Intelligent computing and communication for the internet of vehicles / Mushu Li, Jie Gao, Xuemin (Sherman) Shen, Lian Zhao.
Li, Mushu, author.; Gao, Jie, 1985- author.; Shen, X. (Xuemin), 1958- author.; Zhao, Lian, author.
2023
TE228.37
Available Online

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Title
Intelligent computing and communication for the internet of vehicles / Mushu Li, Jie Gao, Xuemin (Sherman) Shen, Lian Zhao.
Author
Li, Mushu, author.
ISBN
9783031228605 (electronic bk.)
303122860X (electronic bk.)
9783031228599
3031228596
DOI
https://doi.org/10.1007/978-3-031-22860-5
Published
Cham : Springer, [2023]
Copyright
©2023
Language
English
Description
1 online resource (x, 82 pages) : illustrations (some color).
Item Number
10.1007/978-3-031-22860-5 doi
Call Number
TE228.37
Dewey Decimal Classification
388.3/12
Summary
This book investigates intelligent network resource management for IoV, with the objective of maximizing the communication and computing performance of vehicle users. Focusing on two representative use cases in IoV, i.e., safety message broadcast and autonomous driving, the authors propose link-layer protocol design and application-layer computing task scheduling to achieve the objective given the unique characteristics and requirements of IoV. In particular, this book illustrates the challenges of resource management for IoV due to network dynamics, such as time-varying traffic intensity and vehicle mobility, and presents intelligent resource management solutions to adapt to the network dynamics. The Internet of Vehicles (IoV) enables vehicle-to-everything connectivity and supports a variety of applications for vehicles on the road Intelligent resource management is critical for satisfying demanding communication and computing requirements on IoV, while the highly dynamic network environments pose challenges to the design of resource management schemes. This book provides insights into the significance of adaptive resource management in improving the performance of IoV. The customized communication protocol and computing scheduling scheme are designed accordingly by taking the network dynamics information as an integral design factor. Moreover, the decentralized designs of the proposed solutions guarantee low signaling overhead and high scalability. A comprehensive literature review summarizing recent resource management schemes in IoV, followed by the customized design of communication and computing solutions for the two IoV use cases is included which can serve as a useful reference for professionals from both academia and industry in the area of IoV and resource management. Researchers working within this field and computer science and electrical engineering students will find this book useful as well.
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Access limited to authorized users.
Source of Description
Description based on print version record.
Added Author
Gao, Jie, 1985- author.
Shen, X. (Xuemin), 1958- author.
Zhao, Lian, author.
Series
SpringerBriefs in computer science.
Available in Other Form
Intelligent computing and communication for the internet of vehicles.
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Online Access
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1 Introduction
1.1 Internet of Vehicles (IoV)
1.2 IoV Use Cases
1.3 Network Characteristics in IoV
1.4 Outline of the Monograph
References
2 Overview of Communication and Computing in IoV
2.1 Communication and Computing in IoV
2.2 V2X Communication Protocols
2.3 Vehicular Computing Resource Scheduling
References
3 Protocol Design for Safety Message Broadcast
3.1 Communication in Safety Message Broadcast
3.2 Network Scenario
3.2.1 Basic Settings
3.2.2 Features of Safety Message Broadcast
3.2.3 Assumptions
3.3 CIDC: A Distributed and Adaptive MAC Design
3.3.1 Messaging Mechanism Design
3.3.2 Contention Intensity Estimation Method
3.3.3 Channel Access Mechanism Design
3.4 CIDC: Network-Perspective Modeling
3.5 CIDC: Performance Analysis
3.5.1 Basic Features
3.5.2 Packet-to-Slot Ratio
3.5.3 Contention Intensity and Contention Delay
3.5.4 Collision Conditions and Probability
3.6 Performance Evaluation
vii
viii Contents
3.6.1 Performance with Accurate Contention Intensity
Estimation
3.6.2 A Comparison of Analytical and Numerical Results
3.6.3 Performance under Contention Intensity Estimation
Errors
3.7 Summary
References
4 Computing Scheduling for Autonomous Driving
4.1 Computing in Autonomous Driving
4.2 System Model
4.2.1 Network Model
4.2.2 Computing Scheduling Scenarios
4.2.3 Age of Computing Results
4.3 Adaptive Computing Resource Scheduling
4.3.1 Restless Multi-armed Bandit Formulation
4.3.2 Indexability and Index Policy
4.4 Machine Learning-based Scheduling Policy
4.4.1 DRL-assisted Scheduling
4.4.2 Scheduling Scheme for Asynchronous Offloading
4.5 Performance Evaluation
4.5.1 Numerical Results
4.5.2 Simulation in a Real Dataset
4.6 Summary
References
5 Conclusions
5.1 Conclusions on Intelligent Computing and Communication
in IoV
5.2 Open Research Problems.

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