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The Need for a Theory of Modeling and Simulation to Support the MS COI Mission

Premise: Coordination is needed, theory can help. The M

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The Need for a Theory of Modeling and Simulation to Support the MS COI Mission

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    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 Simulation and Joint Interoperability Test Command Fort Huachuca, AZ 85613-7051 zeigler@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

    5. Start with Largest Perspective: M&S Body of Knowledge 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

    6. M&S Framework and System Theory Support*

    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*

    10. M&S Entities and Relations (cont'd)

    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 SIBYL MEASURE is Lockheed Martin Missiles and Space’s HEL System mission effectiveness analysis tool. It provides a high fidelity Monte Carlo discrete event modeling and simulation environment that is intended to support all subsequent phases of the SBL/HEL development program through to deployment. This presentation reviews: the requirements for this development; the current status of the tool; the benefits of SIBYL over similar tools; a demonstration of some of its many features and finally a presentation of some validation results derived from comparing SIBYL’s performance with the performance of the Shafer developed ISAAC. The image on this slide is a screen capture of SIBYL depicting some of its many input and output windows that allow an analysis to easily set up a scenario, execute it and analyze the results. SIBYL MEASURE is Lockheed Martin Missiles and Space’s HEL System mission effectiveness analysis tool. It provides a high fidelity Monte Carlo discrete event modeling and simulation environment that is intended to support all subsequent phases of the SBL/HEL development program through to deployment. This presentation reviews: the requirements for this development; the current status of the tool; the benefits of SIBYL over similar tools; a demonstration of some of its many features and finally a presentation of some validation results derived from comparing SIBYL’s performance with the performance of the Shafer developed ISAAC. The image on this slide is a screen capture of SIBYL depicting some of its many input and output windows that allow an analysis to easily set up a scenario, execute it and analyze the results.

    14. The Distributed Joint MEASURETM Architecture In the distributed Joint MEASURE architecture each model is responsible for the maintenance of its own endomorph. The endomorphs, represented in this diagram as the transparent boxes, only reflect the Hull attributes of the parent. The Hull models includes the signature(s) of the Platform and thus enables the sensors of the platforms co-located with the endomorph to do sensor processing directly on the endomorph. The parent model is responsible for maintaining its’ endomorph with a ‘proper’ orientation and signature. The rate of these updates can be adjusted through the use of quantizers to limit the number of messages sent to maintain these attributes while maintaining the desired level of fidelity.In the distributed Joint MEASURE architecture each model is responsible for the maintenance of its own endomorph. The endomorphs, represented in this diagram as the transparent boxes, only reflect the Hull attributes of the parent. The Hull models includes the signature(s) of the Platform and thus enables the sensors of the platforms co-located with the endomorph to do sensor processing directly on the endomorph. The parent model is responsible for maintaining its’ endomorph with a ‘proper’ orientation and signature. The rate of these updates can be adjusted through the use of quantizers to limit the number of messages sent to maintain these attributes while maintaining the desired level of fidelity.

    15. Joint MEASURE – Model Repository Reuse

    16. Prescriptive Requirements for Simulation Model Repositories *

    17. Middleware-Independent Simulation Architecture for SOA Infrastructure

    18. DEVS Model Continuity as Basis for Life Cycle Development of Web Services

    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

    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 Simulation as 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. Zeigler zeigler@ece.arizona.edu ACIMS www.acims.arizona.edu

    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

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