Preface xv Acknowledgment xix 1 IoT in 5th Generation Wireless Communication 1Sandeep Mathur and Ankita Arora 1.1 Introduction 2 1.2 Internet of Things With Wireless Communication 3 1.2.1 Modules Used for the Communication Protocol 5 1.2.1.1 Wi-Fi Modules for the Connectivity in Less Range 5 1.2.1.2 Wi-Fi Modules for Connectivity in Long Range 6 1.2.2 The Relation Between the Different Internet of Things Protocol 7 1.2.2.1 Effect of Distinction Among Node and Transmission Power 8 1.3 Internet of Things in 5G Mobile Computing 9 1.3.1 Practical Aspects of Integrating the Internet of Things With 5G Technologies 10 1.3.2 The Working of the 5G for the People and Its Generalization 14 1.3.3 5G Deployment Snapshot 15 1.3.4 Architecture of Internet of Things With 5G 16 1.4 Internet of Things and 5G Integration With Artificial Intelligence 16 1.4.1 Opportunity in the Future 20 1.4.2 Challenges Arising 21 1.4.2.1 The Management of IoT Devices Might Become Additional Efficient 21 1.4.2.2 5G Protocol Flaws Might Cause Security Flaws 22 1.4.2.3 5G Could Amend the Styles of Attacks Folks With IoT Devices 22 1.5 A Genetic Algorithm for 5G Technologies With Internet of Things 23 1.5.1 System Model 24 1.5.2 The Planned Algorithm 24 1.6 Conclusion & Future Work 27 References 27 2 Internet of Things-Based Service Discovery for the 5G-VANET Milieu 31P. Dharanyadevi, M. Julie Therese and K. Venkatalakshmi 2.1 VANET 32 2.2 5G 33 2.2.1 Why is 5G Used in VANET? 34 2.3 Service Discovery 34 2.4 Service Discovery in 5G-VANET Milieu 36 2.4.1 Service Discovery Methods 36 2.4.2 A Framework of Service Discovery in the 5G-VANET Milieu 36 2.5 Service Discovery Architecture for 5G-VANET Milieu 39 2.5.1 Vehicle User Side Discovery 39 2.5.2 Service Provider Side Discovery 39 2.5.3 Service Instance 39 2.5.4 Service Registry 40 2.6 Performance Evaluation Metrics for Service Discovery Mechanism in the 5G-VANET Milieu 41 2.7 The Advantage of Service Discovery in the 5G-VANET Milieu 41 2.8 The Disadvantage of Service Discovery in the 5G-VANET Milieu 42 2.9 Future Enhancement and Research Directions 42 2.10 Conclusions 43 References 43 3 IoT-Based Intelligent Transportation System for Safety 47Suthanthira Vanitha, N., Radhika, K., Maheshwari, M., Suresh, P. and Meenakshi, T. 3.1 Introduction 48 3.2 Elements of ITS 48 3.3 Role of ITS in Safety 50 3.4 Sensor Technologies 50 3.4.1 Implanted Vehicle Sensor Applications 52 3.5 Classification of Vehicle Communication Systems 53 3.5.1 V2V Communication Access Technologies 55 3.6 IoT in Vehicles 56 3.7 Embedded Controllers 58 3.8 ITS Challenges and Opportunities 61 References 62 4 Cloud and IoT-Based Vehicular Ad Hoc Networks (VANET) 67Sunita Sunil Shinde, Ravi M.Yadahalli and Ramesh Shabadkar 4.1 Introduction to VANET 68 4.2 Vehicle-Vehicle Communication (V2V) 68 4.3 Vehicle–Infrastructure Communication (V2I) 68 4.4 Vehicle–Broadband Cloud Communication (V2B) 68 4.5 Characteristics of VANET 71 4.6 Prime Applications 74 4.7 State-of-the-Art Technologies 74 4.7.1 DSRC/WAVE 74 4.7.2 4G-LTE 76 4.8 VANET Challenges 76 4.9 Video Streaming Broadcasting 78 4.9.1 Video Streaming Mechanisms 79 4.9.2 Video Streaming Classes Over VANET 80 References 80 5 Interleavers-Centric Conflict Management Solution for 5G Vehicular and Cellular-IoT Communications 83Manish Yadav and Pramod Kumar Singhal 5.1 Introduction 84 5.2 Background 85 5.2.1 Vehicular Communication 85 5.2.2 IoT Communication 87 5.3 Device Identity Conflict Issue 89 5.4 Related Work 89 5.5 Interleavers-Centric Conflict Management (ICM) 90 5.5.1 The Essence of Conflict Resolution 90 5.5.2 The Motivation 91 5.5.3 ICM: An Approach for Conflict Resolution 91 5.5.3.1 Advantages of ICM 92 5.5.3.2 Recommended Interleavers for ICM 93 5.6 Signaling Procedures for Enabling ICM 93 5.6.1 Signaling Between CIoT UE and