Theory of Modeling and Simulation

Theory of Modeling and Simulation

Discrete Event & Iterative System Computational Foundations

3rd Edition - August 14, 2018

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  • Authors: Bernard P. Zeigler, Alexandre Muzy, Ernesto Kofman
  • Paperback ISBN: 9780128133705
  • eBook ISBN: 9780128134078

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Description

Theory of Modeling and Simulation: Discrete Event & Iterative System Computational Foundations, Third Edition, continues the legacy of this authoritative and complete theoretical work. It is ideal for graduate and PhD students and working engineers interested in posing and solving problems using the tools of logico-mathematical modeling and computer simulation. Continuing its emphasis on the integration of discrete event and continuous modeling approaches, the work focuses light on DEVS and its potential to support the co-existence and interoperation of multiple formalisms in model components. New sections in this updated edition include discussions on important new extensions to theory, including chapter-length coverage of iterative system specification and DEVS and their fundamental importance, closure under coupling for iteratively specified systems, existence, uniqueness, non-deterministic conditions, and temporal progressiveness (legitimacy).

Key Features

  • Presents a 40% revised and expanded new edition of this classic book with many important post-2000 extensions to core theory
  • Provides a streamlined introduction to Discrete Event System Specification (DEVS) formalism for modeling and simulation
  • Packages all the "need-to-know" information on DEVS formalism in one place
  • Expanded to include an online ancillary package, including numerous examples of theory and implementation in DEVS-based software, student solutions and instructors manual

Readership

Undergraduate students and graduate students, especially PhD students, researchers, and all workers in computational-based fields benefiting from modeling and simulation, both traditional and non-traditional

