The Need for a Theory of Modeling and Simulation to Support the M&S COI Mission

1. The Need for a Theory of Modeling and Simulation to Support the M&S COI Mission Bernard P. Zeigler, Ph.D.,Arizona Center for Integrative Modeling and SimulationandJoint Interoperability Test CommandFort Huachuca, AZ 85613-7051zeigler@ece.arizona.edu

2. Premise: Coordination is needed, theory can help The M&S COI has partitioned its interests into metadata, mediation, and services, recognizing, at the same time, that applications will not break down neatly into these categories. A framework is needed to • provide an ontology for M&S that recognizes the essential dynamic character of simulation models, • properly distinguish the elements in the M&S enterprise and the relationships that connect such elements in meaningful ways related to the objectives of simulation exercises, • provide a rigorous mathematical theory that supports manipulations of the elements in their real-world incarnations in order to achieve the desired relationships • enable us to • derive meaningful metadata schemes to characterize the identified elements • help delineate services amenable to web-based manipulation • provide well-defined semantics and pragmatics for cross-COI mediation.

3. Potential problems in the absence of an M&S COI Framework • Lack of accepted terminology: multiple definitions for basic terms (model, simulation) make coherent vocabulary of metadata registry problematic • Difficulties in composability of models and simulations come to the fore: WSDL characterizations of M&S service components are likely to break down when new orchestrations are attempted due to incompatibilities that can’t be represented at the interface level • Central feature of M&S – dynamics (time behavior) – is the key impediment to easy interoperability of simulations as services • others…

4. Where Theory of M&S Fits M&S Body of Knowledge MetaData M&S Theory and Framework Mediation DoD Architectural Framework Services

5. Start with Largest Perspective: M&S Body of Knowledge Tuncer I. Ören, Toward the Body of Knowledge of Modeling and Simulation Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC) 2005 • A Body of Knowledge (BOK) for modeling and simulation (M&S) provides a comprehensive and integrative view of the discipline • A systematic top-down decomposition of M&SBOK • Definition: simulation is goal-directed experimentation using dynamic models • M&S knowledge for application • – science, engineering, business… • • Training, Education and learning • Development • • Decision support • • Understanding and Analysis • • Entertainment M&SBOK provides “checklist” to enumerate M&S meta-data, mediation and services Application types signal services that are likely to be of interest to external users: other communities of interest (COI) with which M&S COI must interact • Core elements of M&S discipline • • Input data • • Models and modeling • • Model processing • • Experimentation • • Model behavior • • Behavior generation • • Behavior processing • • M&S infrastructure • • Computerization • • User/system interfaces • • Reliability and ethics Theory of Modeling and Simulation provides an integrating framework for these elements Concepts/terminology of supporting disciplines are likely to be incorporated into M&S COI metadata characterizations or be in need of mediation • Core elements of supporting disciplines • mathematics, computer science, systems science, systems engineering

6. M&S Framework and System Theory Support* Mathematical Systems Theory Framework for M&S Ontology delimiting entities and relationships in M&S rigorous supports manipulating elements in their real-world incarnations to achieve the desired relationships “Theory of Modeling and Simulation” (Zeigler, Praehofer and Kim, Academic Press, 2000)

7. Mathematical Theory of Systems • levels of system specification –are the levels of structure and behavior at which we can describe dynamic systems • systems specification formalisms – these represent the types of models, such continuous and discrete, that modelers can use to build dynamic system models – a formalism specifies a subclass of systems

8. Levels of System Specification and Associated Morphisms:Formal Basis for Multiple Levels of Abstraction

9. M&S Entities and Relations* Device for executing model Real World Simulator Data: Input/output relation pairs modeling relation simulation relation Each entity is represented as a dynamic system Each relation is represented by a homomorphism or other equivalence Model structure for generating behavior claimed to represent real world “Theory of Modeling and Simulation” (Zeigler, Praehofer and Kim, Academic Press, 2000)

10. Experimental Frame M&S Entities and Relations (cont'd) Morphisms at Behavior Level Real World Simulator modeling relation simulation relation • Experimental frame specifies • conditions under which the system • is experimented with, observed and • controlled • captures modeling objectives • needed for validity, simplification • justifications Model Morphisms at Structure Level Morphisms at Structure Level Abstract Model

11. Examples of the M&S theory that might be the basis for scaling up to the SOA • Lockheed’s Model Base Repository • Middleware Independent Distributed Simulation Protocol • Semi-automated generation of standards conformance testing

12. Lockheed’s Managed Modeling Approach to DEVS-Based Modeling and Simulation • DEVS – Discrete Event System Specification • Formal discrete event specification. • Clearly separates Simulation Engine from Models. • Object passing In-ports and Out-ports • Interchangeable Coupled & Atomic Models. • Strong support for reuse and composability. • Multiple implementation are available. • GUI development environments are available • Active developer community distributed worldwide.

