A Practical Process for Simulation Component Reuse

1. A Practical Process for Simulation Component Reuse Dissertation Proposal Presentation by Robert G. Bartholet 27 May 2005

2. Committee Members Worthy N. Martin, Chair Paul F. Reynolds, Jr., Advisor John C. Knight David C. Brogan Harsha K. Chelliah Ernest H. Page

3. Thesis Statement Component selection, applied to reusable simulation components, can be enhanced significantly by including considerations for the utility of component adaptation, simulation specific attributes, and other features that have not been considered in traditional approaches to component selection.

4. Thesis Statement Component selection, applied to reusable simulation components, can be enhanced significantly by including considerations for the utility of component adaptation, simulation specific attributes, and other features that have not been considered in traditional approaches to component selection.

5. M&S Reuse in the Ideal World REQUIREMENTS S1 SIMULATION COMPONENT DATABASE SIMULATION COMPONENT DEVELOPERS BEST PRACTICES COMPONENT SELECTION TOOL S2 THEORY . . . Sn IDEAL FEDERATION

6. What is Available?

7. Software Reuse TRANSFORMATION SCAVENGING S/W ARCHITECTURES COMPONENTS APPLICATION GENERATORS S/W SCHEMAS VERY HIGH LEVEL LANGUAGES Krueger, 1992

8. Related Work • Metrics and Models • Component Representation • Selection Techniques

9. Reuse Exemplars

10. Motivation

11. x8 x5 x7 x6 x2 x4 x3 x1 Simulation ComposabilityComponent Selection (CS) COMPONENTS REQUIREMENTS CS: Is there a subset of X of cardinality k or less that covers R? R X r4 Example instance when k = 3. r1 r2 CS is NP-complete. Proof: reduction from SAT (Page and Opper 1999) and MSC (Petty et al. 2003). CS can be approximated using GREEDY (Fox et al. 2004). r3 r5 r6 r7 r8

12. Composability Assumptions Component selection in the context of simulation composability is inflexible. • Components are immutable. • There exists a master set of components from which all possible sets of requirements can be satisfied. • Requirements are known a priori and do not change.

13. Thesis Statement Component selection, applied to reusable simulation components, can be enhanced significantly by including considerations for the utility of component adaptation, simulation specific attributes, and other features that have not been considered in traditional approaches to component selection.

14. Applied Simulation Component Reuse (ASCR) Exploiting simulation specific characteristics and adaptation changes component selection! • Leverage simulation specific characteristics in component reuse • Exploit adaptability of components to satisfy requirements. • What have we gained? • We no longer have to assume the existence of a master set of components. • We can more flexibly react to changing requirements. • We can pre-select components based on over-arching simulation specific requirements. • But…

15. ASCR Model BEHAVIOR DETERMINATION FUNCTION BEHAVIOR MAPPING FUNCTION UTILITY FUNCTION

16. Assumptions and Notation • θ: Upper bound on the number of requirements that can be satisfied by any one component. • β: scaling factor which captures the change in utility encountered when a component satisfies multiple requirements • uxyz: the utility of the xth component satisfying requirement y while satisfying z-1 other requirements.

17. r1 r2 r3 r4 r5 r6 r7 R X x7 x4 x3 x2 x1 x5 x8 x6 r4 r1 x2 x2 x2 r2 r3 r5 r6 r7 Adapting Components to Satisfy Requirements CS CS-ASCR θ=3

18. r1 r2 r3 r4 r5 r6 r7 u211 u241 u251 x5 x7 x6 x2 x4 x3 x1 x8 u252 u212 u242 u213 u243 u253 Computing Utilities CS CS-ASCR R X r4 r1 r2 r3 r5 r6 θ=3 βreduces the number of computed utilities. r7

19. X x2 x4 x1 x3 r1 r2 r3 r4 r5 r6 r7 r1 r2 r3 r4 r5 r6 r7 R u111 u221 u331 u441 u251 u461 u171 r7 r2 r4 r5 x1 x2 x3 x4 x2 x4 x1 u112 u222 u332 u442 u252 u462 u172 r1 r3 r6 x3 x4 x2 x3 u113 u223 u333 u443 u253 u463 u173 u321 u431 u261 u371 u262 u372 u322 u432 u323 u433 u263 u373 Building a Bin View θ=3 COMPONENTS REQUIREMENTS