Table of Contents

  • Cover image
  • Title page
  • Table of Contents
  • Copyright
  • Contributions
  • Preface to the Third Edition
  • References
  • Preface to the Second Edition
  • Part 1: Basics: Modeling Formalisms and Simulation Algorithms
  • Chapter 1: Introduction to Systems Modeling Concepts
  • Abstract
  • 1.1. Systems Specification Formalisms
  • 1.2. Levels of System Knowledge
  • 1.3. Introduction to the Hierarchy of Systems Specifications
  • 1.4. The Specification Levels Informally Presented
  • 1.5. System Specification Morphisms: Basic Concepts
  • 1.6. Evolution of DEVS
  • 1.7. Summary
  • 1.8. Sources
  • Definitions, Acronyms, Abbreviations
  • References
  • Chapter 2: Framework for Modeling and Simulation
  • Abstract
  • 2.1. The Entities of the Framework
  • 2.2. Primary Relations Among Entities
  • 2.3. Other Important Relationships
  • 2.4. Time
  • 2.5. Historical Trace of V&V Streams
  • 2.6. Summary
  • 2.7. Sources
  • References
  • Chapter 3: Modeling Formalisms and Their Simulators
  • Abstract
  • Introduction
  • 3.1. Discrete Time Models and Their Simulators
  • 3.2. Differential Equation Models and Their Simulators
  • 3.3. Discrete Event Models and Their Simulators
  • 3.4. Summary
  • 3.5. Sources
  • References
  • Chapter 4: Introduction to Discrete Event System Specification (DEVS)
  • Abstract
  • 4.1. Introduction
  • 4.2. Classic DEVS System Specification
  • 4.3. Parallel DEVS System Specification
  • 4.4. Hierarchical Models
  • 4.5. Object-Oriented Implementations of DEVS: an Introduction
  • 4.6. DEVS and Hierarchy of System Specifications: Turing Machine Example
  • 4.7. Are DEVS State Sets Essentially Discrete?
  • 4.8. Summary
  • 4.9. Sources
  • References
  • Chapter 5: Hierarchy of System Specifications
  • Abstract
  • 5.1. Time Base
  • 5.2. Segments and Trajectories
  • 5.3. I/O Observation Frame
  • 5.4. I/O Relation Observation
  • 5.5. I/O Function Observation
  • 5.6. I/O System
  • 5.7. Multi-Component System Specification
  • 5.8. Network of System Specifications (Coupled Systems)
  • 5.9. Summary
  • Chapter 6: Basic Formalisms: DEVS, DESS, DTSS
  • Abstract
  • 6.1. Basic System Specification Formalisms
  • 6.2. Discrete Event System Specification (DEVS)
  • 6.3. Parallel DEVS
  • 6.4. Discrete Time System Specification (DTSS)
  • 6.5. Differential Equation System Specification (DESS)
  • 6.6. Example of DESS
  • 6.7. Summary
  • References
  • Chapter 7: Basic Formalisms: Coupled Multi-Component Systems
  • Abstract
  • 7.1. Discrete Event Specified Network Formalism
  • 7.2. Multi-Component Discrete Event System Formalism
  • 7.3. Discrete Time Specified Network Formalism
  • 7.4. Multi-Component Discrete Time System Formalism
  • 7.5. Differential Equation Specified Network Formalism
  • 7.6. Multi-Component Differential Equations Specified System Formalism
  • 7.7. Multi-Component Parallel Discrete Event System Formalism
  • 7.8. Summary
  • 7.9. Sources
  • Appendix 7.A.
  • References
  • Chapter 8: Simulators for Basic Formalisms
  • Abstract
  • 8.1. Simulators for DEVS
  • 8.2. DEVS Bus
  • 8.3. Simulators for DTSS
  • 8.4. Simulators for DESS
  • 8.5. Summary
  • 8.6. Sources
  • References
  • Chapter 9: Multi-Formalism Modeling and Simulation
  • Abstract
  • 9.1. Brief Introduction to Specialized Formalisms
  • 9.2. Multi-Formalism Modeling
  • 9.3. DEV&DESS: Combined Discrete Event and Differential Equation Specified Systems
  • 9.4. Multi-Modeling With DEV&DESS
  • 9.5. Coupled DEV&DESS: Network of Multi-Formalism Models
  • 9.6. Simulator for DEVS&DESS
  • 9.7. Update on DEV&DESS and Cyber-Physical Systems
  • 9.8. Sources
  • Appendix 9.A. The System Specified by a DEV&DESS
  • Appendix 9.B. The System Specified by a Multi-Formalism System – Closure Under Coupling of Networks of DEV&DESS
  • References
  • Part 2: Iterative System Specification
  • Chapter 10: Introduction to Iterative System Specification
  • Abstract
  • 10.1. Overview of Iterative System Specification
  • 10.2. Abstraction, Formalization, and Implementation
  • 10.3. Deriving Iterative System Specification
  • 10.4. Input Generators
  • 10.5. Progressivity and Well-Definition of Systems
  • 10.6. Active/Passive Compositions
  • 10.7. How Can Feedback Coupled Components Define a System?
  • 10.8. Example: Emergence of Human Conversational Language Interaction
  • 10.9. Simulation of Iterative System Specification by DEVS
  • 10.10. Closure Under Coupling: Concept, Proofs, and Importance
  • 10.11. Activity Formalization and Measurement
  • 10.12. Summary
  • Appendix 10.A. Activity Definitions
  • References
  • Chapter 11: Basic Iterative System Specification (IterSpec)
  • Abstract
  • 11.1. Basic Iterative System Specification: IterSpec Definition
  • 11.2. Composition Process
  • 11.3. Specific Maximal Length Segmentations
  • 11.4. Composition of Segments
  • 11.5. Dilatable Generator Classes
  • 11.6. Summary
  • Appendix 11.A.
  • References
  • Chapter 12: Iterative Specification Subformalisms
  • Abstract
  • 12.1. Class Mapping of Iterative System Specifications
  • 12.2. Basic Iterative Specification (IterSpec)
  • 12.3. Scheduled Iterative System Specification
  • 12.4. Sample-Based Iterative System Specification
  • 12.5. Hybrid Iterative System Specification
  • 12.6. Coupled Iterative Specifications
  • 12.7. Active-Passive Systems
  • 12.8. DEVS Simulation of Iterative Specifications
  • 12.9. Summary
  • Appendix 12.A. Proof That DEVS Is a Scheduled Iterative System Specification
  • Appendix 12.B. Coupled Iterative Specification at the I/O System Level
  • Appendix 12.C. Composition Property for Sample-Based Systems
  • Appendix 12.D. Closure Under Coupling of Sample-Based Iterative Specification
