Network Modeling and Simulation

Preface Acknowledgements 1 Basic Concepts and Techniques 1.1 Why Is Simulation Important? 1.2 What Is a Model? 1.3 Performance Evaluation Techniques 1.4 Development of Systems Simulation 1.5 Summary Recommended Reading 2 Designing and Implementing a Discrete-Event Simulation Framework 2.1 The Scheduler 2.2 The Simulation Entities 2.3 The Events 2.4 Tutorial 1: Hello World 2.5 Tutorial 2: Two-Node Hello Protocol 2.6 Tutorial 3: Two-Node Hello through a Link 2.7 Tutorial 4: Two-Node Hello through a Lossy Link 2.8 Summary Recommended Reading 3 Honeypot Communities: A Case Study with the Discrete-Event Simulation Framework 3.1 Background 3.2 System Architecture 3.3 Simulation Modeling 3.4 Simulation Execution 3.5 Output Analysis 3.6 Summary Recommended Reading 4 Monte Carlo Simulation 4.1 Characteristics of Monte Carlo Simulations 4.2 The Monte Carlo Algorithm 4.3 Merits and Drawbacks 4.4 Monte Carlo Simulation for the Electric Car Charging Station 4.5 Summary Recommended Reading 5 Network Modeling 5.1 Simulation of Networks 5.2 The Network Modeling and Simulation Process 5.3 Developing Models 5.4 Network Simulation Packages 5.5 OPNET: A Network Simulation Package 5.6 Summary Recommended Reading 6 Designing and Implementing CASiNO: A Network Simulation Framework 6.1 Overview 6.2 Conduits 6.3 Visitors 6.4 The Conduit Repository 6.5 Behaviors and Actors 6.6 Tutorial 1: Terminals 6.7 Tutorial 2: States 6.8 Tutorial 3: Making Visitors 6.9 Tutorial 4: Muxes 6.10 Tutorial 5: Factories 6.11 Summary Recommended Reading 7 Statistical Distributions and Random Number Generation 7.1 Introduction to Statistical Distributions 7.2 Discrete Distributions 7.3 Continuous Distributions 7.4 Augmenting CASiNO with Random Variate Generators 7.5 Random Number Generation 7.6 Frequency and Correlation Tests 7.7 Random Variate Generation 7.8 Summary Recommended Reading 8 Network Simulation Elements: A Case Study Using CASiNO 8.1 Making a Poisson Source of Packets 8.2 Making a Protocol for Packet Processing 8.3 Bounding Protocol Resources 8.4 Making a Round-Robin (De)multiplexer 8.5 Dynamically Instantiating Protocols 8.6 Putting It All Together 8.7 Summary 9 Queuing Theory 9.1 Introduction to Stochastic Processes 9.2 Discrete-Time Markov Chains 9.3 Continuous-Time Markov Chains 9.4 Basic Properties of Markov Chains 9.5 Chapman-Kolmogorov Equation 9.6 Birth-Death Process 9.7 Little's Theorem 9.8 Delay on a Link 9.9 Standard Queuing Notation 9.10 The M/M/1 Queue 9.11 The M/M/m Queue 9.12 The M/M/1/b Queue 9.13 The M/M/m/m Queue 9.14 Summary Recommended Reading 10 Input Modeling and Output Analysis 10.1 Data Collection 10.2 Identifying the Distribution 10.3 Estimation of Parameters for Univariate Distributions 10.4 Goodness-of-Fit Tests 10.5 Multivariate Distributions 10.6 Selecting Distributions without Data 10.7 Output Analysis 10.8 Summary Recommended Reading 11 Modeling Network Traffic 11.1 Introduction 11.2 Network Traffic Models 11.3 Traffic Models for Mobile Networks 11.4 Global Optimization Techniques 11.5 Particle Swarm Optimization 11.6 Optimization in Mathematics 11.7 Summary Recommended Reading Index