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Intelligent Computing and Communication for the Internet of Vehicles

by Mushu Li , Jie Gao , Xuemin (Sherman) Shen
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Current price ₹5,069.00
Original price ₹5,199.00
Original price ₹5,199.00
Original price ₹5,199.00
(-3%)
₹5,069.00
Current price ₹5,069.00

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Book cover type: Paperback
  • ISBN13: 9783031228612
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Springer
  • Publisher Imprint: Springer
  • Publication Date:
  • Pages: 94
  • Original Price: GBP 39.99
  • Language: English
  • Edition: N/A
  • Item Weight: 146 grams
  • BISAC Subject(s): Networking / Hardware

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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