Cellular or CIoT RAN 93 5.6.2 Signaling Trilogy for CIoT Communications 95 5.6.3 Signaling for V2I Communications 96 5.6.4 Signaling for gNB-Initiated Software Upgrade 97 5.7 Conclusion 98 References 99 6 Modeling of VANET for Future Generation Transportation System Through Edge/Fog/Cloud Computing Powered by 6G 105Suresh Kumar, K., Radha Mani, A.S., Sundaresan, S. and Ananth Kumar, T. 6.1 Introduction 106 6.2 Related Works 109 6.3 Proposed System Overview 111 6.3.1 Driver Monitoring System 111 6.3.2 Edge/Fog/Cloud Computing 113 6.3.3 Software Defined Networking (SDN) Along With VANET 113 6.3.4 Integration of VANET With 5G Networks 114 6.3.5 IoT with 6G Networks 114 6.4 Modeling of Proposed System 115 6.5 Results and Discussion 118 6.6 Conclusion 122 References 122 7 Integrating IoT and Cloud Computing for Wireless Sensor Network Applications 125M. Julie Therese, P. Dharanyadevi and K. Harshithaa 7.1 Introduction 125 7.1.1 IoT Architecture 126 7.1.2 Cloud Front End and Back End Architecture 128 7.1.3 Wireless Sensor Network 129 7.1.4 IoT Cloud and WSN Architecture 132 7.1.5 Research Motive 132 7.2 Challenges and Opportunities 133 7.2.1 Challenges IoT Cloud Faces 133 7.2.2 Opportunities IoT Cloud Offers 134 7.3 Case Study 134 7.3.1 Case 1 Improved Pollution Monitoring System for Automobiles Using Cloud-Based Wireless Sensor Networks 137 7.3.2 Case 2 Hybrid Electric Vehicle 138 7.4 Conclusion 139 References 140 8 Comparative Study on Security and Privacy Issues in VANETs 145B. Tarakeswara Rao, R.S.M. Lakshmi Patibandla and V. Lakshman Narayana 8.1 Introduction 146 8.2 Characteristics of VANETs 149 8.2.1 VANETs Features 149 8.2.2 Challenges in VANET 150 8.2.3 Mitigating Features 151 8.3 Literature Survey 152 8.4 Authentication Requirements in VANETs Communications 153 8.4.1 Security Model for VANETs’ Communication 154 8.4.2 VANET Security Services 155 8.4.3 Security Recommendation 156 8.4.4 Comparative Analysis 157 8.5 Conclusion 160 References 160 9 Software Defined Network Horizons and Embracing its Security Challenges: From Theory to Practice 163Sugandhi Midha, Khushboo Tripathi and M.K. Sharma 9.1 Introduction 164 9.2 Background and Literature Survey 166 9.3 Objective and Scope of the Chapter 169 9.4 SDN Architecture Overviews 171 9.5 Open Flow 174 9.6 SDN Security Architecture 178 9.7 Techniques to Mitigate SDN Security Threats 180 9.7.1 Performance Metrics 186 9.7.2 Performance Tests 186 9.7.3 Data Hiding-Based Geo Location Authentication Protocol 188 9.7.4 Identity Access Management (IAM) Extended Policies 191 9.7.5 Extended Identity-Based Cryptography 192 9.8 Future Research Directions 194 9.9 Conclusions 195 References 196 10 Bio-Inspired Routing in VANET 199Alankrita Aggarwal, Shivani Gaba, Shally Nagpal and Bhavanshu Vig 10.1 Introduction 199 10.2 Geography-Based Routing 202 10.3 Topology-Based Routing 203 10.3.1 Drawbacks 203 10.3.2 Literature Review 204 10.4 Biological Computing 208 10.5 Elephant Herding Optimization Algorithm 209 10.6 Research Methodology 211 10.6.1 Clan Operator 211 10.6.2 Separating Operator 212 10.6.3 Simulation Results 213 10.7 Conclusion 216 References 216 11 Distributed Key Generation for Secure Communications Between Different Actors in Service Oriented Highly Dense VANET 221Deena Nath Gupta and Rajendra Kumar 11.1 Introduction 222 11.2 Hierarchical Clustering 224 11.3 Layer-Wise Key Generation 225 11.4 Implementation 226 11.5 Randomness Test 227 11.6 Brute Force Attack Analysis 228 11.7 Conclusion 229 References 230 12 Challenges, Benefits and Issues: Future Emerging VANETs and Cloud Approaches 233Bhanu Chander 12.1 Introduction 234 12.2 VANET Background 236 12.3 VANET Communication Standards 238 12.4 VANET Applications 239 12.4.1 Safety Applications 239 12.4.2 Non-Safety Applications 240 12.5 VANET Sensing Technologies 