Estimating the residual life of a software system under a software-based failure mechanism

• US 7,543,192 B2
• Filed: 06/20/2006
• Issued: 06/02/2009
• Est. Priority Date: 06/20/2006
• Status: Active Grant

• Current Assignee: Oracle America, Inc. (Oracle Corporation)
• Original Assignee: Sun Microsystems Incorporated (Oracle Corporation)
• Inventors: Gross, Kenny C., Vaidyanathan, Kalyanaraman
• Primary Examiner(s): DUNCAN, MARC M
• Application Number:
  US11/471,205
• Publication Number:
  US 20080010556A1
• Time in Patent Office: 1,078 Days
• Field of Search: 714/38, 714/47
• US Class Current: 714/47.2
• CPC Class Codes: G06F 11/008 Reliability or availability analysis
• CPC Class Codes: G06F 11/3447 Performance evaluation by modeling
• CPC Class Codes: G06F 11/3452 Performance evaluation by statistical analysis

Abstract

One embodiment of the present invention provides a system that estimates residual life of a software system under a software-based failure mechanism. During operation, the system first constructs a prognostic database for the software-based failure mechanism based on a plurality of software systems of the same type as the software system, wherein the prognostic database includes a set of prognostic readings associated with the software-based failure mechanism from the plurality of software systems. Note that a given prognostic reading in the prognostic database comprises: (1) a symptom index, which is a function of one or more variables associated with the software-based failure mechanism; and (2) a residual life, which is the remaining time to a failure under the software-based failure mechanism. Next, the system obtains a symptom index value from the software system which is being monitored. The system then estimates a residual life for the software system under the software-based failure mechanism by comparing the symptom index value with the prognostic readings in the prognostic database.

Claims

1. A method for estimating residual life of a software system under a software-based failure mechanism, comprising:

constructing a prognostic database for the software-based failure mechanism based on a plurality of software systems of the same type as the software system,

wherein the prognostic database includes a times-series of prognostic readings associated with the software-based failure mechanism from the plurality of software systems; and

wherein a given prognostic reading at a given timestamp in the time-series of prognostic readings comprises;

a symptom index computed at the given timestamp as a function of one or more variables associated with the software-based failure mechanism, wherein the one or more variables are recorded at the given timestamp; and

a residual life, which is the remaining time computed from the given timestamp to a failure time under the software-based failure mechanism;

obtaining a symptom index value from the software system which is being monitored; and

estimating a residual life for the software system under the software-based failure mechanism by comparing the symptom index value with the prognostic readings in the prognostic database.

2. The method of claim 1, wherein for a given system in the plurality of software systems, constructing the prognostic database for the software-based failure mechanism involves:

monitoring the system during operation until a system failure occurs, wherein while monitoring, recording system values associated with the software-based failure mechanism at various recording times t_i;

verifying that the system failure is caused by the software-based failure mechanism, and if so,

recording the time of failure t_f,

computing a set of symptom indices s_iand associated residual lives r_i based on the recorded system values, and

storing the time-series of prognostic readings (s_i, r_i) in the prognostic database for the software-based failure mechanism.

3. The method of claim 2, wherein the residual life r_i at a given recording time t_i is computed as r_i=t_f−

t_i.

4. The method of claim 1, wherein the method is performed for a plurality of software-based failure mechanisms simultaneously.

5. The method of claim 1, wherein estimating the residual life for the software system involves computing at least one of:

a mean of the residual life;

a variance of the residual life; and

confidence bounds for the residual life.

6. The method of claim 5, wherein computing the mean of the residual life involves computing a conditional probability density function f(r|s*) for a given symptom index value s*, wherein r is the residual life.

7. The method of claim 5, wherein the confidence bounds of the residual life are tighter when the number of software systems in the prognostic database is larger.

8. The method of claim 1, wherein the software-based failure mechanism can include software aging, which can involve,

a memory leak;

other types of resource exhaustion problems;

accumulation of numerical errors; and

latching of a share pool memory.

9. The method of claim 8, wherein the symptom index for The memory-leak failure mechanism is computed from a memory leak index (MLI) and a currently-available memory.

