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Internet access in vehicular networks

Shen, X.

Internet access in vehicular networks

Record Type:	Electronic resources : Monograph/item
Title/Author:	Internet access in vehicular networksby Wenchao Xu, Haibo Zhou, Xuemin (Sherman) Shen.
Author:	Xu, Wenchao.
other author:	Zhou, Haibo.
Published:	Cham :Springer International Publishing :2021.
Description:	xii, 165 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Mobile communication systems.
Online resource:	https://doi.org/10.1007/978-3-030-88991-3
ISBN:	9783030889913$q(electronic bk.)

Internet access in vehicular networks
Xu, Wenchao.

Internet access in vehicular networks[electronic resource] /by Wenchao Xu, Haibo Zhou, Xuemin (Sherman) Shen. - Cham :Springer International Publishing :2021. - xii, 165 p. :ill., digital ;24 cm.

Overview of Internet Access of Vehicular Networks -- Internet Access Modeling of Vehicular Internet Access -- V2X Interworking via Vehicular Internet Access -- Intelligent Link Management for Vehicular Internet Access -- Intelligent Networking enabled Vehicular Distributed Learning -- Conclusion and Future Works.

This book introduces the Internet access for vehicles as well as novel communication and computing paradigms based on the Internet of vehicles. To enable efficient and reliable Internet connection for mobile vehicle users, this book first introduces analytical modelling methods for the practical vehicle-to-roadside (V2R) Internet access procedure, and employ the interworking of V2R and vehicle-to-vehicle (V2V) to improve the network performance for a variety of automotive applications. In addition, the wireless link performance between a vehicle and an Internet access station is investigated, and a machine learning based algorithm is proposed to improve the link throughout by selecting an efficient modulation and coding scheme. This book also investigates the distributed machine learning algorithms over the Internet access of vehicles. A novel broadcasting scheme is designed to intelligently adjust the training users that are involved in the iteration rounds for an asynchronous federated learning scheme, which is shown to greatly improve the training efficiency. This book conducts the fully asynchronous machine learning evaluations among vehicle users that can utilize the opportunistic V2R communication to train machine learning models. Researchers and advanced-level students who focus on vehicular networks, industrial entities for internet of vehicles providers, government agencies target on transportation system and road management will find this book useful as reference. Network device manufacturers and network operators will also want to purchase this book.

ISBN: 9783030889913$q(electronic bk.)

Standard No.: 10.1007/978-3-030-88991-3doiSubjects--Topical Terms:

182488
Mobile communication systems.

LC Class. No.: TK5103.2 / .X8 2021

Dewey Class. No.: 621.3845

Internet access in vehicular networks
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245 1 0 $a Internet access in vehicular networks $h [electronic resource] / $c by Wenchao Xu, Haibo Zhou, Xuemin (Sherman) Shen.
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505 0 $a Overview of Internet Access of Vehicular Networks -- Internet Access Modeling of Vehicular Internet Access -- V2X Interworking via Vehicular Internet Access -- Intelligent Link Management for Vehicular Internet Access -- Intelligent Networking enabled Vehicular Distributed Learning -- Conclusion and Future Works.
520 $a This book introduces the Internet access for vehicles as well as novel communication and computing paradigms based on the Internet of vehicles. To enable efficient and reliable Internet connection for mobile vehicle users, this book first introduces analytical modelling methods for the practical vehicle-to-roadside (V2R) Internet access procedure, and employ the interworking of V2R and vehicle-to-vehicle (V2V) to improve the network performance for a variety of automotive applications. In addition, the wireless link performance between a vehicle and an Internet access station is investigated, and a machine learning based algorithm is proposed to improve the link throughout by selecting an efficient modulation and coding scheme. This book also investigates the distributed machine learning algorithms over the Internet access of vehicles. A novel broadcasting scheme is designed to intelligently adjust the training users that are involved in the iteration rounds for an asynchronous federated learning scheme, which is shown to greatly improve the training efficiency. This book conducts the fully asynchronous machine learning evaluations among vehicle users that can utilize the opportunistic V2R communication to train machine learning models. Researchers and advanced-level students who focus on vehicular networks, industrial entities for internet of vehicles providers, government agencies target on transportation system and road management will find this book useful as reference. Network device manufacturers and network operators will also want to purchase this book.
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