Method and apparatus for identifying a failure mechanism for a component in a computer system

• US 7,890,813 B2
• Filed: 05/11/2006
• Issued: 02/15/2011
• Est. Priority Date: 05/11/2006
• Status: Active Grant

• Current Assignee: Oracle America, Inc. (Oracle Corporation)
• Original Assignee: Oracle America, Inc. (Oracle Corporation)
• Inventors: Usynin, Alexander V., Gross, Kenny C., Urmanov, Aleksey M.
• Primary Examiner(s): Beausoliel; Robert
• Assistant Examiner(s): Arcos; Jeison C
• Application Number:
  US11/432,644
• Publication Number:
  US 20070294591A1
• Time in Patent Office: 1,741 Days
• Field of Search: 714/25, 702/182, 702/183, 379/106.01, 379/106.02, 379/106.03, 600/513
• US Class Current: 714/45
• CPC Class Codes: G06F 1/30 Means for acting in the event of power-supply failure or interruption, e.g. power-supply fluctuations for resetting only G06F1/24
• CPC Class Codes: G06F 11/0748 in a remote unit communicating with a single-box computer node experiencing an error/fault remote testing G06F11/2294
• CPC Class Codes: G06F 11/0751 Error or fault detection not based on redundancy power supply failures G06F1/30; network fault management H04L41/06
• CPC Class Codes: G06F 11/2252 using fault dictionaries

Abstract

One embodiment of the present invention provides a system that identifies a failure mechanism for a component. The system first constructs a library of failure signatures from a set of components, wherein each failure signature in the library characterizes a known failure mechanism associated with a component in the set of components. Next, the system receives a telemetry signal which is measured from a component under surveillance. The system then determines if there is an anomaly in the telemetry signal. If so, the system performs pattern-matching operations between the telemetry signal and failure signatures in the library. Next, if a match is found, the system identifies the failure mechanism for the component under surveillance based on the matching failure signature.

Claims

1. A method for identifying a failure mechanism for a component, comprising:

constructing a library of failure signatures from a set of components, wherein each failure signature in the library characterizes a known failure mechanism associated with a component in the set of components, and the failure signature is stored at a high-resolution;

receiving a telemetry signal which is measured from a component under surveillance, wherein the telemetry signal is measured at a low-resolution;

determining if there is an anomaly in the telemetry signal, and if so;

performing pattern-matching operations between the telemetry signal and failure signatures in the library; and

if a match is found, identifying the failure mechanism for the component under surveillance based on the matching failure signature,

wherein the pattern-matching operations recall the high-resolution failure signature based on the low-resolution telemetry signal.

2. The method of claim 1, wherein constructing the library of failure signatures involves constructing a failure signature for each known failure mechanism of a component, which involves:

receiving one or more faulty specimens of the component, wherein the one or more faulty specimens are associated with a known failure mechanism;

collecting telemetry signals from the one or more faulty specimens, wherein the telemetry signals contain the failure signature of the known failure mechanism associated with the component, and wherein the telemetry signals have sufficiently high-resolution and high-sampling-rate for use in pattern-matching operations; and

storing the failure signature for the known failure mechanism of the component in the library of failure signatures.

3. The method of claim 1, wherein constructing the library of failure signatures involves storing the failure signatures in one or more auto-associative memory matrices of failure signatures, wherein each auto-associative memory matrix contains failure signatures for at least one corresponding type or level of failure patterns.

4. The method of claim 3, wherein performing the pattern-matching operations between the telemetry signal and the failure signatures in the library involves using an auto-associative memory, which involves:

feeding the anomalous telemetry signal as an input vector into the auto-associative memory; and

allowing the auto-associative memory to restore a matching failure signature for the input vector from the auto-associative memory matrix.

5. The method of claim 4, wherein restoring the matching failure signature facilitates reconstructing a high-resolution, high-sampling-rate failure signature from a low-resolution, low-sampling-rate input telemetry signal.

