{"product_id":"wireless-communication-security-9781119777144","title":"Wireless Communication Security","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eWIRELESS COMMUNICATION SECURITY  Presenting the concepts and advances of wireless communication security, this volume, written and edited by a global team of experts, also goes into the practical applications for the engineer, student, and other industry professionals.  Covering a broad range of topics in wireless communication security and its solutions, this outstanding new volume is of great interest to engineers, scientists, and students from a variety of backgrounds and interests. Focusing on providing the theory of wireless communication within the framework of its practical applications, the contributors take on a wealth of topics, integrating seemingly diverse areas under one cover.   Wireless Communication Security has been divided into five units. The first unit presents the different protocols and standards for developing a real-time wireless communication security. The second unit presents different widely accepted networks, which are the core of wireless communication secu\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003ePreface xiii\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 M2M in 5G Cellular Networks: Challenges, Proposed Solutions, and Future Directions 1\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eKiran Ahuja and Indu Bala\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 2\u003c\/p\u003e \u003cp\u003e1.2 Literature Survey 5\u003c\/p\u003e \u003cp\u003e1.3 Survey Challenges and Proposed Solutions of M2M 7\u003c\/p\u003e \u003cp\u003e1.3.1 PARCH Overload Problem 8\u003c\/p\u003e \u003cp\u003e1.3.2 Inefficient Radio Resource Utilization and Allocation 10\u003c\/p\u003e \u003cp\u003e1.3.3 M2M Random Access Challenges 12\u003c\/p\u003e \u003cp\u003e1.3.4 Clustering Techniques 13\u003c\/p\u003e \u003cp\u003e1.3.5 QoS Provisioning for M2M Communications 15\u003c\/p\u003e \u003cp\u003e1.3.6 Less Cost and Low Power Device Requirements 16\u003c\/p\u003e \u003cp\u003e1.3.7 Security and Privacy 17\u003c\/p\u003e \u003cp\u003e1.4 Conclusion 18\u003c\/p\u003e \u003cp\u003eReferences 19\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 MAC Layer Protocol for Wireless Security 23\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eSushmita Kumari and Manisha Bharti\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 23\u003c\/p\u003e \u003cp\u003e2.2 MAC Layer 24\u003c\/p\u003e \u003cp\u003e2.2.1 Centralized Control 24\u003c\/p\u003e \u003cp\u003e2.2.2 Deterministic Access 24\u003c\/p\u003e \u003cp\u003e2.2.3 Non-Deterministic Access 24\u003c\/p\u003e \u003cp\u003e2.3 Functions of the MAC Layer 25\u003c\/p\u003e \u003cp\u003e2.4 MAC Layer Protocol 25\u003c\/p\u003e \u003cp\u003e2.4.1 Random Access Protocol 26\u003c\/p\u003e \u003cp\u003e2.4.2 Controlled Access Protocols 29\u003c\/p\u003e \u003cp\u003e2.4.3 Channelization 31\u003c\/p\u003e \u003cp\u003e2.5 MAC Address 31\u003c\/p\u003e \u003cp\u003e2.6 Conclusion and Future Scope 33\u003c\/p\u003e \u003cp\u003eReferences 33\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Enhanced Image Security Through Hybrid Approach: Protect Your Copyright Over Digital Images 35\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eShaifali M. Arora and Poonam