Measuring process model performance and enforcing process performance policy

• US 9,600,795 B2
• Filed: 04/09/2012
• Issued: 03/21/2017
• Est. Priority Date: 04/09/2012
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Demuth, Steve, Heching, Aliza R., Sun, Jimeng, Diament, Judah M.
• Primary Examiner(s): Chad, Aniss
• Assistant Examiner(s): Rogers, David M
• Application Number:
  US13/442,462
• Publication Number:
  US 20130268251A1
• Time in Patent Office: 1,807 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06N 5/00 Computing arrangements using knowledge-based models
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/067 Enterprise or organisation modelling

Abstract

Common sub-process patterns in a plurality of deployed process models may be discovered, and performance measures associated with the sub-process patterns may be computed based on runtime events of the deployed process models. Positive or negative performance patterns among sub-process patterns may be identified and used for creating new process models or improving existing process models.

Claims

1. A method for process model performance measurement and process performance policy enforcement, comprising:

receiving a deployed process model;

discovering a common sub-process pattern in the deployed process model that is in common with at least one previously discovered sub-process pattern in a previously deployed process model;

adding the deployed process model to a member list of the common sub-process pattern, if the deployed process model is not already in the member list, the member list of the common sub-process pattern comprising at least a plurality of process patterns that includes the common sub-process pattern, the common sub-process pattern associated with activities in the process patterns that reify the common sub-process pattern, the member list further comprising information that tells where a given pattern appears;

receiving a signal of one or more events associated with a runtime instance of the deployed process model, the signal of one or more events describing one or more of start, stop, failure, exception, and configured events occurring in an execution of said runtime instance of the deployed process model, the signal of one or more events stored in an event data store;

responsive to determining that the deployed process model or a sub-process within the deployed process model that caused the one or more events to be generated is in the member list of a common sub-process pattern, associating one or more performance dimensions impacted by the one or more events with the common sub-process pattern;

computing performance measurement associated with the discovered common sub-process pattern based on the received one or more events;

based on the performance measurement, identifying a composition of two or more services that individually produce positive performance but when composed together produce negative performance,

wherein generating of the one or more events are configurable to be turned on and off at least for individual process models or instances of process models conforming to a given pattern; and

displaying via a dashboard user interface, the common sub-process pattern and the performance measurement,

wherein a plurality of common sub-process patterns are discovered and saved with respective performance measurements for creating and updating of new process models, performance of the new process models further predicted based on the respective performance measurements of the plurality of common sub-process patterns,

wherein a sub-process pattern data store is rebuilt at set intervals.

2. The method of claim 1, further including discovering existence of negative performance pattern or positive performance pattern or combinations thereof in a newly deployed model based on the computed measurement.

3. The method of claim 1, wherein the method is performed for a plurality of deployed process models, wherein a plurality of sub-process patterns are discovered and the performance measurement is computed for each of the plurality of discovered sub-process patterns.

4. The method of claim 3, wherein a list of the plurality of sub-process patterns and associated performance measurement is presented for creating a new process model or improving an existing process model or combinations thereof.

5. The method of claim 3, further including predicting performance of a new process model based on the plurality of sub-process patterns and associated performance measurement.

6. The method of claim 3, further including enforcing one or more defined policies on the deployed process model based on the plurality of sub-process patterns and associated performance measurement.

7. The method of claim 3, wherein the events are configurable.

8. The method of claim 1, wherein the performance measurement includes a performance pattern describing behavior being exhibited by the sub-process patterns with respect to a performance dimension.

9. The method of claim 1, wherein the performance measurement includes probability distribution of an event recognized to impact a performance dimension of the deployed process model.

10. A system for process model performance measurement and process performance policy enforcement, comprising:

a processor;

a process analyzer operable to execute on the processor and further operable to discover a common sub-process pattern in a deployed process model that is in common with at least one previously discovered sub-process pattern in a previously deployed process model,

the process analyzer further operable to add the deployed process model to a member list of the common sub-process pattern, if the deployed process model is not already in the member list, the member list of the common sub-process pattern comprising at least a plurality of process patterns that includes the common sub-process pattern, the common sub-process pattern associated with activities in the process patterns that reify the common sub-process pattern, the member list further comprising information that tells where a given pattern appears,

the process analyzer module further operable to receive a signal of one or more events associated with a runtime instance of the deployed process model, the signal of one or more events describing one or more of start, stop, failure, exception, and configured events occurring in an execution of said runtime instance of the deployed process model, the signal of one or more events stored in an event data store,

responsive to determining that the deployed process model or a sub-process within the deployed process model that caused the one or more events to be generated is in the member list of the common sub-process pattern, the process analyzer is operable to associate one or more performance dimensions impacted by the one or more events with the common sub-process pattern, and compute performance measurement associated with the discovered common sub-process pattern based on the received one or more events,

wherein the process analyzer discovers a plurality of common sub-process patterns in a plurality of deployed process models and computes performance measurement associated with each of the plurality of common sub-process patterns, and

wherein the process analyzer identifies negative performance patterns and positive performance patterns among the plurality of common sub-process patterns based on the computed performance measurement,

wherein generating of the one or more events are configurable to be turned on and off at least for individual process models or instances of process models conforming to a given pattern

a dashboard user interface displaying the common sub-process pattern and the performance measurement,

wherein a plurality of common sub-process patterns are discovered and saved with respective performance measurements for creating and updating of new process models, performance of the new process models further predicted based on the respective performance measurements of the plurality of common sub-process patterns,

wherein a sub-process pattern data store is rebuilt at set intervals.

