the computer system by subtracting the temperature of the component from a pre-specified maximum operating temperature of the component. Then, the system controls a cooling system that regulates an ambient air temperature for the computer system based on the determined thermal-headroom margins for the one or more components. In some embodiments, controlling the cooling system additionally involves minimizing a collective energy consumption of the computer system and the cooling system.
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Patent Agency Ranking
公开(公告)号：US20170359234A1
公开(公告)日：2017-12-14
申请号：US15180812
申请日：2016-06-13
Applicant: Oracle International Corporation
Inventor： Kenny C. Gross , Kalyanaraman Vaidyanathan , Dustin R. Garvey , Lik Wong
CPC classification number: G06F11/3476 , G06F11/008 , G06F11/263 , G06F11/3058 , G06F17/40
Abstract: The disclosed embodiments relate to a system that gathers telemetry data while testing a computer system. During operation, the system obtains a test script that generates a load profile to exercise the computer system, wherein a running time of the test script is designed to be relatively prime in comparison to a sampling interval for telemetry data in the computer system. Next, the system gathers telemetry data during multiple successive executions of the test script on the computer system. The system merges the telemetry data gathered during the multiple successive executions of the test script, wherein the relatively prime relationship between the running time of the test script and the sampling interval for the telemetry data causes a sampling point for the telemetry data to precess through different points in the test script during the multiple successive executions of the test script, thereby densifying sampled telemetry data points gathered for the test script. Finally, the system outputs the densified telemetry data.
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公开(公告)号：US09600394B2
公开(公告)日：2017-03-21
申请号：US14743847
申请日：2015-06-18
Applicant: Oracle International Corporation
Inventor： Sampanna S. Salunke , Dustin R. Garvey , Lik Wong , Kenny C. Gross
CPC classification number: G06F11/3612 , G06F11/0712 , G06F11/0754 , G06F11/3452 , G06F11/3466 , G06F11/3608
Abstract: The disclosed embodiments provide a system that detects anomalous events. During operation, the system obtains machine-generated time-series performance data collected during execution of a software program in a computer system. Next, the system removes a subset of the machine-generated time-series performance data within an interval around one or more known anomalous events of the software program to generate filtered time-series performance data. The system uses the filtered time-series performance data to build a statistical model of normal behavior in the software program and obtains a number of unique patterns learned by the statistical model. When the number of unique patterns satisfies a complexity threshold, the system applies the statistical model to subsequent machine-generated time-series performance data from the software program to identify an anomaly in an activity of the software program and stores an indication of the anomaly for the software program upon identifying the anomaly.
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公开(公告)号：US12181998B2
公开(公告)日：2024-12-31
申请号：US18171620
申请日：2023-02-20
Applicant: Oracle International Corporation
Inventor： Kenny C. Gross , Sanjeev Raghavendrachar Sondur , Guang Chao Wang
Abstract: A model-based approach to determining an optimal configuration for a data center may use an environmental chamber to characterize the performance of various data center configurations at different combinations of temperature and altitude. Telemetry data may be recorded from different configurations as they execute a stress workload at each temperature/altitude combination, and the telemetry data may be used to train a corresponding library of models. When a new data center is being configured, the temperature/altitude of the new data center may be used to select a pre-trained model from a similar temperature/altitude. Performance of the current configuration can be compared to the performance of the model, and if the model performs better, a new configuration based on the model may be used as an optimal configuration for the data center.
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公开(公告)号：US12158548B2
公开(公告)日：2024-12-03
申请号：US17735245
申请日：2022-05-03
Applicant: ORACLE INTERNATIONAL CORPORATION
Inventor： Matthew T. Gerdes , Guang C. Wang , Timothy D. Cline , Kenny C. Gross
Abstract: Systems, methods, and other embodiments associated with acoustic fingerprint identification of devices are described. In one embodiment, a method includes generating a target acoustic fingerprint from acoustic output of a target device. A similarity metric is generated that quantifies similarity of the target acoustic fingerprint to a reference acoustic fingerprint of a reference device. The similarity metric is compared to a threshold. In response to a first comparison result of the comparing of the similarity metric to the threshold, the target device is indicated to match the reference device. In response to a second comparison result of the comparing of the similarity metric to the threshold, it is indicated that the target device does not match the reference device.
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80.发明授权公开(公告)号：US12038830B2
公开(公告)日：2024-07-16
申请号：US17090151
申请日：2020-11-05
Applicant: Oracle International Corporation
Inventor： Rui Zhong , Guang C. Wang , Kenny C. Gross , Ashin George , Zexi Chen
CPC classification number: G06F11/3688 , G06F11/3692 , G06F21/602 , G06N20/00
Abstract: A double-blind comparison is performed between prognostic-surveillance systems, which are located on a local system and a remote system. During operation, the local system inserts random faults into a dataset to produce a locally seeded dataset, wherein the random faults are inserted into random signals at random times with variable fault signatures. Next, the local system exchanges the locally seeded dataset with a remote system, and in return receives a remotely seeded dataset, which was produced by the remote system by inserting different random faults into the same dataset. Next, the local system uses a local prognostic-surveillance system to analyze the remotely seeded dataset to produce locally detected faults. Finally, the local system determines a performance of the local prognostic-surveillance system by comparing the locally detected faults against actual faults in the remotely seeded fault information. The remote system similarly determines a performance of a remote prognostic-surveillance system.
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