242 12.5.1 Sensing Technology 242 12.5.2 Positioning Technologies 243 12.5.3 Vision Technologies 244 12.5.4 Vehicular Networks 244 12.6 Trust in Ad Hoc Networks 244 12.6.1 Cryptographic Approaches 245 12.6.2 Recommendation-Based Approaches 245 12.6.3 Fuzzy Logic-Based Approaches 245 12.6.4 Game Theory-Based Approaches 246 12.6.5 Infrastructure-Based Approaches 246 12.6.6 Road- and Consensus-Based Advances 246 12.6.7 Blockchain-Based Approaches 246 12.6.8 Machine Learning Base Trust Management in Vehicular Networks 247 12.6.9 Trust in Cellular-Based (5G) VANET 247 12.6.10 Software-Defined VANET (SDVANET) 247 12.6.11 Trust in Vehicular Social Networks (VSN) 248 12.6.12 Future Challenges in VANET Trust Technique 248 12.7 Software-Defined Network (SDN) in VANET 249 12.7.1 Literature Work on SDVN 250 12.7.2 Advantages 251 12.7.3 Challenge 252 12.8 Clustering Approaches: Issues 253 12.9 Up-and-Coming Technologies for Potential VANET 254 12.9.1 Edge Cloud Computing 254 12.9.1.1 Fog Computing 254 12.9.1.2 Mobile Edge Computing (MEC) 255 12.9.1.3 Cloudlets 255 12.10 Challenges, Open Issues and Future Work of VANETs 256 12.10.1 Challenges of VANET 256 12.10.2 Open Issues in VANET Development 257 12.10.3 Future Research Work 258 12.11 Conclusion 259 References 260 13 Role of Machine Learning for Ad Hoc Networks 269Shivani Gaba, Alankrita Aggarwal and Shally Nagpal 13.1 Introduction 270 13.2 Literature Survey 273 13.3 Machine Learning Computing 277 13.3.1 Reinforcement Learning 277 13.3.2 Q-Learning/Transfer Learning 278 13.3.3 Fuzzy Logic 278 13.3.4 Logistic Regression 279 13.4 Methodology 280 13.4.1 Rate Estimation Algorithm 280 13.4.2 Route Selection Algorithm 281 13.4.3 Algorithm for Congestion Free Route (Congestion Algorithm) 283 13.5 Simulation Results 284 13.6 Conclusions 287 References 287 14 Smart Automotive System With CV2X-Based Ad Hoc Communication 293Rabindranath Bera 14.1 Introduction 294 14.2 Realization of Smart Vehicle 300 14.3 Analysis of NXP Smart Vehicle Architecture 303 14.4 Smart Vehicle Proof of Concept (POC) 308 14.4.1 ECE, SMIT Adaptation of 3GPP 5G Standard for 5G-Enabled Smart Vehicle 308 14.4.2 Emulation of Smart Vehicle at ECE, SMIT LAB 308 14.4.2.1 Emulation of V2I (Vehicle to Infrastructure) 5G URLLC Communication Between i) One Intelligent Roadside Unit (RSU), ii) One Smart Vehicle (SV) 308 14.4.2.2 Emulation of V2V (Vehicle to Vehicle) 5G URLLC Communication Between Two Smart Vehicles i) One Smart Vehicle (SV1), ii) Another Smart Vehicle (SV2) 314 14.5 Smart Vehicle Trials 315 14.6 System Comparison 321 14.7 Summary and Conclusion 321 Acknowledgement 321 References 321 15 QoS Enhancement in MANET 325Jayson K. Jayabarathan, S. Robinson and A. Sivanantha Raja 15.1 Introduction 325 15.2 Priority Aware Mechanism (PAM) 327 15.3 Power Aware Mechanism 329 15.4 Hybrid Mechanism 330 15.5 Simulation Results and Discussion 332 15.6 Performance Comparison 339 15.7 Conclusion 342 References 346 16 Simulating a Smart Car Routing Model (Implementing MFR Framework) in Smart Cities 349Nada M. Alhakkak 16.1 Introduction 350 16.2 Background 350 16.3 Literature Review 352 16.4 Methodology 355 16.4.1 System Framework 355 16.5 Discussion and a Future Direction 357 16.5.1 Case Study 358 16.5.2 Fog-Simulator 361 16.5.3 MOA-Simulator 361 16.5.4 CloudSim-Simulator 361 16.6 Conclusions 364 References 365 17 Potentials of Network-Based Unmanned Aerial Vehicles 369P. K. Garg 17.1 Introduction 370 17.2 Applications of UAVs 371 17.3 Advantages of UAVs 375 17.4 UAV Communication System 376 17.5 Types of Communication 378 17.6 Wireless Sensor Network (WSN) System 380 17.7 The Swarm Approach 383 17.7.1 Infrastructure-Based Swarm Architecture 384 17.7.2 FANET-Based Swarm Architecture 385 17.8 Market Potential of UAVs 391 17.9 Conclusion 392 References 393 Index 399