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.

Chapter 1

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). 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.

Department: Computer Science (M.Sc Thesis)

Format: MS Word

Chapters: 1 - 5, Preliminary Pages, Abstract, References, Appendix.

No. of Pages: 44

Price: 20,000 NGN

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