11. The system of claim 10, further including storage device for storing the plurality of deployed process models, the one or more events, and the computed performance measurement associated with each of the plurality of common sub-process patterns.

12. The system of claim 10, further including a user interface module operable to present performance alerts based on the computed performance measurement.

13. The system of claim 10, further including a process improvement module operable to allow a user to create a new process model or improve an existing process model or combinations thereof, based on one or more of the plurality of common sub-process patterns and the associated computed performance measurement and the identified negative performance patterns and positive performance patterns.

14. The system of claim 13, further including a performance policy module operable to enable a user to add policy specification associated with a process model for deploying.

15. The system of claim 10, further including a process server operable to execute the deployed process model and fire the one or more events associated with one or more performance dimensions of the deployed process model in runtime, the process server further operable to enforce one or more policies based on the computed performance measure.

16. A system for process model performance measurement and process performance policy enforcement, comprising:

a processor;

a modeler operable to create a process model and one or more policies associated with the process model;

a process server operable to deploy and execute the process model, the process server further operable to fire one or more events associated with runtime execution of the process model, the one or more events describing one or more of start, stop, failure, exception, and configured events occurring in an execution of said runtime instance of the process model to provide notification of occurrence of said one or more of start, stop, failure, exception, and configured events, the signal of one or more events stored in an event data store;

a process analyzer operable to discover a sub-process pattern in the process model that is common with previously discovered sub-process pattern,

the process analyzer further operable to add the process model to a member list of the common sub-process pattern, if the process model is not already in the member list, the member list of the common sub-process pattern comprising at least a plurality of process patterns that includes the common sub-process pattern, the common sub-process pattern associated with activities in the process patterns that reify the common sub-process pattern, the member list further comprising information that tells where a given pattern appears,

responsive to determining that the process model or a sub-process within the process model that caused the one or more events to be generated is in the member list of a common sub-process pattern, the process analyzer further operable to associate one or more performance dimensions impacted by the one or more events with the common sub-process pattern, the process analyzer further operable to compute performance measure associated with the discovered sub-process pattern based on the fired one or more events,

wherein the modeler further uses the discovered sub-process pattern and associated performance measure to create a new process model, or improve an existing process model, or combinations thereof,

wherein the process server further enforces the one or more policies based on the computed performance measure,

wherein generating of the one or more events are configurable to be turned on and off at least for individual process models or instances of process models conforming to a given pattern,

a dashboard user interface displaying the common sub-process pattern and the performance measurement,

wherein a plurality of common sub-process patterns are discovered and saved with respective performance measurements for creating and updating of new process models, performance of the new process models further predicted based on the respective performance measurements of the plurality of common sub-process patterns,

wherein a sub-process pattern data store is rebuilt at set intervals.

17. A non-transitory computer readable storage medium storing a program of instructions executable by a machine to perform a method of process model performance measurement and process performance policy enforcement, comprising:

receiving a deployed process model;

discovering a common sub-process pattern in the deployed process model that is in common with at least one previously discovered sub-process pattern in a previously deployed process model;

adding the deployed process model to a member list of the common sub-process pattern, if the deployed process model is not already in the member list, the member list of the common sub-process pattern comprising at least a plurality of process patterns that includes the common sub-process pattern, the common sub-process pattern associated with activities in the process patterns that reify the common sub-process pattern, the member list further comprising information that tells where a given pattern appears;

receiving a signal of one or more events associated with a runtime instance of the deployed process model, the signal of one or more events describing one or more of start, stop, failure, exception, and configured events occurring during an execution of said runtime instance of the deployed process model, the signal of one or more events stored in an event data store;

responsive to determining that the deployed process model or a sub-process within the deployed process model that caused the one or more events to be generated is in the member list of the common sub-process pattern, associating one or more performance dimensions impacted by the one or more events with the common sub-process pattern; and

computing performance measurement associated with the discovered common sub-process pattern based on the received one or more events,

wherein generating of the one or more events are configurable to be turned on and off at least for individual process models or instances of process models conforming to a given pattern,

displaying via a dashboard user interface, the common sub-process pattern and the performance measurement,

wherein a plurality of common sub-process patterns are discovered and saved with respective performance measurements for creating and updating of new process models, performance of the new process models further predicted based on the respective performance measurements of the plurality of common sub-process patterns,

wherein a sub-process pattern data store is rebuilt at set intervals.

18. The computer readable storage medium of claim 17, further including discovering existence of negative performance pattern or positive performance pattern or combinations thereof in a newly deployed model based on the computed measurement.

19. The computer readable storage medium of claim 17, wherein the method is performed for a plurality of deployed process models, wherein a plurality of sub-process patterns are discovered and the performance measurement is computed for each of the plurality of discovered sub-process patterns.

20. The computer readable storage medium of claim 19, wherein a list of the plurality of sub-process patterns and associated performance measurement is presented for creating a new process model or improving an existing process model or combinations thereof.

21. The computer readable storage medium of claim 19, further including predicting performance of a new process model based on the plurality of sub-process patterns and associated performance measurement.

22. The computer readable storage medium of claim 19, further including enforcing one or more defined policies on the deployed process model based on the plurality of sub-process patterns and associated performance measurement.

23. The computer readable storage medium of claim 19, wherein the events are configurable.

24. The computer readable storage medium of claim 17, wherein the performance measurement includes a performance pattern describing behavior being exhibited by the sub-process patterns with respect to a performance dimension.

25. The computer readable storage medium of claim 17, wherein the performance measurement includes probability distribution of an event recognized to impact a performance dimension of the deployed process model.