Oracle America, Inc.

Oracle International Corporation

Sun Microsystems, Inc.

Bae Systems Information and Electronic Systems Integration Inc.

Kalyanaraman Vaidyanathan

Kenny C Gross

Aleksey M Urmanov

Ramakrishna C Dhanekula

Kenneth Clayton Gross

David Belanger

Dustin R Garvey

Anton A Bougaev

Timothy Tsai

Andrew Brownsword

Sajjit Thampy

Steven F Zwinger

Ayse K Coskun

David Brian Elting

Michelle C Murrett

Lik Wong

David K McElfresh

Stephen Ho

Keith A Whisnant

Andrew J Lewis

Sanjeev Raghavendrachar Sondur

Leoncio D Lopez

Craig Schelp

Guang-Tong Zhou

John J Cooley

Glenn A Herdeg

Ellen N Hein

Ramakrishna Dhanekula

Nazior Rahman

Debabrata Sarkar

Roger E Blythe

Jonathan Shuai

Ty M Danet

A system and method is provided that tests and determines whether candidate artificial intelligence model contains a Trojan from when it was trained and using the outcome determination of the Trojan to determine whether the candidate artificial intelligence model should be deployed. The system utilizes a first artificial intelligence that operates as a data generator and a second artificial intelligence that operates as a discriminator to determine whether the candidate artificial intelligence contains a Trojan. The first artificial intelligence combines sets of data with random Trojan triggers and the second artificial intelligence discriminates output classifications from the candidate artificial intelligence model to determine whether the Trojan is present based on probability outputs.

System for detecting trojans in an artificial network and method therof

A system for automatic prediction and generation of a Q-Code based on a text description provided in a NOTAM is provided. The present system may be utilized at a top level to generate a Q-Code from a text description or at a mid-level in the flight planning process to verify and/or confirm a human-generated Q-Code based on the text description in a NOTAM. Further, the present disclosure may allow for higher accuracy in the generation of Q-Codes thereby reducing the number of incorrect suboptimal and/or rejected flight plans produced by automatic flight planning systems.

System for automated generation of Q-Codes

The disclosed embodiments relate to a technique for training a prognostic pattern-recognition system to detect incipient anomalies that arise during execution of a computer system. During operation, the system gathers and stores telemetry data obtained from n sensors in the computer system during operation of the computer system. Next, the system uses the telemetry data gathered from the n sensors to train a baseline model for the prognostic pattern-recognition system. The prognostic pattern-recognition system then uses the baseline model in a surveillance mode to detect incipient anomalies that arise during execution of the computer system. The system also uses the stored telemetry data to train a set of additional models, wherein each additional model is trained to operate with one or more missing sensors. Finally, the system stores the additional models to be used in place of the baseline model when one or more sensors fail in the computer system.

Robust training technique to facilitate prognostic pattern recognition for enterprise computer systems

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.

Intelligent energy-optimization technique for computer datacenters

The disclosed embodiments relate to a system that reduces bandwidth requirements for transmitting telemetry data from sensors in a computer system. During operation, the system obtains a cross-imputability value for each sensor in a set of sensors that are monitoring the computer system, wherein a cross-imputability value for a sensor indicates how well a sensor value obtained from the sensor can be predicted based on sensor values obtained from other sensors in the set. Next, the system clusters sensors in the set of sensors into two or more groups based on the determined cross-imputability values. Then, while transmitting sensor values from the set of sensors, for a group of sensors having cross-imputability values exceeding a threshold, the system selectively transmits sensor values from some but not all of the sensors in the group to reduce a number of sensor values transmitted.

Reducing bandwidth requirements for telemetry data using a cross-imputability analysis technique

The disclosed embodiments relate to a system that characterizes I/O performance of a computing device in terms of energy consumption across a range of vibrational operating environments. During operation, the system executes a test script on a computing device that is affixed to a programmable vibration table, wherein the test script causes the computing device to perform a predetermined I/O workload. While the test script is executing, the system controls the programmable vibration table to subject the computing device to different vibrational operating environments. At the same time, the system obtains test results by monitoring a progress of the test script and an associated power consumption of the computing device. Finally, the system uses the obtained test results to characterize the I/O performance of the computing device in terms of energy consumption across the range of vibrational operating environments.