Kadian\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 36\u003c\/p\u003e \u003cp\u003e3.2 Literature Review 38\u003c\/p\u003e \u003cp\u003e3.3 Design Issues 40\u003c\/p\u003e \u003cp\u003e3.3.1 Robustness Against Various Attack Conditions 40\u003c\/p\u003e \u003cp\u003e3.3.2 Distortion and Visual Quality 41\u003c\/p\u003e \u003cp\u003e3.3.3 Working Domain 42\u003c\/p\u003e \u003cp\u003e3.3.4 Human Visual System (HVS) 43\u003c\/p\u003e \u003cp\u003e3.3.5 The Trade-Off between Robustness and Imperceptibility 43\u003c\/p\u003e \u003cp\u003e3.3.6 Computational Cost 43\u003c\/p\u003e \u003cp\u003e3.4 A Secure Grayscale Image Watermarking Based on DWT-SVD 43\u003c\/p\u003e \u003cp\u003e3.5 Experimental Results 45\u003c\/p\u003e \u003cp\u003e3.6 Conclusion 52\u003c\/p\u003e \u003cp\u003eReferences 52\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Quantum Computing 59\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eManisha Bharti and Tanvika Garg\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 59\u003c\/p\u003e \u003cp\u003e4.2 A Brief History of Quantum Computing 60\u003c\/p\u003e \u003cp\u003e4.3 Postulate of Quantum Mechanics 61\u003c\/p\u003e \u003cp\u003e4.4 Polarization and Entanglement 61\u003c\/p\u003e \u003cp\u003e4.5 Applications and Advancements 63\u003c\/p\u003e \u003cp\u003e4.5.1 Cryptography, Teleportation and Communication Networks 63\u003c\/p\u003e \u003cp\u003e4.5.2 Quantum Computing and Memories 63\u003c\/p\u003e \u003cp\u003e4.5.3 Satellite Communication Based on Quantum Computing 64\u003c\/p\u003e \u003cp\u003e4.5.4 Machine Learning \u0026amp; Artificial Intelligence 65\u003c\/p\u003e \u003cp\u003e4.6 Optical Quantum Computing 65\u003c\/p\u003e \u003cp\u003e4.7 Experimental Realisation of Quantum Computer 66\u003c\/p\u003e \u003cp\u003e4.7.1 Hetero-Polymers 66\u003c\/p\u003e \u003cp\u003e4.7.2 Ion Traps 67\u003c\/p\u003e \u003cp\u003e4.7.3 Quantum Electrodynamics Cavity 67\u003c\/p\u003e \u003cp\u003e4.7.4 Quantum Dots 67\u003c\/p\u003e \u003cp\u003e4.8 Challenges of Quantum Computing 67\u003c\/p\u003e \u003cp\u003e4.9 Conclusion and Future Scope 68\u003c\/p\u003e \u003cp\u003eReferences 68\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Feature Engineering for Flow-Based IDS 69\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eRahul B. Adhao and Vinod K. Pachghare\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 70\u003c\/p\u003e \u003cp\u003e5.1.1 Intrusion Detection System 71\u003c\/p\u003e \u003cp\u003e5.1.2 IDS Classification 71\u003c\/p\u003e \u003cp\u003e5.2 IP Flows 72\u003c\/p\u003e \u003cp\u003e5.2.1 The Architecture of Flow-Based IDS 73\u003c\/p\u003e \u003cp\u003e5.2.2 Wireless IDS Designed Using Flow-Based Approach 73\u003c\/p\u003e \u003cp\u003e5.2.3 Comparison of Flow- and Packet-Based IDS 74\u003c\/p\u003e \u003cp\u003e5.3 Feature Engineering 75\u003c\/p\u003e \u003cp\u003e5.3.1 Curse of Dimensionality 76\u003c\/p\u003e \u003cp\u003e5.3.2 Feature Selection 78\u003c\/p\u003e \u003cp\u003e5.3.3 Feature Categorization 78\u003c\/p\u003e \u003cp\u003e5.4 Classification of Feature Selection Technique 78\u003c\/p\u003e \u003cp\u003e5.4.1 The Wrapper, Filter, and Embedded Feature Selection 78\u003c\/p\u003e \u003cp\u003e5.4.2 Correlation, Consistency, and PCA-Based Feature Selection 80\u003c\/p\u003e \u003cp\u003e5.4.3 Similarity, Information Theoretical, Sparse Learning, and Statistical-Based