20. r1 r2 r3 r4 r5 r6 r7 u111 u221 u331 u441 u251 u461 u171 u112 u222 u332 u442 u252 u462 u172 u113 u223 u333 u443 u253 u463 u173 C u321 u431 u261 u371 u222 u112 u222 u171 u111 u221 u251 u261 u252 u172 u262 u262 u372 u322 u432 C1 C2 u323 u433 u263 u373 u223 u433 u252 u462 u442 u331 u371 u321 u263 u463 u262 u432 u432 u443 u253 C3 C4 u323 u332 u332 u372 u442 u441 u431 u373 u461 u372 u322 u462 u322 u333 Building a Set View Scenario for x2

21. CS-ASCR Definition CS-ASCR (Informal): Is there an exact cover of R, constructed by choosing no more than 1 element from each Ci, with a total utility greater than k? CS-ASCR is NP-complete (Bartholet et al. submitted to ACM/IEEE WSC 2005). Proof: By reduction from X3C. Optimization problem is NP-hard. C u222 u112 u222 u171 u111 u221 u251 u261 r1 u252 u172 u262 R C1 r2 C2 r7 u223 u433 u252 u462 u442 r3 u331 u371 u321 u263 u463 u262 u432 u432 u443 u253 r4 r5 C3 C4 u323 u332 u332 u372 u442 u441 r6 u431 u373 u461 u372 u322 u462 u322 u333

22. Interesting Effects of θ and β • θ • θ= 1, CS-ASCR is in P • θ= 2, complexity of CS-ASCR is open • θ>= 3 but bounded, CS-ASCR is NP-complete • θis unbounded, CS-ASCR is exponential • β • β=1, CS-ASCR is in P

23. x1 x2 x4 x6 x6 x3 x6 x7 x6 θ=3 r1 r2 r3 r4 r5 r6 r7 r8 Generalizing the Result Modified definition of θ: utility can be dependent on selection of other components. CS-ASCR-X: ASCR component selection with the modified θ. Corollary: CS-ASCR-X when θ >= 3 is at least NP-complete (by reduction from X3C).

24. Leveraging Simulation Properties • Stochastic sampling • Time • Event generation

25. XX X MODEL GC2 MODEL AC1 Example of Leveraging Time LANCHESTER ATTRITION CALCULATED EVERY HOUR OF LOGICAL TIME LOW UTILITY Requirement 1: Model ground combat. Requirement 2: Model air combat. Requirement A: Provide up-to-date conflict adjudication data no less than once per minute. MODEL GC1 STOCHASTIC ATTRITION AGGREGATED EVERY 5 MINUTES OF LOGICAL TIME HIGH UTILITY STOCHASTIC ATTRITION AGGREGATED EVERY 10 MINUTES OF LOGICAL TIME HIGH UTILITY

26. MODEL GC2 MODEL AC1 Example of Leveraging Time TIME SCALE FACTORED INTO COMPONENT SELECTION PRE-SELECTION

27. Sim Specific Characteristics Adaptation Research Areas of Focus • Define the problem • Define the process • Characterize complexity of ASCR • Component selection

28. Measures of Success • Accurately formalized ASCR problem • Defined a practical ASCR process • Built practical methods for component selection • Developed useful utility functions • Analyzed complexity of critical algorithms in ASCR

29. Expected Contributions • Creation of a methodology that significantly improves state of simulation component reuse and provides practical methods for component selection • Improved understanding of complexity of component selection • Demonstration of how simulation specific properties can be leveraged in component selection

30. Publication Efforts Bartholet, Brogan, Reynolds, Carnahan. In Search of the Philosopher's Stone: Simulation Composability Versus Component Based Software Design. Proceedings of the Fall 2004 Simulation Interoperability Workshop, Orlando, FL, September 2004. Brogan, Reynolds, Bartholet, Carnahan, Loitière. Semi-automated Simulation Transformation for DDDAS. Proceedings of the 5th International Conference on Computational Science, Atlanta, GA, May 2005. Bartholet, Reynolds, Brogan. The Computational Complexity of Component Selection in Simulation Reuse. Submitted to the ACM/IEEE 2005 Winter Simulation Conference, Orlando, FL, December 2005. Bartholet, Kuang, Son. Intelligent Decentralized Update Management in Real-Time Embedded Applications. Working Draft Completed. Submission in August 2005 to conference TBD.

31. Conclusion Component selection, applied to reusable simulation components, can be enhanced significantly by including considerations for the utility of component adaptation, simulation specific attributes, and other features that have not been considered in traditional approaches to component selection.

32. Discussion