Cloud and IoT-Based Vehicular Ad Hoc Networks

Gurinder Singh, Group Vice Chancellor - Amity Universities, Director General, Amity Group of Institutions and Vice Chairman, Global Foundation for Learning Excellence & Director General Amity International Business School, has an extensive experience of more than 26 years in Institutional Building, Teaching, Consultancy, Research & Industry. A renowned scholar & academician in the area of International Business, he holds a prestigious Doctorate in the area along with a Post Graduate degree from Indian Institute of Foreign Trade.Vishal Jain is an associate professor at Bharati Vidyapeeth's Institute of Computer Applications and Management (BVICAM), New Delhi, India. He has more than 350 research citation indices with Google Scholar (h-index score 9 and i-10 index 9). He has authored more than 70 research papers in reputed conferences and journals indexed by Web of Science and Scopus, as well as authored and edited more than 10 books with various international publishers. His research areas include information retrieval, semantic web, ontology engineering, data mining, adhoc networks, and sensor networks.Jyotir Moy Chatterjee is working as an Assistant Professor (IT) at Lord Buddha Education Foundation, Kathmandu, Nepal. He has completed M.Tech in Computer Science & Engineering from Kalinga Institute of Industrial Technology, Bhubaneswar, India.Loveleen Gaur, Professor and Program Director (MBA Business Intelligence and Data Analytics), Amity International Business School, Amity University, Noida. Loveleen Gaur is an established Author, Researcher, Teacher, Educator, consultant, Administrator and Program leader. She has published about 12 books and more than 80 research papers in high quality impact journals.

• Preface xvAcknowledgment xix1 IoT in 5th Generation Wireless Communication 1Sandeep Mathur and Ankita Arora1.1 Introduction 21.2 Internet of Things With Wireless Communication 31.2.1 Modules Used for the Communication Protocol 51.2.1.1 Wi-Fi Modules for the Connectivity in Less Range 51.2.1.2 Wi-Fi Modules for Connectivity in Long Range 61.2.2 The Relation Between the Different Internet of Things Protocol 71.2.2.1 Effect of Distinction Among Node and Transmission Power 81.3 Internet of Things in 5G Mobile Computing 91.3.1 Practical Aspects of Integrating the Internet of Things With 5G Technologies 101.3.2 The Working of the 5G for the People and Its Generalization 141.3.3 5G Deployment Snapshot 151.3.4 Architecture of Internet of Things With 5G 161.4 Internet of Things and 5G Integration With Artificial Intelligence 161.4.1 Opportunity in the Future 201.4.2 Challenges Arising 211.4.2.1 The Management of IoT Devices Might Become Additional Efficient 211.4.2.2 5G Protocol Flaws Might Cause Security Flaws 221.4.2.3 5G Could Amend the Styles of Attacks Folks With IoT Devices 221.5 A Genetic Algorithm for 5G Technologies With Internet of Things 231.5.1 System Model 241.5.2 The Planned Algorithm 241.6 Conclusion & Future Work 27References 272 Internet of Things-Based Service Discovery for the 5G-VANET Milieu 31P. Dharanyadevi, M. Julie Therese and K. Venkatalakshmi2.1 VANET 322.2 5G 332.2.1 Why is 5G Used in VANET? 342.3 Service Discovery 342.4 Service Discovery in 5G-VANET Milieu 362.4.1 Service Discovery Methods 362.4.2 A Framework of Service Discovery in the 5G-VANET Milieu 362.5 Service Discovery Architecture for 5G-VANET Milieu 392.5.1 Vehicle User Side Discovery 392.5.2 Service Provider Side Discovery 392.5.3 Service Instance 392.5.4 Service Registry 402.6 Performance Evaluation Metrics for Service Discovery Mechanism in the 5G-VANET Milieu 412.7 The Advantage of Service Discovery in the 5G-VANET Milieu 412.8 The Disadvantage of Service Discovery in the 5G-VANET Milieu 422.9 Future Enhancement and Research Directions 422.10 Conclusions 43References 433 IoT-Based Intelligent Transportation System for Safety 47Suthanthira Vanitha, N., Radhika, K., Maheshwari, M., Suresh, P. and Meenakshi, T.3.1 Introduction 483.2 Elements of ITS 483.3 Role of ITS in Safety 503.4 Sensor Technologies 503.4.1 Implanted Vehicle Sensor Applications 523.5 Classification of Vehicle Communication Systems 533.5.1 V2V Communication Access Technologies 553.6 IoT in Vehicles 