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Toward connected, cooperative and intelligent IoV = frontier technologies and applications /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Toward connected, cooperative and intelligent IoV/ by Kai Liu ... [et al.].
其他題名:	frontier technologies and applications /
其他作者:	Liu, Kai.
出版者:	Singapore :Springer Nature Singapore : : 2024.,
面頁冊數:	xx, 327 p. :ill., digital ;24 cm.
內容註:	Part I. Introduction -- Chapter 1. Background of IoV -- Chapter 2. State-of-the-Art -- Part II. Connected IoV: Vehicular Communications and Data Dissemination -- Chapter 3. Data Dissemination via I2V/V2V Communications in Software Defined Vehicular Networks -- Chapter 4. Network Coding Assisted Data Broadcast in Large-Scale Vehicular Networks -- Chapter 5. Fog Computing Empowered Data Dissemination in Heterogeneous Vehicular Networks -- Chapter 6. Temporal Data Uploading and Dissemination in Real-time Vehicular Networks -- Part III Cooperative IoV: End-Edge-Cloud Cooperative Scheduling and Optimization -- Chapter 7. Convex Optimization on Vehicular End-Edge-Cloud Cooperative Task Offloading -- Chapter 8. An Approximation Algorithm for Joint Data Uploading and Task Offloading in IoV -- Chapter 9. Distributed Task Offloading and Workload Balancing in IoV -- Part IV. Intelligent IoV: Key Enabling Technologies in Vehicular Edge Intelligence -- Chapter 10. Toward Timely and Reliable DNN Inference in Vehicular Edge Intelligence -- Chapter 11. Deep Q-learning based Adaptive Multimedia Streaming in Vehicular Edge Intelligence -- Chapter 12. A Multi-agent Multi-objective Deep Reinforcement Learning Solution for Digital Twin in Vehicular Edge Intelligence -- Part V. Case Studies -- Chapter 13. See Through System -- Chapter 14. Non-Line-of-Sight Collision Warning System -- Chapter 15. Proactive Traffic Abnormity Warning System -- Chapter 16. UAV-assisted Pedestrian Detection System -- Chapter 17. Vehicular Indoor Localization and Tracking System -- Part VI. Conclusion and Future Directions -- Chapter 18. Conclusion -- Chapter 19. Future Directions.
Contained By:	Springer Nature eBook
標題:	Vehicular ad hoc networks (Computer networks) -
電子資源:	https://doi.org/10.1007/978-981-99-9647-6
ISBN:	9789819996476

Toward connected, cooperative and intelligent IoV = frontier technologies and applications /
Toward connected, cooperative and intelligent IoVfrontier technologies and applications /[electronic resource] :by Kai Liu ... [et al.]. - Singapore :Springer Nature Singapore :2024. - xx, 327 p. :ill., digital ;24 cm.

Part I. Introduction -- Chapter 1. Background of IoV -- Chapter 2. State-of-the-Art -- Part II. Connected IoV: Vehicular Communications and Data Dissemination -- Chapter 3. Data Dissemination via I2V/V2V Communications in Software Defined Vehicular Networks -- Chapter 4. Network Coding Assisted Data Broadcast in Large-Scale Vehicular Networks -- Chapter 5. Fog Computing Empowered Data Dissemination in Heterogeneous Vehicular Networks -- Chapter 6. Temporal Data Uploading and Dissemination in Real-time Vehicular Networks -- Part III Cooperative IoV: End-Edge-Cloud Cooperative Scheduling and Optimization -- Chapter 7. Convex Optimization on Vehicular End-Edge-Cloud Cooperative Task Offloading -- Chapter 8. An Approximation Algorithm for Joint Data Uploading and Task Offloading in IoV -- Chapter 9. Distributed Task Offloading and Workload Balancing in IoV -- Part IV. Intelligent IoV: Key Enabling Technologies in Vehicular Edge Intelligence -- Chapter 10. Toward Timely and Reliable DNN Inference in Vehicular Edge Intelligence -- Chapter 11. Deep Q-learning based Adaptive Multimedia Streaming in Vehicular Edge Intelligence -- Chapter 12. A Multi-agent Multi-objective Deep Reinforcement Learning Solution for Digital Twin in Vehicular Edge Intelligence -- Part V. Case Studies -- Chapter 13. See Through System -- Chapter 14. Non-Line-of-Sight Collision Warning System -- Chapter 15. Proactive Traffic Abnormity Warning System -- Chapter 16. UAV-assisted Pedestrian Detection System -- Chapter 17. Vehicular Indoor Localization and Tracking System -- Part VI. Conclusion and Future Directions -- Chapter 18. Conclusion -- Chapter 19. Future Directions.

This book offers a comprehensive introduction to technological advances in Internet of Vehicles (IoV), including vehicular communications, vehicular system architectures, data dissemination algorithms, resource allocation schemes, and AI-enabled applications. It focuses on the state-of-the-art IoV with regard to three major directions, namely networking, cooperation, and intelligence, including advanced wireless communication technologies, algorithm theory, optimization mechanisms, and AI technologies. In addition, the book includes a number of case studies with system prototype implementation and hands-on experiments in IoV, making it suitable both as a technical reference work for professionals and as a textbook for graduate students.

ISBN: 9789819996476

Standard No.: 10.1007/978-981-99-9647-6doiSubjects--Topical Terms:

1581494
Vehicular ad hoc networks (Computer networks)

LC Class. No.: TE228.37

Dewey Class. No.: 629.20285

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505 0 $a Part I. Introduction -- Chapter 1. Background of IoV -- Chapter 2. State-of-the-Art -- Part II. Connected IoV: Vehicular Communications and Data Dissemination -- Chapter 3. Data Dissemination via I2V/V2V Communications in Software Defined Vehicular Networks -- Chapter 4. Network Coding Assisted Data Broadcast in Large-Scale Vehicular Networks -- Chapter 5. Fog Computing Empowered Data Dissemination in Heterogeneous Vehicular Networks -- Chapter 6. Temporal Data Uploading and Dissemination in Real-time Vehicular Networks -- Part III Cooperative IoV: End-Edge-Cloud Cooperative Scheduling and Optimization -- Chapter 7. Convex Optimization on Vehicular End-Edge-Cloud Cooperative Task Offloading -- Chapter 8. An Approximation Algorithm for Joint Data Uploading and Task Offloading in IoV -- Chapter 9. Distributed Task Offloading and Workload Balancing in IoV -- Part IV. Intelligent IoV: Key Enabling Technologies in Vehicular Edge Intelligence -- Chapter 10. Toward Timely and Reliable DNN Inference in Vehicular Edge Intelligence -- Chapter 11. Deep Q-learning based Adaptive Multimedia Streaming in Vehicular Edge Intelligence -- Chapter 12. A Multi-agent Multi-objective Deep Reinforcement Learning Solution for Digital Twin in Vehicular Edge Intelligence -- Part V. Case Studies -- Chapter 13. See Through System -- Chapter 14. Non-Line-of-Sight Collision Warning System -- Chapter 15. Proactive Traffic Abnormity Warning System -- Chapter 16. UAV-assisted Pedestrian Detection System -- Chapter 17. Vehicular Indoor Localization and Tracking System -- Part VI. Conclusion and Future Directions -- Chapter 18. Conclusion -- Chapter 19. Future Directions.
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