Network Modeling, Simulation and Analysis in MATLAB

Dac-Nhuong Le obtained his PhD in computer science from Vietnam National University, Vietnam in 2015. He is Deputy-Head of Faculty of Information Technology, Haiphong University, Vietnam. His area of research includes: evaluation computing and approximate algorithms, network communication, security and vulnerability, network performance analysis and simulation, cloud computing, IoT and image processing in biomedicine. He has authored 4 computer science books and has multiple research articles in international journals. Abhishek Kumar Pandey is pursuing a doctorate in computer science from the University of Madras and is doing ongoing research on face recognition using the IoT concept. He has a Masters of Technology in Computer Science and Engineering from Government Engineering College, Ajmer, Rajasthan Technical University, Kota, India. He has been working as an Assistant Professor of Computer Science at Aryabhatt Engineering College and Research Center, Ajmer, as well as a visiting faculty member at Government University MDS Ajmer. Sairam Tadepalli completed his Bachelors in Computer Science and Engineering and Masters in Cloud Computing and is pursuing a PhD in Machine Learning from Vellore Institute of Technology. He has a certification in data science from John Hopkins University, USA. Pramod Singh Rathore has a Masters of Technology in Computer Science and Engineering from Government Engineering College, Ajmer, Rajasthan Technical University, Kota, India. He has been working as the Assistant Professor of Computer Science at Aryabhatt Engineering College and Research Centre, Ajmer, and also as a visiting faculty member at Government University MDS Ajmer. He has authored a book on network simulation. Jyotir Moy Chatterjee is currently working as an Assistant Professor of IT at Lord Buddha Education Foundation (Asia Pacific University of Technology and Innovation), Kathmandu, Nepal. He received his M.Tech from KIIT University, Bhubaneswar, Odisha and B.Tech in Computer Science & Engineering from Dr. MGR Educational & Research Institute University, Chennai, (Tamil Nadu). His research interests include cloud computing, big data, privacy preservation and data mining.

• List of Figures xiList of Tables xvForeword xviiPreface xixAcknowledgments xxiAcronyms xxiii1 Introduction to Modeling, Simulations and Analysis 11.1 MATLAB Modeling and Simulation 21.2 Computer Networks Performance Modeling and Simulation 41.2.1 Computer-Based Models 41.2.2 Computer Network Simulation 51.3 Discrete-Event Simulation for MATLAB 61.3.1 Terminology and Components of Discrete-Event Simulation 71.3.2 The Principle of Discrete-Event Simulation 81.3.3 ESTA Algorithm 91.3.4 ANALYSIS: Determination of Time to Attain Steady State Condition for MATLAB 111.4 Simulation Software Selection for MATLAB 111.5 Simulation Tools Based on High Performance 121.5.1 Network Model 131.5.2 Network Simulators 151.6 Conclusion 22References 232 Introduction to MATLAB Programming 252.1 Introduction 262.2 Basic Features 272.2.1 Features of MATLAB 272.2.2 Uses of MATLAB 272.3 Notation, Syntax, and Operations 272.3.1 Practical Examples for MATLAB 272.3.2 Use of Semicolon (;) in MATLAB 282.3.3 Adding Comments 292.3.4 Commonly Utilized Operators and Special Characters 292.3.5 Unique Variables and Constants 302.3.6 Sparing Process 302.3.7 MATLAB Decisions 302.3.8 MATLAB Loops 312.4 Import and Export Operations 322.4.1 Import Data in MATLAB 322.4.2 Export Data in MATLAB 382.5 Elements 402.5.1 Commands 402.5.2 MATLAB Basics 412.5.3 Creating Matrices 422.5.4 Framework Operations 422.5.5 Using M-Files 442.6 