  • Appendix 12.E. Abstract Simulator for Sample-Based Iterative Specification
  • Appendix 12.F. Example of Closure Under Coupling: Memoryless Systems
  • Appendix 12.G. Proof That a DEVS Atomic Model Can Simulate an Iterative Specification
  • References
  • Chapter 13: Finite and Timed Iterative Specifications and Simulations
  • Abstract
  • 13.1. Time Management
  • 13.2. Basic Finite Iterative Specification (FinIterSpec)
  • 13.3. Finite PDEVS
  • 13.4. Basic Timed Iterative Specification (TimedIterSpec)
  • 13.5. Basic Finite Timed Iterative Specification (FiniTimedIterSpec)
  • 13.6. Event Based Control and Finite Timed PDEVS
  • 13.7. Summary
  • References
  • Part 3: System Morphisms: Abstraction, Representation, Approximation
  • Chapter 14: Parallel and Distributed Discrete Event Simulation
  • Abstract
  • 14.1. The Value of Information
  • 14.2. The Value of Parallel Model Execution
  • 14.3. Speedup, Scaling, and Parallel Execution
  • 14.4. Parallel DEVS Simulator
  • 14.5. Optimistic and Conservative Simulation
  • 14.6. Summary
  • References
  • Chapter 15: Hierarchy of System Morphisms
  • Abstract
  • 15.1. The I/O Frame Morphism
  • 15.2. The I/O Relation Observation Morphism
  • 15.3. The I/O Function Morphism
  • 15.4. The I/O System Morphism
  • 15.5. System Morphism for Iteratively Specified Systems
  • 15.6. The Structured System Morphism
  • 15.7. Multi-Component System Morphism
  • 15.8. The Network of Systems Morphism
  • 15.9. Homomorphism and Cascade Decompositions
  • 15.10. Characterization of Realizable I/O Relations and Functions
  • 15.11. Summary
  • 15.12. Sources
  • References
  • Chapter 16: Abstraction: Constructing Model Families
  • Abstract
  • 16.1. Scope/Resolution/Interaction Product
  • 16.2. Integrated Families of Models
  • 16.3. Aggregation: Homogeneity/Coupling Indifference Principles
  • 16.4. All-to-One Coupling
  • 16.5. Abstractions for Event-Based Control
  • 16.6. Parameter Morphisms
  • 16.7. Summary
  • 16.8. Sources
  • References
  • Chapter 17: Verification, Validation, Approximate Morphisms: Living With Error
  • Abstract
  • 17.1. Verification
  • 17.2. Validation at the Behavioral Level
  • 17.3. Performance/Validity (e.g. Speed/Accuracy) Trade-off
  • 17.4. Approximate Morphisms and Error Behavior
  • 17.5. Approximate Morphisms at the Coupled System Level
  • 17.6. Validation at Structural Levels
  • 17.7. Handling Time Granularity Together With Abstraction
  • 17.8. Multi-Fidelity Modeling and Simulation Methodology
  • 17.9. Summary
  • References
  • Chapter 18: DEVS and DEVS-Like Systems: Universality and Uniqueness
  • Abstract
  • 18.1. Relation Between Classical and Parallel DEVS: Are There One DEVS or Two?
  • 18.2. Universality and Uniqueness of DEVS
  • 18.3. DEVS Representation of DTSS
  • 18.4. Efficient DEVS Simulation of DTSS Networks
  • Summary
  • 18.5. Sources
  • Appendix 18.A. Isomorphically Representing DEVS-Like Systems by DEVS
  • References
  • Chapter 19: Quantization-Based Simulation of Continuous Time Systems
  • Abstract
  • 19.1. Quantization Principles
  • 19.2. Quantized State Systems
  • 19.3. QSS Extensions
  • 19.4. QSS Simulation of Hybrid Systems
  • 19.5. Logarithmic Quantization
  • 19.6. Software Implementations of QSS Methods
  • 19.7. Applications of QSS Methods
  • 19.8. Comparison of QSS With Discrete Time Methods: Activity-Based Approach
  • Sources and Further Reading
  • References
  • Chapter 20: DEVS Representation of Iteratively Specified Systems
  • Abstract
  • 20.1. DEVS Bus Revisited
  • 20.2. DEVS Simulation of DESS With Arbitrarily Small Error
  • 20.3. DEVS Component-Wise Simulation of Iteratively Specified Coupled Systems
  • 20.4. Simulation Study of Message Reduction Under Quantization
  • 20.5. Summary
  • 20.6. Sources
  • References
  • Part 4: Enhanced DEVS Formalisms
  • Chapter 21: DEVS Markov Modeling and Simulation
  • Abstract
  • 21.1. Markov Modeling
  • 21.2. Background
  • 21.3. Mapping DEVS Markov Models
  • 21.4. Hidden Markov Models
  • 21.5. Preview: Closure Under Coupling of DEVS Markov Models
  • 21.6. Formalization of DEVS Markov Models
  • 21.7. Continuous and Discrete Time Subclasses of Markov Models
  • 21.8. Relations Between DEVS CTM and DTM
  • Appendix 21.A. Exponential Distribution and Markov Model Basics
  • Appendix 21.B. Traditional Approach to CTM Implementation
  • References
  • Chapter 22: DEVS Markov Model Lumping
  • Abstract
  • 22.1. Overall Approach
  • 22.2. Homomorphism of Timed Non-Deterministic Models
  • 22.3. Homomorphism of DEVS Markov Models
  • 22.4. Example: Combat Attrition Modeling
  • 22.5. Approximate Morphisms
  • 22.6. Application to General Markov Matrix Lumpability
  • 22.7. Lumping of DEVS Markov Models to Study Speedup in Multiprocessor Computation
  • 22.8. Summary
  • Appendix 22.A. Prioritized Communication in Multiprocessor Clusters
  • References
  • Chapter 23: Spiking Neuron Modeling – Iterative Specification
  • Abstract
  • 23.1. A Biological Neuron as a Dynamic System
  • 23.2. Discrete Event Modeling of a Leaky Integrate and Fire Neuron
  • 23.3. Multi-Level Iterative Specification
  • 23.4. Iterative Specification Modeling of Spiky Neurons
  • 23.5. Summary
  • Appendix 23.A. Iterative System Specification of a Spiking Neuron
  • Appendix 23.B. Iterative Specification Modeling of Bursty Neurons
  • References
  • Chapter 24: Open Research Problems: Systems Dynamics, Complex Systems
  • Abstract
  • 24.1. Systems Dynamics, DEVS, and Challenges for M&S of Complex Systems
  • 24.2. System Dynamics
  • 24.3. Mapping SD Into DEVS
  • 24.4. Challenges for Sound Interdisciplinary M&S of Large Complex Systems: the Case of Socio-Ecological Global Sustainability
  • 24.5. Theory-Based Research Needed
  • References
  • Index

