Complete project work PDF and DOC download titled Approach To A Simulation Virtual Machine: Object Oriented Implementation Of Cdevs And Pdevs
Approach To A Simulation Virtual Machine: Object Oriented Implementation Of Cdevs And Pdevs
ABSTRACT
In the world today, the size of complex problems and systems has increased, due to
the advances in technology and the area of computer design and architecture.
Modeling and predicting the behaviour of complex systems (Weather forecast, Fire
spreading, River floods, Earthquake, Nanotechnology; design of new materials from
molecule scale, decoding the human genome and many others) is becoming complex
due to huge amount of data, high statistics need, and the need to serve user
communities around the world. Therefore there is a need of exploiting the computing
power of nowadays technologies by distributing simulation on multiple processors in
order to reduce execution time, perform real time execution, and integrate simulators.
In this work we present an approach to Discrete Event System Specification (DEVS)
virtual machine that will take a DEVS model and maps its simulation onto any
hardware host like a LAN, a WAN, a Grid, a Cluster, the Internet and so on. The
virtual machine is structured in 3 layers; the modeling layer which receives the
DEVS model, the simulation layer which simulates the model using either the
pessimistic synchronization algorithm or the optimistic synchronization algorithm,
and the last layer which is the Middleware layer that allows the mapping of the
simulation onto any hardware host.
The kernel of the virtual machine contains a CDEVS implementation of the simulator,
PDEVS implementation of the simulator, and the distributed versions of them.
Starting with an existing CDEVS simulator we got its PDEVS implementation using a
meta modeling approach. And we finally provide the multilayer simulation package
TABLE OF CONTENTS
Abstract…………………………………………………………………………….iii
Dedication………………………………………………………………………….iv
Acknowledgements………………………………………………………………..v
Table of Contents………………………………………………………………… vi
Chapter 1 Introduction
1.1 Introduction to Computer Simulation.………………………………….1
1.2 Objective……………………………………………………………………2
1.3 Work Done………………………………………………………………………2
1.3 Organisation..……………………………………………………………3
Chapter 2 Discrete Event System Specification (DEVS)
2.1 Discrete Event Simulation………………………………….………………4
2.2 Discrete Event System Specification (DEVS)……….…………………….4
2.3 Classic DEVS (CDEVS)……………………………………………………5
2.4 Parallel DEVS (PDEVS)……………………………………………………9
Chapter 3 Modeling the Simulation System
3.1 The Static View of the CDEVS Simulator……………………………………….12
3.2 The Dynamic View of the CDEVS Simulator………………………………….15
3.3 The Static View of the PDEVS Simulator……………………………………….16
3.4 The Dynamic View of the PDEVS Simulator………………………………….17
vi
Chapter 4 Translation to Code
4.1 The CDEVS Simulation Algorithm Implementation…………………..18
4.2 The PDEVS Simulation Algorithm Implementation…………………..20
Chapter 5 Case Study and Comparison
5.1 Case Study: The Microwave Oven Example………..…………………..21
5.2 The CDEVS Microwave Oven Example………………………..……..22
5.3 The PDEVS Microwave Oven Example………………..……………..27
5.4 Comparison between the CDEVS and the PDEVS Simulation
Time……………………………………………………………………………………………….34
Chapter 6 Conclusions
6.1 Conclusions…………………………………………………………………36
CHAPTER ONE
Introduction
1.1 Introduction to Computer Simulation
A Simulation is a computation that models the behaviour of some real or imagined
system over time. And it is referred to as Computer Simulation when the computation
is done on a computer. In the world today simulations are widely used to analyse the
behaviour of systems such as fire spread, weather forecast, air traffic control,
decoding the human genome and the design of new telecommunication networks
without physically constructing the system in cases where constructing a prototype
may be costly or even infeasible. But modeling and predicting the behaviour of
complex systems is becoming complex too, due to huge amount of data, high statistics
need, and the need to serve user communities around the world. Therefore there is a
need of exploiting the computing power of nowadays technologies by distributing
simulation on multiple processors in order to reduce execution time, perform real time
execution, and integrate simulators. To see more about parallel and distributed
simulation see the book (Fujimoto 2000).
“The study of any physical system to be simulated begins with the creation of a
model. Such a model can be in one of several types: 1) Conceptual, 2) Declarative, 3)
Functional, 4) Constraints, 5) Spatial or 6) Multi model.” (Fishwick and Lin
1996). The conceptual model describes qualitative terms and class hierarchies for the
system. In many ways the conceptual model organizes the definition of attributes,
methods and general characteristics of each system components without going so far
to ascribe dynamics to components. The next four model types reflect an orientation
to system construction; a system may be constructed as Petri net, Queuing model or as
cellular automaton for instance. The last model type (Multi model) permits the
integration of basic model types to create a model composed of component models
where each component model represents a level of abstraction for the system
(Fishwick and Lin 1996).
2
After building a model from the real system or imagined system, aspects
relevant to simulation are retained and irrelevant aspects are discarded then a
simulation model is constructed that can be executed on a computer.
DEVS abbreviating Discrete Event System Specification is a modular and
hierarchical formalism for modeling and analyzing general systems that can be
discrete event systems which might be described by state transition tables, and
continuous state systems which might be described by differential equations and
hybrid continuous state and discrete event systems (Wikipedia 2007). We will talk
more about DEVS in the next chapter.
1.2 Objective
Our main objective is to present a DEVS virtual machine that will take a DEVS
model and maps its simulation onto any hardware host like a LAN, a WAN, a Grid, a
Cluster, the Internet and so on. The virtual machine is structured in 3 layers; the
modeling layer which receives the DEVS model, the simulation layer which
simulates the model using either the pessimistic synchronization algorithm or the
optimistic synchronization algorithm, and the last layer which is the Middleware layer
that allows the mapping of the simulation onto any hardware host.
The kernel of the virtual machine will contain a CDEVS implementation of the
simulator, PDEVS implementation of the simulator, and the distributed versions of
them.
1.3 Work Done
Starting with an existing CDEVS simulator we got its PDEVS implementation using a
meta modeling approach. The two simulation packages for the CDEVS and the
PDEVS are available, but the complete package for the virtual machine is not
available being it a research prototype. Both the CDEVS and the PDEVS simulators
are implemented using Java, and JVM is used as our virtual machine in this case. We
tested the simulators with an example, and make a comparison between the duration
of the simulation in each simulator.
3
1.4 Organisation
Chapter 1 is the introductory chapter. The CDEVS and PDEVS formalisms are
described in chapter 2. And their modeling using Unified Modeling Language (UML)
is presented in chapter 3, where we show the static and the dynamic view of the
simulators. In Chapter 4 we present how we translate the Model into Java code, the
packages and classes involved. An example is considered in Chapter 5, where we
compare the simulation time between the two simulators. Chapter 6 is the conclusion
chapter.
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