Feature Selection 80\u003c\/p\u003e \u003cp\u003e5.4.4 Univariate and Multivariate Feature Selection 81\u003c\/p\u003e \u003cp\u003e5.5 Tools and Library for Feature Selection 82\u003c\/p\u003e \u003cp\u003e5.6 Literature Review on Feature Selection in Flow-Based IDS 82\u003c\/p\u003e \u003cp\u003e5.7 Challenges and Future Scope 86\u003c\/p\u003e \u003cp\u003e5.8 Conclusions 87\u003c\/p\u003e \u003cp\u003eAcknowledgement 87\u003c\/p\u003e \u003cp\u003eReferences 88\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Environmental Aware Thermal (EAT) Routing Protocol for Wireless Sensor Networks 91\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eB. Banuselvasaraswathy and Vimalathithan Rathinasabapathy\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 92\u003c\/p\u003e \u003cp\u003e6.1.1 Single Path Routing Protocol 93\u003c\/p\u003e \u003cp\u003e6.1.2 Multipath Routing Protocol 94\u003c\/p\u003e \u003cp\u003e6.1.3 Environmental Influence on WSN 96\u003c\/p\u003e \u003cp\u003e6.2 Motivation Behind the Work 97\u003c\/p\u003e \u003cp\u003e6.3 Novelty of This Work 98\u003c\/p\u003e \u003cp\u003e6.4 Related Works 99\u003c\/p\u003e \u003cp\u003e6.5 Proposed Environmental Aware Thermal (EAT) Routing Protocol 102\u003c\/p\u003e \u003cp\u003e6.5.1 Sensor Node Environmental Modeling and Analysis 104\u003c\/p\u003e \u003cp\u003e6.5.2 Single Node Environmental Influence Modeling 105\u003c\/p\u003e \u003cp\u003e6.5.3 Multiple Node Modeling 106\u003c\/p\u003e \u003cp\u003e6.5.4 Sensor Node Surrounding Temperature Field 106\u003c\/p\u003e \u003cp\u003e6.5.5 Sensor Node Remaining Energy Calculation 107\u003c\/p\u003e \u003cp\u003e6.5.6 Delay Modeling 107\u003c\/p\u003e \u003cp\u003e6.6 Simulation Parameters 108\u003c\/p\u003e \u003cp\u003e6.7 Results and Discussion 109\u003c\/p\u003e \u003cp\u003e6.7.1 Temperature Influence on Network 109\u003c\/p\u003e \u003cp\u003e6.7.2 Power Consumption 109\u003c\/p\u003e \u003cp\u003e6.7.3 Lifetime Analysis 110\u003c\/p\u003e \u003cp\u003e6.7.4 Delay Analysis 111\u003c\/p\u003e \u003cp\u003e6.8 Conclusion 112\u003c\/p\u003e \u003cp\u003eReferences 112\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 A Comprehensive Study of Intrusion Detection and Prevention Systems 115\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eBhoopesh Singh Bhati, Dikshita, Nitesh Singh Bhati and Garvit Chugh\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 116\u003c\/p\u003e \u003cp\u003e7.1.1 Intrusion and Detection 116\u003c\/p\u003e \u003cp\u003e7.1.2 Some Basic Definitions 116\u003c\/p\u003e \u003cp\u003e7.1.3 Intrusion Detection and Prevention System 117\u003c\/p\u003e \u003cp\u003e7.1.4 Need for IDPS: More Than Ever 118\u003c\/p\u003e \u003cp\u003e7.1.5 Introduction to Alarms 118\u003c\/p\u003e \u003cp\u003e7.1.6 Components of an IDPS 119\u003c\/p\u003e \u003cp\u003e7.2 Configuring IDPS 120\u003c\/p\u003e \u003cp\u003e7.2.1 Network Architecture of IDPS 120\u003c\/p\u003e \u003cp\u003e7.2.2 A Glance at Common Types 121\u003c\/p\u003e \u003cp\u003e7.2.2.1 Network-Based IDS 123\u003c\/p\u003e \u003cp\u003e7.2.2.2 Host-Based IDS 124\u003c\/p\u003e \u003cp\u003e7.2.3 Intrusion Detection Techniques 125\u003c\/p\u003e \u003cp\u003e7.2.3.1 Conventional Techniques 125\u003c\/p\u003e \u003cp\u003e7.2.3.2 Machine Learning-Based and Hybrid Techniques 128\u003c\/p\u003e \u003cp\u003e7.2.4 Three Considerations 