Product details

  • No. of pages: 692
  • Language: English
  • Copyright: © Academic Press 2018
  • Published: August 14, 2018
  • Imprint: Academic Press
  • Paperback ISBN: 9780128133705
  • eBook ISBN: 9780128134078

About the Authors

Bernard P. Zeigler

Bernard P. Zeigler, is a Professor of Electrical & Computer Engineering at the University of Arizona and co-director of the Arizona Center for Integrative Modeling and Simulation. He is the author of numerous books and publications, a Fellow of the IEEE, and of the Society for Modeling and Simulation International.

Zeigler is currently heading a project for the Joint Interoperability Test Command (JITC) where he is leading the design of the future architecture for large distributed simulation events for the Joint Distributed Engineering Plant (JDEP). He is also developing DEVS-methodology approaches for testing mission thread end-to-end interoperability and combat effectiveness of Defense Department acquisitions and transitions to the Global Information Grid with its Service Oriented Architecture (GIG/SOA).

Affiliations and Expertise

University of Arizona, Tucson, USA

Alexandre Muzy

Alexandre MUZY is research fellow at CNRS, France, where he is in charge of the research group Modélisation, Simulation & Neurocognition (MS&N) at I3S laboratory in Sophia Antipolis.

Affiliations and Expertise

Universite Cote d'Azur, CNRS, I3S, France

Ernesto Kofman

Ernesto Kofman is a Professor at the Control Department at the Faculty of Exact Sciences, Engineering and Surveying of the National University of Rosario (FCEIA-UNR) and a Research Member of the National Research Council of Argentina (CONICET) , where he is in charge of the Simulation and Automatic Control Group of the French-Argentine International Center for Information and Systems Sciences (CIFASIS).

Affiliations and Expertise

FCEIA, Universidad Nacional de Rosario - CIFASIS-CONICET, Argentina

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  • GianniFerretti Sat Mar 30 2019

    Theory of Modeling and Simulation

    Theory of Modeling and Simulation