Plotting 472.6.1 Including Various Types of Graphs 482.6.2 Creation of a Multiple Number of Functions in a Similar Graph 492.6.3 Creating a Graph According to Various Colors 502.7 Uncommon Function 512.8 Executable Files Generation 522.9 Calling and Accumulating Executable Documents 542.10 Calling Objects from External Programs 552.11 JAVA Classes 562.12 The Guide 562.12.1 Open a New User Interface 572.12.2 Guide Window Size Setting 582.12.3 Design the User Interface 582.12.4 Adjust the Components 592.12.5 Mark the Push Buttons 602.12.6 Menu Items-Rundown Pop-Up 612.12.7 Static Test Alteration Procedure in MATLAB 612.12.8 Spare the Layout 622.12.9 Behavior of the App 632.12.10 Produce Data to Plot in MATLAB 632.12.11 Pop-Up Menu Characteristics 652.12.12 Behavior of Push Button 662.13 Effective Programming through MATLAB 672.13.1 Condition 682.13.2 Practice Programs 682.13.3 Specific Functions in MATLAB 692.14 Clones Process Using MATLAB 692.14.1 GNU Octave 692.14.2 Scilab 702.14.3 Sage 702.15 Parallel MATLAB System 712.15.1 Run a Batch Job 712.15.2 Run a Batch Parallel Loop 722.15.3 Current Folder Browser - Run Script as Batch Job 732.16 Conclusion 74References 753 Digital Communication System Simulation Using MATLAB 773.1 Introduction to Digital Communication 783.1.1 Data Transmission 783.1.2 Example 793.1.3 The Conversion of Analog and Digital Signals 803.1.4 Information, Bandwidth, and Noise 823.2 Simulation of Rayleigh Fading Model 833.2.1 Rayleigh Fading Basics 833.2.2 Rayleigh Fading 843.3 BPSK Modulation and Demodulation 863.3.1 BPSK Modulation 863.3.2 BPSK Demodulation 873.4 QPSK Modulation and Demodulation 893.4.1 QPSK Transmitter 903.4.2 QPSK Receiver 933.4.3 Performance Simulation over AWGN 933.5 Image Error Rate vs Signal-to-Noise Ratio 943.5.1 M-QAM Modulation 943.5.2 Baseband Rectangular M-QAM Modulator 953.6 Recreation of OFDM Framework 993.6.1 Figuring (Es /n0) or (Eb /n0) for OFDM Framework 1013.6.2 Impact of Cyclic Prefix on Es /n 1013.6.3 Effect of Unused Subcarriers on Es/N 1023.6.4 Arrangement of Subcarriers 1033.6.5 MATLAB Sample Code 1033.7 Conclusion 108References 1094 Statistical Analysis of Network Data Using MATLAB 1114.1 Introduction to Association Networks 1124.2 Time Series, Stationary, Time Series Decomposition, De-trending 1144.2.1 Time Series Analysis 1144.2.2 Stationarity 1154.2.3 Time Series Decomposition 1174.2.4 De-trending 1184.3 Autocorrelation, Test for Independence, Linear Autoregressive Models 1244.3.1 Autocorrelation 1244.3.2 ACF and IACF Parameters 1264.3.3 Test of Independence 1284.3.4 Linear Autoregressive Models 1354.3.5 Linear Prediction and Autoregressive Modeling 1374.4 Mutual Information and Test for Independence 1394.4.1 Testing the Significance of the Null Hypothesis I(X; Y) = 0 1394.4.2 Producing the Mutual Information Distribution from Surrogates 1414.5 Spurious Cross-Correlation, Vector Autoregressive Models and Dynamic Regression Models 1434.5.1 Cross Correlation 1434.5.2 Vector Autoregression (VAR) Models 1464.5.3 Coupled Dynamical Systems 1494.6 Conclusion 150References 1505 Network Routing Simulation Using MATLAB 1555.1 Evaluation of Granger Causality Measures on Known Systems 1565.1.1 A Historical Viewpoint 1585.1.2 Application to Recreated Information 1645.1.3 Application to FMRI BOLD Information from a Visuospatial Consideration Undertaking 1705.2 Demand Modeling and Performance Measurement 1735.2.1 Objectives 1735.2.2 Approach to Model Development 1745.2.3 Development of Models 1755.2.4 Outline of Findings from Phase Two: Model Validation 1765.3 Universal Algorithms and Sequential Algorithms 1785.3.1 Genetic Algorithm for Improvement Utilizing