131\u003c\/p\u003e \u003cp\u003e7.2.4.1 Location of Sensors 131\u003c\/p\u003e \u003cp\u003e7.2.4.2 Security Capabilities 131\u003c\/p\u003e \u003cp\u003e7.2.4.3 Management Capabilities 133\u003c\/p\u003e \u003cp\u003e7.2.5 Administrators’ Functions 134\u003c\/p\u003e \u003cp\u003e7.2.5.1 Deployment 134\u003c\/p\u003e \u003cp\u003e7.2.5.2 Testing 134\u003c\/p\u003e \u003cp\u003e7.2.5.3 Security Consideration of IDPS 135\u003c\/p\u003e \u003cp\u003e7.2.5.4 Regular Backups and Monitoring 135\u003c\/p\u003e \u003cp\u003e7.2.6 Types of Events Detected 135\u003c\/p\u003e \u003cp\u003e7.2.7 Role of State in Network Security 136\u003c\/p\u003e \u003cp\u003e7.3 Literature Review 137\u003c\/p\u003e \u003cp\u003e7.4 Conclusion 138\u003c\/p\u003e \u003cp\u003eReferences 139\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Hardware Devices Integration With IoT 143\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eSushant Kumar and Saurabh Mukherjee\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 143\u003c\/p\u003e \u003cp\u003e8.2 Literature Review 144\u003c\/p\u003e \u003cp\u003e8.3 Component Description 146\u003c\/p\u003e \u003cp\u003e8.3.1 Arduino Board UNO 146\u003c\/p\u003e \u003cp\u003e8.3.2 Raspberry Pi 147\u003c\/p\u003e \u003cp\u003e8.4 Case Studies 148\u003c\/p\u003e \u003cp\u003e8.4.1 Ultrasonic Sensor 148\u003c\/p\u003e \u003cp\u003e8.4.2 Temperature and Humidity Sensor 150\u003c\/p\u003e \u003cp\u003e8.4.3 Weather Monitoring System Using Raspberry Pi 151\u003c\/p\u003e \u003cp\u003e8.5 Drawbacks of Arduino and Raspberry Pi 153\u003c\/p\u003e \u003cp\u003e8.6 Challenges in IoT 154\u003c\/p\u003e \u003cp\u003e8.6.1 Design Challenges 154\u003c\/p\u003e \u003cp\u003e8.6.2 Security Challenges 155\u003c\/p\u003e \u003cp\u003e8.6.3 Development Challenges 155\u003c\/p\u003e \u003cp\u003e8.7 Conclusion 155\u003c\/p\u003e \u003cp\u003e8.8 Annexures 156\u003c\/p\u003e \u003cp\u003eReferences 157\u003c\/p\u003e \u003cp\u003eAdditional Resources 158\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Depth Analysis On DoS \u0026amp; DDoS Attacks 159\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eGaurav Nayak, Anjana Mishra, Uditman Samal and Brojo Kishore Mishra\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 160\u003c\/p\u003e \u003cp\u003e9.1.1 Objective and Motivation 161\u003c\/p\u003e \u003cp\u003e9.1.2 Symptoms and Manifestations 163\u003c\/p\u003e \u003cp\u003e9.2 Literature Survey 163\u003c\/p\u003e \u003cp\u003e9.3 Timeline of DoS and DDoS Attacks 164\u003c\/p\u003e \u003cp\u003e9.4 Evolution of Denial of Service (DoS) \u0026amp; Distributed Denial of Service (DDoS) 165\u003c\/p\u003e \u003cp\u003e9.5 DDoS Attacks: A Taxonomic Classification 166\u003c\/p\u003e \u003cp\u003e9.5.1 Classification Based on Degree of Automation 166\u003c\/p\u003e \u003cp\u003e9.5.2 Classification Based on Exploited Vulnerability 167\u003c\/p\u003e \u003cp\u003e9.5.3 Classification Based on Rate Dynamics of Attacks 168\u003c\/p\u003e \u003cp\u003e9.5.4 Classification Based on Impact 168\u003c\/p\u003e \u003cp\u003e9.6 Transmission Control Protocol 169\u003c\/p\u003e \u003cp\u003e9.6.1 TCP Three-Way Handshake 169\u003c\/p\u003e \u003cp\u003e9.7 User Datagram Protocol 170\u003c\/p\u003e \u003cp\u003e9.7.1 UDP Header 170\u003c\/p\u003e \u003cp\u003e9.8 Types of DDoS Attacks 170\u003c\/p\u003e \u003cp\u003e9.8.1 TCP SYN