DEVS Today Recent Advances in Discrete Event Based

DEVS Today: Recent Advances in Discrete Event Based Information Technology • Bernard P. Zeigler • Professor, ECE • Arizona Center for Integrative Modeling and Simulation • University of Arizona • Tucson Keynote Talk www. acims. arizona. edu to MASCOTS, 2003: International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems

Outline • • • Framework for M&S Discrete Event Processing DEVS Formalism Implications for Current Practice Application Examples M&S as a Bridge Discipline 2

Framework for M&S: Entities and Relations Experimental Frame Device for executing model Simulator Real World Data: Input/output relation pairs Experimental frame specifies conditions under which the system is experimented with and observed Each entity is formalized as a Mathematical Dynamic System Each relation is represented by a homomorphism or other equivalence modeling relation simulation relation Model Structure for generating behavior claimed to represent real world 3

Primacy of Discrete Event Perception events as perceived e 2 e 1 t 1 e 3 t 2 t 3 e 4 t 4 1 hr time images as committed to memory e 1 e 2 e 3 t 2 -t 1 past 1 sec e 4 time line future 4

DEVS Background • DEVS = Discrete Event System Specification • Based on formal M&S framework • Derived from mathematical dynamical system theory • Supports hierarchical, modular composition • Object oriented implementation • Supports discrete and continuous paradigms • Exploits efficient parallel and distributed simulation techniques

DEVS Hierarchical Modular Composition Atomic: lowest level model, contains structural dynamics -- model level modularity + co upli Coupled: composed of ng one or more atomic and/or coupled models Hierarchical construction

DEVS Theoretical Properties • Closure Under Coupling • Universality for Discrete Event Systems • Representation of Continuous Systems – quantization integrator approximation – pulse representation of wave equations • Simulator Correctness, Efficiency 7

DEVS Expressability Coupled Models Atomic Models Ordinary Differential Equation Models Processing/ Queuing/ Coordinating Spiking Neuron Models Petri Net Models Processing Networks Physical Space Spiking Neuron Networks n-Dim Cell Space Cellular Automata Quantized Integrator Models Reactive Agent Models Partial Differential Equations Networks, Collaborations Discrete Time/ State. Chart Models Stochastic Models Fuzzy Logic Models can be components in a coupled model Multi Agent Systems Self Organized Criticality Models 8

M&S Framework Implications for Current Practice • Separate Models From Simulators • Separate Models From Experimental Frames • Use the DEVS Formalism for Developing Models, Experimental Frames, and Simulators • Experimental Frames Support Defense Certification Testing • Maintain Repositories of Reusable Models and Frames 9

Separate Models From Simulators • Models are goal oriented abstractions of reality. • Simulators are the computational engines that drive the models to obtain results. Currently… Simulation software tends to encapsulate models and simulators in tightly coupled packages. In the M&S-Framework-based approach. . • Models and Simulators are treated as distinct entities with their own software representations. • There are simulators for different kinds of models that can be selected according to the needs of the simulation, • For example, a simulator might be chosen for its efficiency on a single host, or for its ability to execute the model on multiple hosts (distributed simulation) 10

Separate Models From Experimental Frames • • Experimental Frames are specifications of the experimentation to be done on a model Frames represent the objectives of the experimenter, tester, or analyst Currently… Simulation software tends to encapsulate models, simulators and experimental frames into tightly coupled packages. In the M&S-Framework-based approach. . • Models and Experimental Frames are treated as distinct entities with their own software representations. • Since the experimental frames appropriate to a model are distinctly identified, it is easier for potential users of a model to uncover the objectives and assumptions that went into its creation. 11

Use the DEVS Formalism for Developing Models, Experimental Frames, and Simulators • • The DEVS formalism enables users to develop models separately from experimental frames. Models and frames can then be coupled together and given to an appropriate simulator to execute. Currently… Programming languages such as Fortran, C, C++ or Java are used to develop software packages of strongly coupled models, frames and simulators. In the M&S-Framework-based approach. . • The DEVS formalism Is employed for all simulation software development. • DEVS simulators are employed to perform single host, distributed and heterogeneous real-time execution as needed. • DEVS simulators exist that run over various middleware such as MPI, HLA, CORBA, P 2 P, and MOM. 12

Experimental Frames Support Defense Certification Testing • • Experimental Frames express procedures for testing interoperability of distributed military systems In development are Frames that assess combat effectiveness of such systems Currently… There is no comprehensive approach for developing and executing simulation technology for interoperability and combat effectiveness testing. In the M&S-Framework-based approach. . • A spiral methodology extends the already existing DEVS-based approach to creating and reusing models and frames. • Models and frames are developed in systematic fashion for various interoperability and combat effectiveness assessment applications 13