563.7 Embedded Controllers 583.8 ITS Challenges and Opportunities 61References 624 Cloud and IoT-Based Vehicular Ad Hoc Networks (VANET) 67Sunita Sunil Shinde, Ravi M.Yadahalli and Ramesh Shabadkar4.1 Introduction to VANET 684.2 Vehicle-Vehicle Communication (V2V) 684.3 Vehicle–Infrastructure Communication (V2I) 684.4 Vehicle–Broadband Cloud Communication (V2B) 684.5 Characteristics of VANET 714.6 Prime Applications 744.7 State-of-the-Art Technologies 744.7.1 DSRC/WAVE 744.7.2 4G-LTE 764.8 VANET Challenges 764.9 Video Streaming Broadcasting 784.9.1 Video Streaming Mechanisms 794.9.2 Video Streaming Classes Over VANET 80References 805 Interleavers-Centric Conflict Management Solution for 5G Vehicular and Cellular-IoT Communications 83Manish Yadav and Pramod Kumar Singhal5.1 Introduction 845.2 Background 855.2.1 Vehicular Communication 855.2.2 IoT Communication 875.3 Device Identity Conflict Issue 895.4 Related Work 895.5 Interleavers-Centric Conflict Management (ICM) 905.5.1 The Essence of Conflict Resolution 905.5.2 The Motivation 915.5.3 ICM: An Approach for Conflict Resolution 915.5.3.1 Advantages of ICM 925.5.3.2 Recommended Interleavers for ICM 935.6 Signaling Procedures for Enabling ICM 935.6.1 Signaling Between CIoT UE and Cellular or CIoT RAN 935.6.2 Signaling Trilogy for CIoT Communications 955.6.3 Signaling for V2I Communications 965.6.4 Signaling for gNB-Initiated Software Upgrade 975.7 Conclusion 98References 996 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 1066.2 Related Works 1096.3 Proposed System Overview 1116.3.1 Driver Monitoring System 1116.3.2 Edge/Fog/Cloud Computing 1136.3.3 Software Defined Networking (SDN) Along With VANET 1136.3.4 Integration of VANET With 5G Networks 1146.3.5 IoT with 6G Networks 1146.4 Modeling of Proposed System 1156.5 Results and Discussion 1186.6 Conclusion 122References 1227 Integrating IoT and Cloud Computing for Wireless Sensor Network Applications 125M. Julie Therese, P. Dharanyadevi and K. Harshithaa7.1 Introduction 1257.1.1 IoT Architecture 1267.1.2 Cloud Front End and Back End Architecture 1287.1.3 Wireless Sensor Network 1297.1.4 IoT Cloud and WSN Architecture 1327.1.5 Research Motive 1327.2 Challenges and Opportunities 1337.2.1 Challenges IoT Cloud Faces 1337.2.2 Opportunities IoT Cloud Offers 1347.3 Case Study 1347.3.1 Case 1 Improved Pollution Monitoring System for Automobiles Using Cloud-Based Wireless Sensor Networks 1377.3.2 Case 2 Hybrid Electric Vehicle 1387.4 Conclusion 139References 1408 Comparative Study on Security and Privacy Issues in VANETs 145B. Tarakeswara Rao, R.S.M. Lakshmi Patibandla and V. Lakshman Narayana8.1 Introduction 1468.2 Characteristics of VANETs 1498.2.1 VANETs Features 1498.2.2 Challenges in VANET 1508.2.3 Mitigating Features 1518.3 Literature Survey 1528.4 Authentication Requirements in VANETs Communications 1538.4.1 Security Model for VANETs’ Communication 1548.4.2 VANET Security Services 1558.4.3 Security Recommendation 1568.4.4 Comparative Analysis 1578.5 Conclusion 160References 1609 Software Defined Network Horizons and Embracing its Security Challenges: From Theory to Practice 163Sugandhi Midha, Khushboo Tripathi and M.K. Sharma9.1 Introduction 1649.2 Background and Literature Survey 1669.3 Objective and Scope of the Chapter 1699.4 SDN Architecture Overviews 1719.5 Open Flow 1749.6 SDN Security Architecture 1789.7 Techniques to Mitigate SDN Security Threats 1809.7.1 Performance Metrics 1869.7.2 Performance Tests 1869.7.3 Data Hiding-Based Geo Location Authentication Protocol 1889.7.4 Identity Access Management (IAM) Extended Policies 1919.7.5 Extended Identity-Based Cryptography 1929.8 Future Research Directions 1949.9 Conclusions 195References 19610 Bio-Inspired Routing in VANET 199Alankrita Aggarwal, Shivani Gaba, Shally Nagpal and Bhavanshu Vig10.1 Introduction 19910.2 Geography-Based Routing 20210.3 Topology-Based Routing 20310.3.1 Drawbacks 20310.3.2 Literature Review 20410.4 Biological Computing 20810.5 Elephant Herding Optimization Algorithm 20910.6 Research Methodology 21110.6.1 Clan Operator 21110.6.2 Separating Operator 21210.6.3 Simulation Results 21310.7 Conclusion 216References 21611 Distributed Key Generation for Secure Communications Between Different Actors in Service Oriented Highly