Flooding Attack 171\u003c\/p\u003e \u003cp\u003e9.8.2 UDP Flooding Attack 172\u003c\/p\u003e \u003cp\u003e9.8.3 Smurf Attack 172\u003c\/p\u003e \u003cp\u003e9.8.4 Ping of Death Attack 173\u003c\/p\u003e \u003cp\u003e9.8.5 HTTP Flooding Attack 174\u003c\/p\u003e \u003cp\u003e9.9 Impact of DoS\/DDoS on Various Areas 175\u003c\/p\u003e \u003cp\u003e9.9.1 DoS\/DDoS Attacks on VoIP Networks Using SIP 175\u003c\/p\u003e \u003cp\u003e9.9.2 DoS\/DDoS Attacks on VANET 175\u003c\/p\u003e \u003cp\u003e9.9.3 DoS\/DDoS Attacks on Smart Grid System 176\u003c\/p\u003e \u003cp\u003e9.9.4 DoS\/DDoS Attacks in IoT-Based Devices 176\u003c\/p\u003e \u003cp\u003e9.10 Countermeasures to DDoS Attack 177\u003c\/p\u003e \u003cp\u003e9.10.1 Prevent Being Agent\/Secondary Target 177\u003c\/p\u003e \u003cp\u003e9.10.2 Detect and Neutralize Attacker 178\u003c\/p\u003e \u003cp\u003e9.10.3 Potential Threats Detection\/Prevention 178\u003c\/p\u003e \u003cp\u003e9.10.4 DDoS Attacks and How to Avoid Them 178\u003c\/p\u003e \u003cp\u003e9.10.5 Deflect Attack 178\u003c\/p\u003e \u003cp\u003e9.10.6 Post-Attack Forensics 179\u003c\/p\u003e \u003cp\u003e9.11 Conclusion 179\u003c\/p\u003e \u003cp\u003e9.12 Future Scope 180\u003c\/p\u003e \u003cp\u003eReferences 180\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 SQL Injection Attack on Database System 183\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eMohit Kumar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 183\u003c\/p\u003e \u003cp\u003e10.1.1 Types of Vulnerabilities 184\u003c\/p\u003e \u003cp\u003e10.1.2 Types of SQL Injection Attack 185\u003c\/p\u003e \u003cp\u003e10.1.3 Impact of SQL Injection Attack 186\u003c\/p\u003e \u003cp\u003e10.2 Objective and Motivation 186\u003c\/p\u003e \u003cp\u003e10.3 Process of SQL Injection Attack 188\u003c\/p\u003e \u003cp\u003e10.4 Related Work 188\u003c\/p\u003e \u003cp\u003e10.5 Literature Review 189\u003c\/p\u003e \u003cp\u003e10.6 Implementation of the SQL Injection Attack 192\u003c\/p\u003e \u003cp\u003e10.6.1 Access the Database Using the 1=1 SQL Injection Statement 192\u003c\/p\u003e \u003cp\u003e10.6.2 Access the Database Using the ““=’’’’ SQL Injection Statement 193\u003c\/p\u003e \u003cp\u003e10.6.3 Access and Upgrade the Database by Using Batch SQL Injection Statement 194\u003c\/p\u003e \u003cp\u003e10.7 Detection of SQL Injection Attack 196\u003c\/p\u003e \u003cp\u003e10.8 Prevention\/Mitigation from SQL Injection Attack 196\u003c\/p\u003e \u003cp\u003e10.9 Conclusion 197\u003c\/p\u003e \u003cp\u003eReferences 197\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Machine Learning Techniques for Face Authentication System for Security Purposes 199\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eVibhuti Jain, Madhavendra Singh and Jagannath Jayanti\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 200\u003c\/p\u003e \u003cp\u003e11.2 Face Recognition System (FRS) in Security 201\u003c\/p\u003e \u003cp\u003e11.3 Theory 202\u003c\/p\u003e \u003cp\u003e11.3.1 Neural Networks 202\u003c\/p\u003e \u003cp\u003e11.3.2 Convolutional Neural Network (CNN) 204\u003c\/p\u003e \u003cp\u003e11.3.3 K-Nearest Neighbors (KNN) 207\u003c\/p\u003e \u003cp\u003e11.3.4 Support Vector Machine (SVM) 208\u003c\/p\u003e \u003cp\u003e11.3.5 Logistic Regression (LR) 209\u003c\/p\u003e \u003cp\u003e11.3.6 Naive Bayes (NB) 210\u003c\/p\u003e \u003cp\u003e11.3.7 