Oracle America, Inc.

Sun Microsystems, Inc.

Ramakrishna C Dhanekula

Kenny C Gross

Kalyanaraman Vaidyanathan

Keith A Whisnant

Aleksey M Urmanov

Andrew J Lewis

David K McElfresh

Steven F Zwinger

Kenneth Clayton Gross

Robert Paul Masleid

Gregory A Cumberford

Glenn A Herdeg

Eugenio J Schuster

One embodiment provides a system that analyzes telemetry data from a monitored system. During operation, the system periodically obtains the telemetry data as a set of telemetry variables from the monitored system and updates a multidimensional real-time distribution of the telemetry data using the obtained telemetry variables. Next, the system analyzes a statistical deviation of the multidimensional real-time distribution from a multidimensional reference distribution for the monitored system using a multivariate sequential probability ratio test (SPRT) and assesses the integrity of the monitored system based on the statistical deviation of the multidimensional real-time distribution. If the assessed integrity falls below a threshold, the system determines a fault in the monitored system corresponding to a source of the statistical deviation.

Telemetry data analysis using multivariate sequential probability ratio test

A system that balances thermal variations within a set of computer systems in a datacenter. During operation, the system obtains a thermal flux map for the set of computer systems. The system then analyzes the thermal flux map to determine whether imbalances exist in the thermal flux across the set of computer systems. If so, the system can adjust: (1) the scheduling of loads across the set of computer systems, and/or (2) air conditioning within the datacenter, so that the thermal flux is more balanced across the set of computer systems.

Method and apparatus for balancing thermal variations across a set of computer systems

One embodiment provides a system that analyzes a target electromagnetic signal radiating from a monitored system. During operation, the system monitors the target electromagnetic signal using a near-isotropic antenna that includes a set of receiving surfaces arranged in a regular polyhedron. Next, the system obtains a set of received target electromagnetic signals from the receiving surfaces. Finally, the system assesses the integrity of the monitored system by separately analyzing each of the received target electromagnetic signals.

Near-isotropic antenna for monitoring electromagnetic signals

A method for identifying a degraded fan measures acoustic data from an operating datacenter fan. A motor rotation frequency and a vane passing frequency are determined from the acoustic data. Amplitudes of the frequencies are determined from the acoustic data. If the amplitude of the motor rotation frequency is greater than the amplitude of the vane passing frequency, then it is determined that the fan is degraded.

Identifying degraded fans in datacenters

Some embodiments provide a system that analyzes telemetry data from a computer system. During operation, the system obtains the telemetry data as a set of telemetric signals using a set of sensors in the computer system, wherein the set of sensors includes temperature sensors at different locations in a cooling airflow through the computer system. Next, the system calculates a set of pairwise temperature differences from the telemetric signals. The system then infers an altitude of the computer system based on the pairwise temperature differences. Finally, the system uses the inferred altitude to manage the operation of the computer system.

Inference of altitude using pairwise comparison of telemetry/temperature signals using regression analysis

One embodiment of the present invention provides a system that non-intrusively detects counterfeit components in a target computer system. During operation, the system collects target electromagnetic interference (EMI) signals generated by the target computer system using one or more antennas positioned in close proximity to the target computer system. The system then generates a target EMI fingerprint for the target computer system from the target EMI signals. Next, the system compares the target EMI fingerprint against a reference EMI fingerprint to determine whether the target computer system contains a counterfeit component.

Detecting counterfeit electronic components using EMI telemetric fingerprints

One embodiment provides a technique for analyzing a target electromagnetic signal radiating from a monitored system. During the technique, the monitored system is positioned at a first locus of an ellipsoidal surface to amplify the target electromagnetic signal received at a second locus of the ellipsoidal surface. Next, the amplified target electromagnetic signal is monitored using an antenna positioned at the second locus of the ellipsoidal surface. Finally, the integrity of the monitored system is assessed by analyzing the amplified target electromagnetic signal monitored by the antenna.