MATLAB 1785.3.2 Masses Diversity-Measure-Run, Prosperity Scaling 1825.4 Acoustic-Centric and Radio-Centric Algorithms 1905.5 AODV Routing Protocol 1945.5.1 Keeping Up Sequence Numbers 1965.5.2 Association Breaks 1965.5.3 Neighborhood Repairs 1975.5.4 Security Considerations 1975.6 Conclusion 203References 2046 Wireless Network Simulation Using MATLAB 2096.1 Radio Propagation for Shadowing Methods 2106.1.1 Radio Propagation Modeling 2106.1.2 Partition Dependence 2106.1.3 Small-Scale Blurring 2106.1.4 Free-Space Propagation 2116.1.5 Ray Tracing 2126.1.6 Indoor Propagation 2206.1.7 Classic Empirical Models 2216.1.8 COST 231-Hata Model 2216.1.9 COST 231-Walfish-Ikegami Model 2226.1.10 Erceg Model 2246.1.11 Multiple Slope Models 2256.2 Mobility: Arbitrary Waypoint Demonstrates 2346.2.1 Random Waypoint Model 2346.2.2 Regular Problems with Random Waypoint Model 2356.2.3 Irregular Waypoint on the Border (RWPB) 2356.2.4 Markovian Waypoint Model 2356.3 PHY: SNR-Based Bundle Catches, Communication, Dynamic Transmission Rate and Power 2356.3.1 Mac: Ieee 802.11 2366.3.2 IEEE 802.11 RTS/CTS Exchange 2376.4 NET: Ad Hoc Routing 2386.4.1 Dynamic Destination Sequenced Distance Vector 2406.4.2 Wireless Routing Protocol 2436.4.3 Global State Routing 2436.4.4 Fisheye State Routing 2446.4.5 Hierarchical State Routing 2446.4.6 Zone-Based Hierarchical Link State Routing Protocol 2456.4.7 Clusterhead Gateway Switch Routing Protocol 2466.4.8 Cluster-Based Routing Protocols 2476.4.9 Ad Hoc On-Demand Distance Vector Routing 2486.4.10 Dynamic Source Routing Protocol 2496.4.11 Temporally Ordered Routing Algorithm 2506.4.12 Associativity-based Routing 2526.4.13 Signal Stability Routing 2536.5 APP: Overlay Routing Protocols 2546.5.1 System/Application Designs, Optimizations, and Implementations on Overlay Networks 2546.5.2 Routing Overlays for VoIP 2556.5.3 Measurement, Modeling, and Improvement of BitTorrent Overlays 2566.6 Conclusion 259References 2607 Mobility Modeling for Vehicular Communication Networks Using MATLAB 2677.1 Vehicle Network Toolbox 2687.1.1 Transmit and Receive CAN Messages 2687.1.2 Examine Received Messages 2717.1.3 CAN Message Reception Callback Function 2727.2 Network Management (NM) 2747.2.1 Plan Your Network Installation 2747.2.2 Planning Your Network Installation 2757.2.3 Setting Up a Remote Client Access Configuration 2757.2.4 Setting Up Local Client Access Configuration 2757.3 Interaction Layer 2777.3.1 Directing Protocols in MANET 2787.3.2 Specially Appointed On-Demand Distance Vector 2787.3.3 Dynamic Source Routing (DSR) 2787.3.4 Diagram of Mobility Model 2797.3.5 Results and Analysis 2807.3.6 Association Variation Results 2827.4 Transport Protocols 2857.4.1 TCP Transport Protocol 2857.4.2 User Datagram Protocol, or UDP 2867.4.3 Reliable Data Protocol, or RDP 2867.4.4 Transmission Control Protocol, or TCP 2867.5 Conclusion 287References 2888 Case Studies and Sample Codes 2918.1 Case Determination and Structure 2928.1.1 Exhibiting Analysis 2938.1.2 Case Example 2938.1.3 The Best Strategy 2938.1.4 Impediment of the Technique 2938.1.5 Sorts of Contextual Investigations 2948.1.6 Relevant Examinations in Business 2948.1.7 Summing Up from Logical Investigations 2948.1.8 History 2958.1.9 Related Vocations 2958.2 Case Study 1: Gas Online 2968.2.1 Load Data into Project 2968.2.2 Construct Boundary Models 2968.3 Case Study 2 3028.3.1 Case 1: Create a Credit Scorecard Dissent 3028.3.2 Case 2: Binning Information 3048.4 Case Study 3: Random Waypoint Mobility Model 3068.5 Case Study 4: Node localization in Wireless Sensor Network 3128.6 Case Study 5: LEACH Routing Protocol for a WSN 3258.7 Conclusion 334References 334