Discrete-Event Modeling and Simulation

Theory and Applications

Gabriel A. Wainer, Pieter J. Mosterman, Gabriel A. Wainer, Pieter J. Mosterman

• Publisher: CRC Press
• Year: 2018
• ISBN:
  9781351834629
• Edition: 1
• Topic: Technik & Maschinenbau
• Subtopic: Maschinenbau Allgemein

Collecting the work of the foremost scientists in the field, Discrete-Event Modeling and Simulation: Theory and Applications presents the state of the art in modeling discrete-event systems using the discrete-event system specification (DEVS) approach. It introduces the latest advances, recent extensions of formal techniques, and real-world examples of various applications.

The book covers many topics that pertain to several layers of the modeling and simulation architecture. It discusses DEVS model development support and the interaction of DEVS with other methodologies. It describes different forms of simulation supported by DEVS, the use of real-time DEVS simulation, the relationship between DEVS and graph transformation, the influence of DEVS variants on simulation performance, and interoperability and composability with emphasis on DEVS standardization. The text also examines extensions to DEVS, new formalisms, and abstractions of DEVS models as well as the theory and analysis behind real-world system identification and control. To support the generation and search of optimal models of a system, a framework is developed based on the system entity structure and its transformation to DEVS simulation models. In addition, the book explores numerous interesting examples that illustrate the use of DEVS to build successful applications, including optical network-on-chip, construction/building design, process control, workflow systems, and environmental models.

A one-stop resource on advances in DEVS theory, applications, and methodology, this volume offers a sampling of the best research in the area, a broad picture of the DEVS landscape, and trend-setting applications enabled by the DEVS approach. It provides the basis for future research discoveries and encourages the development of new applications.

Section I

Theory

1	DEVS as a Semantic Domain for Programmed Graph Transformation Eugene Syriani and Hans Vangheluwe

CONTENTS

1.1 Introduction

1.1.1 Meta-Modeling and Model Transformation

1.1.2 The Discrete Event System Specification

1.2 The Antworld Simulation Case Study

1.2.1 The AntWorld Language (Abstract and Concrete Syntax)

1.2.2 The AntWorld Semantics (Graph Transformation)

1.3 A Meta-Model for DEVS-Based Graph Transformation

1.3.1 The ARule

1.3.2 The CRule

1.3.3 The Selector

1.3.4 The Synchronizer

1.4 Using MoTif for the Antworld Simulator Case Study

1.4.1 The Round Block

1.4.2 The HumanStep Block

1.4.3 The Controller Block

1.4.4 The User Block

1.4.5 Simulation Results

1.5 Timed Graph Transformation

1.5.1 Introduction of Time

1.5.2 Real-Time Model Transformation and Deployment

1.6 Related Graph Transformation Tools

1.7 Conclusions

References

1.1 INTRODUCTION

1.1.1 META-MODELING AND MODEL TRANSFORMATION

Model-driven approaches are becoming increasingly important in the area of software engineering. In model-driven development, models are constructed to conform to meta-models. A meta-model defines the (possibly infinite) set of all well-formed model instances. As such, a meta-model specifies the syntax and static semantics of models. Meta-models are often described as the Unified Modeling Language (UML) Class Diagrams. In model-driven engineering, meta-modeling goes hand-in-hand with model transformation.

In almost all modeling and simulation endeavors, some form of model transformation is used. Models are, for example, transformed for optimization purposes, to address new requirements, to synthesize real-time embedded code, and so on. Transformations are also commonly used to describe the semantics of a modeling formalism. In the case of operational semantics, the transformation iteratively updates the state of a model. In the case of denotational semantics, the transformation maps a model in one formalism onto a model in a known formalism, thereby defining the meaning of the original model. Model transformations can be described in many ways. Rule-based descriptions are elegant and easy to understand. Such descriptions have declarative (specifying “what” to change, not “how” to) model rewriting rules as their primitive building blocks. A rule consists of a left-hand side (LHS) pattern that is matched against a host model. If a match is found, this pattern is updated, in the host model, based on what is specified in the right-hand side (RHS) of the rule. Additionally, Negative Application Condition (NAC) patterns may be used, specifying which patterns should not be found in the host model. Because at some level of abstraction, all models can be represented as (typed, attributed) graphs, and thanks to its rigorous formal underpinning, our rule-based specification is based on the theory of graph rewriting.

Though elegant, the declarative, rule-based specifications of model transformations do not scale well. When the number of rules grows, it becomes difficult for a modeler to ...