10. The method of claim 1, wherein the method further comprises taking preventive action based on the estimated residual life for the software system, which can include performing a software rejuvenation operation.

11. The method of claim 1, wherein the method is performed using a Continuous System Telemetry Harness (CSTH).

12. A computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for estimating residual life of a software system under a software-based failure mechanism, the method comprising:

constructing a prognostic database for the software-based failure mechanism based on a plurality of software systems of the same type as the software system,

wherein the prognostic database includes a time-series of prognostic readings associated with the software-based failure mechanism from the plurality of software systems; and

wherein a given prognostic reading at a given timestamp in the time-series of prognostic readings comprises;

a symptom index computed at the given timestamp as a function of one or more variables associated with the software-based failure mechanism wherein the one or more variables are recorded at the given timestamp; and

a residual life, which is the remaining time computed from the given timestamp to a failure time under the software-based failure mechanism;

obtaining a symptom index value from the software system which is being monitored; and

estimating a residual life for the software system under the software-based failure mechanism by comparing the symptom index value with the prognostic readings in the prognostic database.

13. The computer-readable storage medium of claim 12, wherein for a given system in the plurality of software systems, constructing the prognostic database for the software-based failure mechanism involves:

monitoring the system during operation until a system failure occurs, wherein while monitoring, recording system values associated with the software-based failure mechanism at various recording times t_i;

verifying that the system failure is caused by the software-based failure mechanism, and if so,

recording the time of failure t_f,

computing a set of symptom indices s_iand associated residual lives r_i based on the recorded system values, and

storing the time-series of prognostic readings (s_i, r_i) in the prognostic database for the software-based failure mechanism.

14. The computer-readable storage medium of claim 12, wherein the method is performed for a plurality of software-based failure mechanisms simultaneously.

15. The computer-readable storage medium of claim 12, wherein estimating the residual life for the software system involves computing at least one of:

a mean of the residual life;

a variance of the residual life; and

confidence bounds for the residual life.

16. The computer-readable storage medium of claim 15, wherein computing the mean of the residual life involves computing a conditional probability density function f(r|s*) for a given symptom index value s*, wherein r is the residual life.

17. The computer-readable storage medium of claim 12, wherein the software-based failure mechanism can include software aging, which can involve,

a memory leak;

other types of resource exhaustion problems; and

accumulation of numerical errors; and

latching of a share pool memory.

18. An apparatus that estimates residual life of a software system under a software-based failure mechanism, comprising:

a construction mechanism configured to construct a prognostic database for the software-based failure mechanism based on a plurality of software systems of the same type as the software system;

wherein the prognostic database includes a time-series of prognostic readings associated with the software-based failure mechanism from the plurality of software systems; and

wherein a given prognostic reading at a given timestamp in the time-series of prognostic readings comprises;

a symptom index, computed at the given timestamp as a function of one or more variables associated with the software-based failure mechanism wherein the one or more variables are recorded at the given timestamp; and

a residual life, which is the remaining time computed from the given timestamp to a failure time under the software-based failure mechanism;

an obtaining mechanism configured to obtain a symptom index value from the software system which is being monitored; and

an computing mechanism configured to estimate a residual life for the software system under the software-based failure mechanism by comparing the symptom index value with the prognostic readings in the prognostic database.

19. The apparatus of claim 18, wherein for a given system in the plurality of software systems, the construction mechanism is configured to construct the prognostic database for the software-based failure mechanism by:

monitoring the system during operation until a system failure occurs, wherein while monitoring, recording system values associated with the software-based failure mechanism at various recording times t_i;

verifying that the system failure is caused by the software-based failure mechanism, and if so,

recording the time of failure t_f,

computing a set of symptom indices s_iand associated residual lives r_i based on the recorded system values, and

storing the time-series of prognostic readings (s_i, r_i) in the prognostic database for the software-based failure mechanism.

20. The apparatus of claim 18, wherein the estimation mechanism is configured to estimate the residual life for the software system by computing at least one of:

a mean of the residual life;

a variance of the residual life; and

confidence bounds for the residual life.