Decision Tree (DT) 211\u003c\/p\u003e \u003cp\u003e11.4 Experimental Methodology 212\u003c\/p\u003e \u003cp\u003e11.4.1 Dataset 212\u003c\/p\u003e \u003cp\u003e11.4.2 Convolutional Neural Network (CNN) 212\u003c\/p\u003e \u003cp\u003e11.4.3 Other Machine Learning Techniques 215\u003c\/p\u003e \u003cp\u003e11.5 Results 218\u003c\/p\u003e \u003cp\u003e11.6 Conclusion 220\u003c\/p\u003e \u003cp\u003eReferences 220\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Estimation of Computation Time for Software-Defined Networking-Based Data Traffic Offloading System in Heterogeneous Network 223\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eShashila S. Abayagunawardhana, Malka N. Halgamuge and Charitha Subhashi Jayasekara\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 224\u003c\/p\u003e \u003cp\u003e12.1.1 Motivation 225\u003c\/p\u003e \u003cp\u003e12.1.2 Objective 228\u003c\/p\u003e \u003cp\u003e12.1.3 The Main Contributions of This Chapter 228\u003c\/p\u003e \u003cp\u003e12.2 Analysis of SDN-TOS Mechanism 229\u003c\/p\u003e \u003cp\u003e12.2.1 Key Components of SDN-TOS 229\u003c\/p\u003e \u003cp\u003e12.2.2 LTE\/Wi-Fi in a Heterogeneous Network (HetNet) 229\u003c\/p\u003e \u003cp\u003e12.2.3 Centralized SDN Controller 229\u003c\/p\u003e \u003cp\u003e12.2.4 Key Design Considerations of SDN-TOS 230\u003c\/p\u003e \u003cp\u003e12.2.4.1 The System Architecture 230\u003c\/p\u003e \u003cp\u003e12.2.4.2 Mininet Wi-Fi Emulated Networks 230\u003c\/p\u003e \u003cp\u003e12.2.4.3 Software-Defined Networking Controller 231\u003c\/p\u003e \u003cp\u003e12.3 Materials and Methods 232\u003c\/p\u003e \u003cp\u003e12.3.1 Estimating Time Consumption for Mininet Wi-Fi Emulator 232\u003c\/p\u003e \u003cp\u003e12.3.1.1 Total Time Consumption for Offloading the Data Traffic by Service Provider 233\u003c\/p\u003e \u003cp\u003e12.3.1.2 Total Time Consumption of Mininet Wi-Fi Emulator (Time Consumption for Both LTE and Wi-Fi Network) 236\u003c\/p\u003e \u003cp\u003e12.3.2 Estimating Time Consumption for SDN Controller 237\u003c\/p\u003e \u003cp\u003e12.3.2.1 Total Response Time for Sub-Controller 237\u003c\/p\u003e \u003cp\u003e12.3.2.2 Total Response Time for The Total Process of Centralized SDN Controller 238\u003c\/p\u003e \u003cp\u003e12.3.3 Estimating Total Time Consumption for SDN-Based Traffic Offloading System (sdn-tos) 239\u003c\/p\u003e \u003cp\u003e12.4 Simulation Results 240\u003c\/p\u003e \u003cp\u003e12.4.1 Effect of Computational Data Traffic θ\u003csub\u003eI \u003c\/sub\u003eon Total Response Time (T\u003csub\u003eA\u003c\/sub\u003e)\/Service Provider A and CSP Approach 242\u003c\/p\u003e \u003cp\u003e12.4.2 Effect of Computational Data Traffic θ\u003csub\u003eI\u003c\/sub\u003e on Total Response Time (T\u003csub\u003eA\u003c\/sub\u003e) for Different Service Providers\/Service Provider A and Service Provider B 243\u003c\/p\u003e \u003cp\u003e12.5 Discussion 244\u003c\/p\u003e \u003cp\u003e12.6 Conclusion 246\u003c\/p\u003e \u003cp\u003eReferences 247\u003c\/p\u003e \u003cp\u003eAbout the Editors 253\u003c\/p\u003e \u003cp\u003eIndex 255\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":53186831548759,"sku":"9781119777144","price":153.9,"currency_code":"GBP","in_stock":true}],"url":"https:\/\/bookcurl.com\/products\/wireless-communication-security-9781119777144","provider":"Book Curl","version":"1.0","type":"link"}