Radio frequency microscope for amplifying and analyzing electromagnetic signals by positioning the monitored system at a locus of an ellipsoidal surface

One embodiment of the present invention provides a system that characterizes a computer system parameter by analyzing a target electromagnetic signal radiating from the computer system. First, the system monitors the target electromagnetic signal using a first directional antenna located outside of the computer system, wherein the first directional antenna is directed at a location inside the computer system. The system also monitors the target electromagnetic signal using a second directional antenna located outside of the computer system, wherein a receiving axis of the second antenna is oriented non-parallel to a receiving axis of the first antenna, and wherein the second directional antenna is directed at the location inside the computer system. Next, the system characterizes the computer system parameter based on the target electromagnetic signal received from the first antenna and the target electromagnetic signal received from the second antenna. Then, the system generates a request for an action based on the characterization of the computer system.

Analyzing a target electromagnetic signal radiating from a computer system

One embodiment provides a system that analyzes a target electromagnetic signal radiating from a monitored system. During operation, the system monitors the target electromagnetic signal using a set of antennas to obtain a set of received target electromagnetic signals from the monitored system. Next, the system calculates a weighted mean of the received target electromagnetic signals using a first pattern-recognition model. The system then subtracts the received target electromagnetic signals from the weighted mean of the received target electromagnetic signals to obtain a set of noise-reduced signals for the monitored system. Finally, the system assesses the integrity of the monitored system by analyzing the noise-reduced signals using a second pattern-recognition model.

Noise reduction technique for monitoring electromagnetic signals

Some embodiments of the present invention provide a system that characterizes a computer system using a pattern-recognition model. First, values for an environmental parameter are monitored from a set of sensors associated with the computer system. Then, a baseline for the environmental parameter is calculated based on the monitored values from a subset of the set of sensors. Next, the baseline is subtracted from the monitored values from sensors in the set of sensors to produce compensated values. Then, the compensated values are used as inputs to the pattern-recognition model, which produces estimates for the compensated values based on correlations between the compensated values learned during a training phase. Next, residuals are calculated by subtracting the estimates for the compensated values from the compensated values. Then, the residuals are analyzed to characterize the computer system.

Characterizing a computer system using a pattern-recognition model

One embodiment of the present invention provides a system that determines a total whisker length for conductive whiskers on a circuit in a computer system. During operation, a target electromagnetic signal radiating from the computer system is monitored. Then, the target electromagnetic signal is analyzed to determine the total whisker length for conductive whiskers on the circuit in the computer system.

Determining a total length for conductive whiskers in computer systems

Some embodiments of the present invention provide a system that generates extended data for a pattern-recognition model used in electronic prognostication for a computer system. During operation the system determines, for each sensor in a set of sensors, a regression coefficient between training data from the sensor and training data from each of the other sensors in the set of sensors. Next, for each sensor in the set of sensors, the system stretches the training data from each of the other sensors by a predetermined amount, and generates extended data for the sensor based on the stretched training data for each of the other sensors and the regression coefficients between training data from the sensor and training data from each of the other sensors.

Generating extended data from a pattern-recognition model for a computer system

One embodiment of the present invention provides a system that proactively monitors and detects metal whisker growth in a target area within a computer system. During operation, the system collects target electromagnetic interference (EMI) signals using one or more antennas positioned in the vicinity of the target area. Next, the system analyzes the target EMI signals to proactively detect the onset of metal whisker growth in the target area.

Proactive detection of metal whiskers in computer systems

One embodiment of the present invention provides a system that monitors a physical variable associated with an electronic component within a computer system. During operation, the system receives telemetry signals of the physical variable which are collected by one or more physical sensors associated with the electronic component. The system also collects electromagnetic interference (EMI) signals generated by the electronic component. Next, the system builds an inferential model for the physical variable by correlating the EMI signals with the telemetry signals. The system then uses the inferential model to infer values for the physical variable from the EMI signals.

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San Diego, CA, United States of America

Ramakrishna C Dhanekula