Оглавление
Группа авторов. Cloud and IoT-Based Vehicular Ad Hoc Networks
Table of Contents
List of Illustrations
List of Tables
Guide
Pages
Cloud and IoT-Based Vehicular Ad Hoc Networks
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
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
12.9.1.1.1 Fog Computing for Future VANETs
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)
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)
14.5 Smart Vehicle Trials
14.6 System Comparison
14.7 Summary and Conclusion
Acknowledgement
References
15. QoS Enhancement in MANET
15.1 Introduction
15.2 Priority Aware Mechanism (PAM)
15.3 Power Aware Mechanism
15.4 Hybrid Mechanism
15.5 Simulation Results and Discussion
15.6 Performance Comparison
15.7 Conclusion
References
16. Simulating a Smart Car Routing Model (Implementing MFR Framework) in Smart Cities
16.1 Introduction
16.2 Background
16.3 Literature Review
16.4 Methodology
16.4.1 System Framework
16.5 Discussion and a Future Direction
16.5.1 Case Study
16.5.2 Fog-Simulator
16.5.3 MOA-Simulator
16.5.4 CloudSim-Simulator
16.6 Conclusions
References
17. Potentials of Network-Based Unmanned Aerial Vehicles
17.1 Introduction
17.2 Applications of UAVs
17.3 Advantages of UAVs
17.4 UAV Communication System
17.5 Types of Communication
17.6 Wireless Sensor Network (WSN) System
17.7 The Swarm Approach
17.7.1 Infrastructure-Based Swarm Architecture
17.7.2 FANET-Based Swarm Architecture
17.8 Market Potential of UAVs
17.9 Conclusion
References
Index
About the Editors
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