Characterizing the I/O-performance-per-watt of a computing device across a range of vibrational operating environments

The disclosed embodiments relate to a system for validating a prognostic-surveillance mechanism, which detects anomalies that arise during operation of a computer system. During operation, the system obtains telemetry data comprising a set of raw signals gathered from sensors in the computer system during operation of the computer system, wherein the telemetry signals are gathered over a monitored time period. Next, for each raw signal in the set of raw signals, the system decomposes the raw signal into deterministic and stochastic components. The system then generates a corresponding set of synthesized signals based on the deterministic and stochastic components of the raw signals, wherein the synthesized signals are generated for a simulated time period, which is longer than the monitored time period. Finally, the system uses the set of synthesized signals to validate one or more performance metrics of the prognostic-surveillance mechanism.

Technique for validating a prognostic-surveillance mechanism in an enterprise computer system

A system for controlling energy usage in a server having a processor, where the system includes a memory for storing energy cost information, and a controller for determining a transaction rate for the processor. The controller is also for determining a cumulative of energy expended by the server based on the determined transaction rate for each of a number of available power level states (P-states) for operation of the processor, and for selecting one of the available P-states for operation of the processor based on the determined cumulative energy expended and the stored energy cost information.

System and method for controlling energy usage in a server

The disclosed embodiments relate to a system that performs an intrusion-detection technique to differentiate between packets received from malicious remote users and legitimate local users in a networked computer system. During operation, the system determines arrival times for incoming packets at a node in the networked computer system. Next, the system determines inter-arrival times between the incoming packets from the arrival times. The system then determines a mean cumulative function (MCF) for the inter-arrival times by computing a cumulative sum of the inter-arrival times. Finally, upon detecting a change in a slope of the MCF, the system generates an alarm to indicate that a malicious remote user may be generating some of the incoming packets.

Inter-arrival time intrusion-detection technique to provide enhanced cybersecurity

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.

Sampling-densification technique to facilitate high-sampling-density signatures for telemetry data in enterprise computing systems

The disclosed embodiments provide a system that analyzes telemetry data from a computer system. During operation, the system obtains the telemetry data, which includes first information containing telemetric signals gathered using sensors in the computer system and second information that indicates one or more transaction latencies of software running on the computer system. Upon detecting an upward trend in the one or more transaction latencies, the system analyzes the telemetry data for a correlation between the one or more transaction latencies and one or more environmental factors represented by a subset of the telemetric signals. Upon identifying the correlation between the one or more transaction latencies and an environmental factor, the system stores an indication that the environmental factor may be contributing to the upward trend in the one or more transaction latencies.

Intelligent inter-process communication latency surveillance and prognostics

A system for generating a power consumption model of at least one server includes one or more computers configured to obtain n time series telemetry signals indicative of operating parameters of the at least one server, obtain a time series power signal indicative of power consumed by the at least one server, and correlate each of the n time series telemetry signals with the time series power signal. The one or more computers are further configured to select a set of the n time series telemetry signals having an overall correlation with the time series power signal greater than a predetermined threshold, and generate a power consumption model of the at least one server based on at least the set of the n time series telemetry signals.

Method and system for generating a power consumption model of at least one server

Computer system fans having fixed operating states corresponding to discreet operating speeds may be controlled by collecting temperature information upstream or downstream of the fans and commanding the fans to switch between the fixed operating states based on the temperature information at a frequency sufficient to controllably achieve speeds between the discreet operating speeds.

System and method for controlling computer system fan speed

Some embodiments of the present invention provide a system that determines whether a cooling device in a computer system is responsive to control signals. During operation of the computer system, a control signal is sent to the cooling device. Next, a response of the computer system to the control signal is measured, wherein the response includes a temperature profile. The frequency content of the control signal is then compared to the frequency content of the temperature profile to determine whether the cooling device is responsive to the control signal.

Growing community of inventors

San Diego, CA, United States of America

Kalyanaraman Vaidyanathan