Cover -- Half-Title Page -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Acknowledgment -- 1 IoT in 5th Generation Wireless Communication -- 1.1 Introduction -- 1.2 Internet of Things With Wireless Communication -- 1.2.1 Modules Used for the Communication Protocol -- 1.2.1.1 Wi-Fi Modules for the Connectivity in Less Range -- 1.2.1.2 Wi-Fi Modules for Connectivity in Long Range -- 1.2.2 The Relation Between the Different Internet of Things Protocol -- 1.2.2.1 Effect of Distinction Among Node and Transmission Power -- 1.3 Internet of Things in 5G Mobile Computing -- 1.3.1 Practical Aspects of Integrating the Internet of Things With 5G Technologies -- 1.3.2 The Working of the 5G for the People and Its Generalization -- 1.3.3 5G Deployment Snapshot -- 1.3.4 Architecture of Internet of Things With 5G -- 1.4 Internet of Things and 5G Integration With Artificial Intelligence -- 1.4.1 Opportunity in the Future -- 1.4.2 Challenges Arising -- 1.4.2.1 The Management of IoT Devices Might Become Additional Efficient -- 1.4.2.2 5G Protocol Flaws Might Cause Security Flaws -- 1.4.2.3 5G Could Amend the Styles of Attacks Folks With IoT Devices -- 1.5 A Genetic Algorithm for 5G Technologies With Internet of Things -- 1.5.1 System Model -- 1.5.2 The Planned Algorithm -- 1.6 Conclusion & -- Future Work -- References -- 2 Internet of Things-Based Service Discovery for the 5G-VANET Milieu -- 2.1 VANET -- 2.2 5G -- 2.2.1 Why is 5G Used in VANET? -- 2.3 Service Discovery -- 2.4 Service Discovery in 5G-VANET Milieu -- 2.4.1 Service Discovery Methods -- 2.4.2 A Framework of Service Discovery in the 5G-VANET Milieu -- 2.5 Service Discovery Architecture for 5G-VANET Milieu -- 2.5.1 Vehicle User Side Discovery -- 2.5.2 Service Provider Side Discovery -- 2.5.3 Service Instance -- 2.5.4 Service Registry.

2.6 Performance Evaluation Metrics for Service Discovery Mechanism in the 5G-VANET Milieu -- 2.7 The Advantage of Service Discovery in the 5G-VANET Milieu -- 2.8 The Disadvantage of Service Discovery in the 5G-VANET Milieu -- 2.9 Future Enhancement and Research Directions -- 2.10 Conclusions -- References -- 3 IoT-Based Intelligent Transportation System for Safety -- 3.1 Introduction -- 3.2 Elements of ITS -- 3.3 Role of ITS in Safety -- 3.4 Sensor Technologies -- 3.4.1 Implanted Vehicle Sensor Applications -- 3.5 Classification of Vehicle Communication Systems -- 3.5.1 V2V Communication Access Technologies -- 3.6 IoT in Vehicles -- 3.7 Embedded Controllers -- 3.8 ITS Challenges and Opportunities -- References -- 4 Cloud and IoT-Based Vehicular Ad Hoc Networks (VANET) -- 4.1 Introduction to VANET -- 4.2 Vehicle-Vehicle Communication (V2V) -- 4.3 Vehicle-Infrastructure Communication (V2I) -- 4.4 Vehicle-Broadband Cloud Communication (V2B) -- 4.5 Characteristics of VANET -- 4.6 Prime Applications -- 4.7 State-of-the-Art Technologies -- 4.7.1 DSRC/WAVE -- 4.7.2 4G-LTE -- 4.8 VANET Challenges -- 4.9 Video Streaming Broadcasting -- 4.9.1 Video Streaming Mechanisms -- 4.9.2 Video Streaming Classes Over VANET -- References -- 5 Interleavers-Centric Conflict Management Solution for 5G Vehicular and Cellular-IoT Communications -- 5.1 Introduction -- 5.2 Background -- 5.2.1 Vehicular Communication -- 5.2.2 IoT Communication -- 5.3 Device Identity Conflict Issue -- 5.4 Related Work -- 5.5 Interleavers-Centric Conflict Management (ICM) -- 5.5.1 The Essence of Conflict Resolution -- 5.5.2 The Motivation -- 5.5.3 ICM: An Approach for Conflict Resolution -- 5.5.3.1 Advantages of ICM -- 5.5.3.2 Recommended Interleavers for ICM -- 5.6 Signaling Procedures for Enabling ICM -- 5.6.1 Signaling Between CIoT UE and Cellular or CIoT RAN.

5.6.2 Signaling Trilogy for CIoT Communications -- 5.6.3 Signaling for V2I Communications -- 5.6.4 Signaling for gNB-Initiated Software Upgrade -- 5.7 Conclusion -- References -- 6 Modeling of VANET for Future Generation Transportation System Through Edge/Fog/Cloud Computing Powered by 6G -- 6.1 Introduction -- 6.2 Related Works -- 6.3 Proposed System Overview -- 6.3.1 Driver Monitoring System -- 6.3.2 Edge/Fog/Cloud Computing -- 6.3.3 Software Defined Networking (SDN) Along With VANET -- 6.3.4 Integration of VANET With 5G Networks -- 6.3.5 IoT with 6G Networks -- 6.4 Modeling of Proposed System -- 6.5 Results and Discussion -- 6.6 Conclusion -- References -- 7 Integrating IoT and Cloud Computing for Wireless Sensor Network Applications -- 7.1 Introduction -- 7.1.1 IoT Architecture -- 7.1.2 Cloud Front End and Back End Architecture -- 7.1.3 Wireless Sensor Network -- 7.1.4 IoT Cloud and WSN Architecture -- 7.1.5 Research Motive -- 7.2 Challenges and Opportunities -- 7.2.1 Challenges IoT Cloud Faces -- 7.2.2 Opportunities IoT Cloud Offers -- 7.3 Case Study -- 7.3.1 Case 1 Improved Pollution Monitoring System for Automobiles Using Cloud-Based Wireless Sensor Networks -- 7.3.2 Case 2 Hybrid Electric Vehicle -- 7.4 Conclusion -- References -- 8 Comparative Study on Security and Privacy Issues in VANETs -- 8.1 Introduction -- 8.2 Characteristics of VANETs -- 8.2.1 VANETs Features -- 8.2.2 Challenges in VANET -- 8.2.3 Mitigating Features -- 8.3 Literature Survey -- 8.4 Authentication Requirements in VANETs Communications -- 8.4.1 Security Model for VANETs' Communication -- 8.4.2 VANET Security Services -- 8.4.3 Security Recommendation -- 8.4.4 Comparative Analysis -- 8.5 Conclusion -- References -- 9 Software Defined Network Horizons and Embracing its Security Challenges: From Theory to Practice -- 9.1 Introduction -- 9.2 Background and Literature Survey.