13. Joint MEASURE Advanced Simulation Development Tool for Systems of Systems • Advanced Analyst-oriented GUI. • Models SoS Engagement Domain. • Platforms (how they move and react), • Sensor (& networks), • Communications (& networks), • Weapons (& systems), • C3 (at multiple levels). • High Performance Simulation Engine • Managed Software • Full Complement of Integrated Tools Joint MEASURE - Mission Effectiveness Analysis Simulator for Utility, Analysis and Evaluation

14. GIS dB GIS dB GIS GIS Sensors C3 C3 Sensors Propagator Propagator Weapons Hull Hull Weapons Platform Platform Logger Logger Sensors C3 C3 Sensors Weapons Hull Hull Weapons Platform Platform Hull Hull Endomorphs Endomorphs HLA/RTI The Distributed Joint MEASURETM Architecture

15. Joint MEASURE – Model Repository Reuse “… the Lockheed-Martin activities may well represent the state of the art in complex model composability …”, Davis, Paul and Anderson, Robert in Improving the Composability of Department of Defense Models and Simulations, RAND, 2004 Use of infrared model in JCTS project Note presence of discrete and continuous dynamic model types

16. Prescriptive Requirements for Simulation Model Repositories * * adapted from: ZEIGLER, B. P. 1997. A framework for modeling & simulation. Applied Modeling & Simulation: An Integrated Approach to Development & Operation, McGraw-Hill, New York.

17. Middleware-Independent Simulation Architecture for SOA Infrastructure Conceptual Systems Architecture Pragmatic Tolk’s Levels DEVS Model Semantic DEVS Model DEVS Simulator Syntactic DEVS Simulator Middleware Technical Interoperability Middleware Network DEVS component models are correctly integrated into a higher level coupled model by the DEVS simulator protocol • Parallel and sequential simulation of the same DEVS model will always produce the same results • This is a strong proof of correctness that no logical-processor-based proof has been able to rival.

18. DEVS Model DEVS Model DEVS Model DEVS Simulator DEVS Distributed Executor DEVS Distributed Simulator DEVS Model Continuity as Basis for Life Cycle Development of Web Services Pre-test of Conceptual Model in non-distributed environment Packaging:XML The model can remain basically invariant as it is transitioned through the phases from conception to realization SOA Messaging:SOAP Service Discovery: UDDI Communication: HTTP Sevice Description: WSDL Refine and Transfer model to distributed environment Packaging:XML Messaging:SOAP Communication: HTTP • Change engine • Provide meta-data for • Web presence as service

19. Model-Driven Development (MDD)* for SOA(Service Oriented Architecture) • Organizations must integrate MDD into the development process for distributed, heterogeneous, loosely coupled service environment • Models • represent the problem domain • raise the level of abstraction • serve as blueprints • drive the development process • Facilitate creating and managing complicated systems • Use/Re-use model-based code generators • Accelerate/Automate the software life cycle • Transition study of systems capable of expansion and evolution • Reduce manual work required in development and testing • Deliver higher-quality service components *Anne T. Manes, Burton Group Pub.

20. Summary: Dynamic Systems and Semantics • Dynamics are a major component in the semantics of simulation models • Dynamic properties must be represented in schemes for semantic layers of model interoperability • Model formalisms key in on different features of dynamics (e.g., continuous, discrete event) • Multiple formalisms need to be managed in any M&S repository supporting reusability and composability

21. Summary: DEVS-based SOA Development • Simulation Model framework supported by: • Systems Theory-based • Formal, allows proofs of correctness and other properties • Dynamics – integrates model formalisms in one theory and framework • Modularly separates • Model • Simulator • Experimental Frame • Model Continuity supports development life cycle

22. Theory of Modeling and Simulationas Framework for M&S COI • Formally characterizes the elements and relationships to support discovery, interoperability and composability • Ontology identifies the elements as dynamic systems within mathematical systems theory • well-defined levels of behavior and structure specifications • relationships are made operational by appropriate morphisms • rigorous mathematical theory supports orchestration of components • Provides the basis for metadata schemes that are unambiguous and compatible with the vocabulary and concepts of the theory • expose the proper elements for efficient discovery • reuse of M&S data and services. Results: • solid foundation for a well-defined semantics and pragmatics of the M&S enterprise • well-defined infrastructure for SOA development

23. Bernard P. Zeiglerzeigler@ece.arizona.eduACIMSwww.acims.arizona.edu Contact: More information:

24. Other Presentations • Standards Conformance Testing as an M&S Web Service • The Special Role of M&S in Cross-COI Mediation • M&S Services at the Crossroads of Service Oriented Architecture and the DoD Architectural Framework