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    <title>Toward Connected, Cooperative and Intelligent IoV</title>
    <subTitle>Frontier Technologies and Applications</subTitle>
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    <namePart>Liu, Kai.</namePart>
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    <namePart>Dai, Penglin.</namePart>
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    <namePart>Lee, Victor C.S.</namePart>
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    <namePart>Ng, Joseph Kee-Yin.</namePart>
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    <namePart>Son, Sang Hyuk.</namePart>
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    <dateIssued encoding="marc">2024</dateIssued>
    <edition>1st ed. 2024.</edition>
    <issuance>monographic</issuance>
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    <extent>XX, 327 p. 1 illus. online resource.</extent>
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  <abstract>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.</abstract>
  <tableOfContents>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.</tableOfContents>
  <note type="statement of responsibility">by Kai Liu, Penglin Dai, Victor C.S. Lee, Joseph Kee-Yin Ng, Sang Hyuk Son.</note>
  <subject authority="lcsh">
    <topic>Mobile computing</topic>
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  <subject authority="lcsh">
    <topic>Cooperating objects (Computer systems)</topic>
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  <subject authority="lcsh">
    <topic>Mathematical optimization</topic>
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    <topic>Algorithms</topic>
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  <subject authority="lcsh">
    <topic>Internet of things</topic>
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  <subject authority="lcsh">
    <topic>Machine learning</topic>
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  <subject>
    <topic>Mobile Computing</topic>
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  <subject>
    <topic>Cyber-Physical Systems</topic>
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  <subject>
    <topic>Discrete Optimization</topic>
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  <subject>
    <topic>Design and Analysis of Algorithms</topic>
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  <subject>
    <topic>Internet of Things</topic>
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  <subject>
    <topic>Machine Learning</topic>
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  <identifier type="isbn">9789819996476</identifier>
  <identifier type="uri">https://doi.org/10.1007/978-981-99-9647-6</identifier>
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