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.