9.3 Objective and Scope of the Chapter -- 9.4 SDN Architecture Overviews -- 9.5 Open Flow -- 9.6 SDN Security Architecture -- 9.7 Techniques to Mitigate SDN Security Threats -- 9.7.1 Performance Metrics -- 9.7.2 Performance Tests -- 9.7.3 Data Hiding-Based Geo Location Authentication Protocol -- 9.7.4 Identity Access Management (IAM) Extended Policies -- 9.7.5 Extended Identity-Based Cryptography -- 9.8 Future Research Directions -- 9.9 Conclusions -- References -- 10 Bio-Inspired Routing in VANET -- 10.1 Introduction -- 10.2 Geography-Based Routing -- 10.3 Topology-Based Routing -- 10.3.1 Drawbacks -- 10.3.2 Literature Review -- 10.4 Biological Computing -- 10.5 Elephant Herding Optimization Algorithm -- 10.6 Research Methodology -- 10.6.1 Clan Operator -- 10.6.2 Separating Operator -- 10.6.3 Simulation Results -- 10.7 Conclusion -- References -- 11 Distributed Key Generation for Secure Communications Between Different Actors in Service Oriented Highly Dense VANET -- 11.1 Introduction -- 11.2 Hierarchical Clustering -- 11.3 Layer-Wise Key Generation -- 11.4 Implementation -- 11.5 Randomness Test -- 11.6 Brute Force Attack Analysis -- 11.7 Conclusion -- References -- 12 Challenges, Benefits and Issues: Future Emerging VANETs and Cloud Approaches -- 12.1 Introduction -- 12.2 VANET Background -- 12.3 VANET Communication Standards -- 12.4 VANET Applications -- 12.4.1 Safety Applications -- 12.4.2 Non-Safety Applications -- 12.5 VANET Sensing Technologies -- 12.5.1 Sensing Technology -- 12.5.2 Positioning Technologies -- 12.5.3 Vision Technologies -- 12.5.4 Vehicular Networks -- 12.6 Trust in Ad Hoc Networks -- 12.6.1 Cryptographic Approaches -- 12.6.2 Recommendation-Based Approaches -- 12.6.3 Fuzzy Logic-Based Approaches -- 12.6.4 Game Theory-Based Approaches -- 12.6.5 Infrastructure-Based Approaches -- 12.6.6 Road- and Consensus-Based Advances.

12.6.7 Blockchain-Based Approaches -- 12.6.8 Machine Learning Base Trust Management in Vehicular Networks -- 12.6.9 Trust in Cellular-Based (5G) VANET -- 12.6.10 Software-Defined VANET (SDVANET) -- 12.6.11 Trust in Vehicular Social Networks (VSN) -- 12.6.12 Future Challenges in VANET Trust Technique -- 12.7 Software-Defined Network (SDN) in VANET -- 12.7.1 Literature Work on SDVN -- 12.7.2 Advantages -- 12.7.3 Challenge -- 12.8 Clustering Approaches: Issues -- 12.9 Up-and-Coming Technologies for Potential VANET -- 12.9.1 Edge Cloud Computing -- 12.9.1.1 Fog Computing -- 12.9.1.2 Mobile Edge Computing (MEC) -- 12.9.1.3 Cloudlets -- 12.10 Challenges, Open Issues and Future Work of VANETs -- 12.10.1 Challenges of VANET -- 12.10.2 Open Issues in VANET Development -- 12.10.3 Future Research Work -- 12.11 Conclusion -- References -- 13 Role of Machine Learning for Ad Hoc Networks -- 13.1 Introduction -- 13.2 Literature Survey -- 13.3 Machine Learning Computing -- 13.3.1 Reinforcement Learning -- 13.3.2 Q-Learning/Transfer Learning -- 13.3.3 Fuzzy Logic -- 13.3.4 Logistic Regression -- 13.4 Methodology -- 13.4.1 Rate Estimation Algorithm -- 13.4.2 Route Selection Algorithm -- 13.4.3 Algorithm for Congestion Free Route (Congestion Algorithm) -- 13.5 Simulation Results -- 13.6 Conclusions -- References -- 14 Smart Automotive System With CV2X-Based Ad Hoc Communication -- 14.1 Introduction -- 14.2 Realization of Smart Vehicle -- 14.3 Analysis of NXP Smart Vehicle Architecture -- 14.4 Smart Vehicle Proof of Concept (POC) -- 14.4.1 ECE, SMIT Adaptation of 3GPP 5G Standard for 5G-Enabled Smart Vehicle -- 14.4.2 Emulation of Smart Vehicle at ECE, SMIT LAB -- 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).