Dense VANET 221Deena Nath Gupta and Rajendra Kumar11.1 Introduction 22211.2 Hierarchical Clustering 22411.3 Layer-Wise Key Generation 22511.4 Implementation 22611.5 Randomness Test 22711.6 Brute Force Attack Analysis 22811.7 Conclusion 229References 23012 Challenges, Benefits and Issues: Future Emerging VANETs and Cloud Approaches 233Bhanu Chander12.1 Introduction 23412.2 VANET Background 23612.3 VANET Communication Standards 23812.4 VANET Applications 23912.4.1 Safety Applications 23912.4.2 Non-Safety Applications 24012.5 VANET Sensing Technologies 24212.5.1 Sensing Technology 24212.5.2 Positioning Technologies 24312.5.3 Vision Technologies 24412.5.4 Vehicular Networks 24412.6 Trust in Ad Hoc Networks 24412.6.1 Cryptographic Approaches 24512.6.2 Recommendation-Based Approaches 24512.6.3 Fuzzy Logic-Based Approaches 24512.6.4 Game Theory-Based Approaches 24612.6.5 Infrastructure-Based Approaches 24612.6.6 Road- and Consensus-Based Advances 24612.6.7 Blockchain-Based Approaches 24612.6.8 Machine Learning Base Trust Management in Vehicular Networks 24712.6.9 Trust in Cellular-Based (5G) VANET 24712.6.10 Software-Defined VANET (SDVANET) 24712.6.11 Trust in Vehicular Social Networks (VSN) 24812.6.12 Future Challenges in VANET Trust Technique 24812.7 Software-Defined Network (SDN) in VANET 24912.7.1 Literature Work on SDVN 25012.7.2 Advantages 25112.7.3 Challenge 25212.8 Clustering Approaches: Issues 25312.9 Up-and-Coming Technologies for Potential VANET 25412.9.1 Edge Cloud Computing 25412.9.1.1 Fog Computing 25412.9.1.2 Mobile Edge Computing (MEC) 25512.9.1.3 Cloudlets 25512.10 Challenges, Open Issues and Future Work of VANETs 25612.10.1 Challenges of VANET 25612.10.2 Open Issues in VANET Development 25712.10.3 Future Research Work 25812.11 Conclusion 259References 26013 Role of Machine Learning for Ad Hoc Networks 269Shivani Gaba, Alankrita Aggarwal and Shally Nagpal13.1 Introduction 27013.2 Literature Survey 27313.3 Machine Learning Computing 27713.3.1 Reinforcement Learning 27713.3.2 Q-Learning/Transfer Learning 27813.3.3 Fuzzy Logic 27813.3.4 Logistic Regression 27913.4 Methodology 28013.4.1 Rate Estimation Algorithm 28013.4.2 Route Selection Algorithm 28113.4.3 Algorithm for Congestion Free Route (Congestion Algorithm) 28313.5 Simulation Results 28413.6 Conclusions 287References 28714 Smart Automotive System With CV2X-Based Ad Hoc Communication 293Rabindranath Bera14.1 Introduction 29414.2 Realization of Smart Vehicle 30014.3 Analysis of NXP Smart Vehicle Architecture 30314.4 Smart Vehicle Proof of Concept (POC) 30814.4.1 ECE, SMIT Adaptation of 3GPP 5G Standard for 5G-Enabled Smart Vehicle 30814.4.2 Emulation of Smart Vehicle at ECE, SMIT LAB 30814.4.2.1 Emulation of V2I (Vehicle to Infrastructure) 5G URLLC Communication Between i) One Intelligent Roadside Unit (RSU), ii) One Smart Vehicle (SV) 30814.4.2.2 Emulation of V2V (Vehicle to Vehicle) 5G URLLC Communication Between Two Smart Vehicles i) One Smart Vehicle (SV1), ii) Another Smart Vehicle (SV2) 31414.5 Smart Vehicle Trials 31514.6 System Comparison 32114.7 Summary and Conclusion 321Acknowledgement 321References 32115 QoS Enhancement in MANET 325Jayson K. Jayabarathan, S. Robinson and A. Sivanantha Raja15.1 Introduction 32515.2 Priority Aware Mechanism (PAM) 32715.3 Power Aware Mechanism 32915.4 Hybrid Mechanism 33015.5 Simulation Results and Discussion 33215.6 Performance Comparison 33915.7 Conclusion 342References 34616 Simulating a Smart Car Routing Model (Implementing MFR Framework) in Smart Cities 349Nada M. Alhakkak16.1 Introduction 35016.2 Background 35016.3 Literature Review 35216.4 Methodology 35516.4.1 System Framework 35516.5 Discussion and a Future Direction 35716.5.1 Case Study 35816.5.2 Fog-Simulator 36116.5.3 MOA-Simulator 36116.5.4 CloudSim-Simulator 36116.6 Conclusions 364References 36517 Potentials of Network-Based Unmanned Aerial Vehicles 369P. K. Garg17.1 Introduction 37017.2 Applications of UAVs 37117.3 Advantages of UAVs 37517.4 UAV Communication System 37617.5 Types of Communication 37817.6 Wireless Sensor Network (WSN) System 38017.7 The Swarm Approach 38317.7.1 Infrastructure-Based Swarm Architecture 38417.7.2 FANET-Based Swarm Architecture 38517.8 Market Potential of UAVs 39117.9 Conclusion 392References 393Index 399