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.

SIMULATION COMPONENT DATABASE SIMULATION COMPONENT DEVELOPERS S1S1 S2S2 SnSn... COMPONENT SELECTION TOOL IDEAL FEDERATION REQUIREMENTS THEORY BEST PRACTICES M&S Reuse in the Ideal World

6 What is Available?

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

8 Related Work Metrics and Models Component Representation Selection Techniques

9 Reuse Exemplars

10 Motivation

11 Simulation Composability Component Selection (CS) r1r1 r3r3 r4r4 r2r2 r5r5 r6r6 R x1x1 x3x3 x4x4 x8x8 x2x2 x6x6 x7x7 x5x5 r8r8 r7r7 X CS: Is there a subset of X of cardinality k or less that covers R? Example instance when k = 3. 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). REQUIREMENTS COMPONENTS

12 Composability Assumptions 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. Component selection in the context of simulation composability is inflexible.

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) 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… Exploiting simulation specific characteristics and adaptation changes component selection!

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 u xyz : the utility of the x th component satisfying requirement y while satisfying z-1 other requirements.

17 Adapting Components to Satisfy Requirements r1r1 r2r2 r3r3 r4r4 r5r5 r6r6 r7r7 x2x2 x2x2 x2x2 r1r1 r3r3 r4r4 r2r2 r5r5 r6r6 R x1x1 x3x3 x4x4 x8x8 x2x2 x6x6 x7x7 x5x5 r7r7 X CSCS-ASCR θ=3

18 Computing Utilities r1r1 r3r3 r4r4 r2r2 r5r5 r6r6 R x1x1 x3x3 x4x4 x8x8 x2x2 x6x6 x7x7 x5x5 r7r7 X CSCS-ASCR θ=3 r1r1 r2r2 r3r3 r4r4 r5r5 r6r6 r7r7 u 211 u 212 u 213 u 241 u 243 u 242 u 253 u 252 u 251 β reduces the number of computed utilities.

19 Building a Bin View r1r1 r2r2 r3r3 r4r4 r5r5 r6r6 r7r7 R x1x1 x2x2 x3x3 x4x4 X r1r1 r2r2 r3r3 r4r4 r5r5 r6r6 r7r7 u 111 u 221 u 112 u 222 u 223 u 113 u 321 u 322 u 323 u 331 u 332 u 333 u 432 u 431 u 433 u 441 u 442 u 443 u 251 u 252 u 253 u 461 u 462 u 463 u 261 u 262 u 263 u 171 u 172 u 173 u 371 u 372 u 373 REQUIREMENTS COMPONENTS r1r1 r2r2 r3r3 r4r4 r5r5 r6r6 r7r7 x1x1 x2x2 x3x3 x3x3 x4x4 x4x4 x2x2 x4x4 x2x2 x1x1 x3x3 θ=3

20 Building a Set View u 111 u 171 u 112 u 172 u 221 u 251 u 261 u 371 u 331 u 321 u 433 u 443 u 463 u 432 u 442 u 223 u 253 u 263 u 252 u 262 u 322 u 372 u 323 u 333 u 373 u 431 u 461 u 441 u 222 u 252 u 222 u 262 u 332 u 372 u 332 u 322 u 442 u 462 u 432 C1C1 C2C2 C3C3 C4C4 C r1r1 r2r2 r3r3 r4r4 r5r5 r6r6 r7r7 u 111 u 221 u 112 u 222 u 223 u 113 u 321 u 322 u 323 u 331 u 332 u 333 u 432 u 431 u 433 u 441 u 442 u 443 u 251 u 252 u 253 u 461 u 462 u 463 u 261 u 262 u 263 u 171 u 172 u 173 u 371 u 372 u 373 Scenario for x 2

21 CS-ASCR Definition r1r1 r2r2 r3r3 r4r4 r5r5 r6r6 r7r7 R u 111 u 171 u 112 u 172 u 221 u 251 u 261 u 371 u 331 u 321 u 433 u 443 u 463 u 432 u 442 u 223 u 253 u 263 u 252 u 262 u 322 u 372 u 323 u 333 u 373 u 431 u 461 u 441 u 222 u 252 u 222 u 262 u 332 u 372 u 332 u 322 u 442 u 462 u 432 C1C1 C2C2 C3C3 C4C4 C CS-ASCR (Informal): Is there an exact cover of R, constructed by choosing no more than 1 element from each C i, 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.

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 θ is unbounded, CS-ASCR is exponential β β =1, CS-ASCR is in P

23 Generalizing the Result r1r1 r2r2 r3r3 r4r4 r5r5 r6r6 r7r7 r8r8 θ=3 x1x1 x3x3 x6x6 x6x6 x4x4 x2x2 Modified definition of θ: utility can be dependent on selection of other components. x6x6 x7x7 x6x6 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 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. Example of Leveraging Time XX X MODEL GC1 MODEL GC2 MODEL AC1 LANCHESTER ATTRITION CALCULATED EVERY HOUR OF LOGICAL TIME STOCHASTIC ATTRITION AGGREGATED EVERY 10 MINUTES OF LOGICAL TIME STOCHASTIC ATTRITION AGGREGATED EVERY 5 MINUTES OF LOGICAL TIME LOW UTILITY HIGH UTILITY HIGH UTILITY

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

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

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 Brogan, Reynolds, Bartholet, Carnahan, Loitière. Semi-automated Simulation Transformation for DDDAS. Proceedings of the 5th International Conference on Computational Science, Atlanta, GA, May Bartholet, Reynolds, Brogan. The Computational Complexity of Component Selection in Simulation Reuse. Submitted to the ACM/IEEE 2005 Winter Simulation Conference, Orlando, FL, December 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.

Discussion