Maintain Repositories of Reusable Models and Frames • Models and Experimental Frames can be stored in organized repositories to support reuse under well specified conditions Currently… There are relatively few examples of storing previously developed simulation infrastructure commodities in such a way that they can be easily adapted to developing interoperability test requirements In the M&S-Framework-based approach. . • Repositories of models and frames are created and maintained. • Such repositories foster reuse of existing models and frames to serve as components for constructing new ones. • When new models or frames are developed they are deposited in the repositories with appropriate information to enable their reuse with high confidence of success. 14

DEVS Application to Interoperability Certification Tactical Data Communication Standard intended to facilitate communication in joint C 4 ISR • Document states requirements at behavioral level – “system shall …” • Voluminous, with many hyperlinked chapters and appendixes • Ambiguous, potentially incomplete, inconsistent, selfcontradictory • Interpretation is labor intensive, error prone • Will be required across numerous military services, nations, & manufacturers How to ensure certification test is complete, consistent and can be replicated? 15

DEVS Application to Interoperability Certification (cont’d) Implementations within various systems Development of Standard Government Formalization as a DEVS Contractors simulation-based tests of implementations in systems Automated distributed simulation environment / test procedures for V&V Government Other Contractors 16

Managed Modeling in Lockheed’s “System of Systems” M&S Environment • DEVS (Discrete Event Modeling Formalism) – Separates Model and Simulators – Defines Couple Models and Atomic Models – Modularized via Ports and Defined Events • SES (System Entity Structure) – Provides a well defined structure for model reuse – Maintains: kind-of, part-of, multiplicity relationships – Supports constraints on model compatibility • Architecture based on SES/DEVS supports component model reuse evolved during last decade 17

Component Reusability in Lockheed’s DEVS M&S Environment Project Model RAD IR Critical Mobile Target x Arsen al Ship Coast Guard Deep Water Space Operatio ns Vehicle Commo n Aero Vehicle Joint Compos ite Tracking Network x Global Positionin g System III x x x x Integrat ed System Center Space Based Laser Space Based Discrimi nation Missile Defense (Theater / National) x LAS Comm x CC x Earth x WC x x x x MIS x x x 18

DEVS framework for knowledge based control of steel production Sachem = large-scale real-time monitor/diagnose control system for blast furnace operation Usinor -- world’s largest producer of steel products, Sachem saves it millions of euros annually Problems for conventional control and AI: • Experts’ perception knowledge is implicit, concerns dynamic physical processes • Difficult to model the reasoning of a control process expert. • Lack of mathematical models for blast furnace dynamics Solution: • time-based perception and discrete event processing for dealing with complex dynamical systems 19

DEVS framework for knowledge based control of steel production (cont’d) quanti zation signal events signal pheno mena process pheno mena Large Scale: • Conceptual model contains 25, 000 objects for 33 goals, 27 tasks, etc. • Approximately 400, 000 lines of code. • 14 man-years: 6 knowledge engineers and 12 experts One advantage of DEVS is compactness: 50, 000 reduction in data volume Effective analysis and control of the behavior of blast furnaces at high resolution 20

Modeling and Simulation as a Bridging Discipline (1) M&S Systems Engineering • Overall Systems View • Model-based Design • Wymore’s Theory • DEVS Formalism • Computational basis • Validation • Model Continuity Software Engineering • SW/HW architecture • Spiral Methodology • OO Design: UML 21

Modeling and Simulation as a Bridging Discipline (2) M&S Natural Systems • Biological • Genetic • Ecological • Models enable new approaches • Simulation provides experimentation • Testing Technological Systems • AI • Soft Computing • Drug Research 22

Modeling and Simulation as a Bridging Discipline (3) DEVS Continuous Systems • Analog • Control theory • Linear/Non Linear • ODE/PDEs • Representation • Quantized Integration • Discrete Pulse Wave Approx Discrete Systems • Digital • Computer Science • Algorithms 23

Modeling and Simulation as a Bridging Discipline (4) DEVS Computational Science • Numerical Methods • Supercomputing • MPI • PDEs • Discrete Event Universality • DEVS Simulation Protocol • Representation of Cont Sys PADS • Logical Process • Time Warp • Large Numbers • Network, Agent Apps 24

More Information • Zeigler, B. P. , Praehofer, H. , and Kim, T. G. , Theory of Modeling and Simulation, 2 nd Edition. Academic Press, 2000. ACIMS : www. acims. arizona. edu DEVSJAVA downloadable software • • Society for Modeling and Simulation, Intl. : www. scs. org – – Simulation Journal, new: Journal of Defense Modeling and Simulation 25