6. A computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for identifying a failure mechanism for a component, the method comprising:

constructing a library of failure signatures from a set of components, wherein each failure signature in the library characterizes a known failure mechanism associated with a component in the set of components, and the failure signature is stored at a high-resolution;

receiving a telemetry signal which is measured from a component under surveillance, wherein the telemetry signal is measured at a low-resolution;

determining if there is an anomaly in the telemetry signal, and if so;

performing pattern-matching operations between the telemetry signal and failure signatures in the library; and

if a match is found, identifying the failure mechanism for the component under surveillance based on the matching failure signature,

wherein the pattern-matching operations recall the high-resolution failure signature based on the low-resolution telemetry signal.

7. The computer-readable storage medium of claim 6, wherein constructing the library of failure signatures involves constructing a failure signature for each known failure mechanism of a component, which involves:

receiving one or more faulty specimens of the component, wherein the one or more faulty specimens are associated with a known failure mechanism;

collecting telemetry signals from the one or more faulty specimens, wherein the telemetry signals contain the failure signature of the known failure mechanism associated with the component, and wherein the telemetry signals have sufficiently high-resolution and high-sampling-rate for use in pattern-matching operations; and

storing the failure signature for the known failure mechanism of the component in the library of failure signatures.

8. The computer-readable storage medium of claim 6, wherein constructing the library of failure signatures involves storing the failure signatures in one or more auto-associative memory matrices of failure signatures, wherein each auto-associative memory matrix contains failure signatures for at least one corresponding type or level of failure patterns.

9. The computer-readable storage medium of claim 8, wherein performing the pattern-matching operations between the telemetry signal and the failure signatures in the library involves using an auto-associative memory, which involves:

feeding the anomalous telemetry signal as an input vector into the auto-associative memory; and

allowing the auto-associative memory to restore a matching failure signature for the input vector from the auto-associative memory matrix.

10. The computer-readable storage medium of claim 9, wherein restoring the matching failure signature facilitates reconstructing a high-resolution, high-sampling-rate failure signature from a low-resolution, low-sampling-rate input telemetry signal.

11. An apparatus that identifies a failure mechanism for a component, comprising:

a construction mechanism configured to construct a library of failure signatures from a set of components, wherein each failure signature in the library characterizes a known failure mechanism associated with a component in the set of components, and the failure signature is stored at a high-resolution;

a receiving mechanism configured to receive a telemetry signal which is measured from a component under surveillance, wherein the telemetry signal is measured at a low-resolution;

a determination mechanism configured to determine if there is an anomaly in the telemetry signal,

wherein the determination mechanism is further configured to;

perform pattern-matching operations between the telemetry signal and failure signatures in the library; and

if a match is found, to identify a failure mechanism for the component under surveillance based on the matching failure signature,

wherein the pattern-matching operations recall the high-resolution failure signature based on the low-resolution telemetry signal.

12. The apparatus of claim 11, wherein the construction mechanism is further configured to construct a failure signature for each known failure mechanism of a component by:

receiving one or more faulty specimens of the component, wherein the one or more faulty specimens are associated with a known failure mechanism;

collecting telemetry signals from the one or more faulty specimens, wherein the telemetry signals contain the failure signature of the known failure mechanism associated with the component, and wherein the telemetry signals have sufficiently high-resolution and high-sampling-rate for use in pattern-matching operations; and

storing the failure signature for the known failure mechanism of the component in the library of failure signatures.

13. The apparatus of claim 11, wherein, when constructing the library of failure signatures, the construction mechanism is configured to store the failure signatures in one or more auto-associative memory matrices of failure signatures, wherein each auto-associative memory matrix contains failure signatures for at least one corresponding type or level of failure patterns.

14. The apparatus of claim 13, wherein the determination mechanism is further configured to perform the pattern-matching operations between the telemetry signal and the failure signatures in the library by using an auto-associative memory, which involves:

feeding the anomalous telemetry signal as an input vector into the auto-associative memory; and

allowing the auto-associative memory to restore a matching failure signature for the input vector from the auto-associative memory matrix.

15. The apparatus of claim 14, wherein restoring the matching failure signature facilitates reconstructing a high-resolution, high-sampling-rate failure signature from a low-resolution, low-sampling-rate input telemetry signal.