Intelligent Resource Management in Vehicular Networks / by Haixia Peng, Qiang Ye, Xuemin Sherman Shen
By: Peng, Haixia, autor
Contributor(s): Ye, Qiang., autor | Shen, Xuemin Sherman., autor
Series: (Wireless Networks, 2366-1445).Publisher: Cham : Springer International Publising, 2022Edition: First edition 2022.Description: 1 recurso en línea (XIII, 154 páginas) : 32 ilustraciones, 31 ilustraciones a color.ISBN: 9783030965075.Subject: Sistemas inteligentes de transporte -- Congresos y asambleas
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|---|
LIBRO-E NO PRÉSTAMO
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Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | TK7895.E42 TK5105.8857 (Browse shelf(Opens below)) | Acceso electrónico | eBook.22092255 |
Introduction -- Overview of Vehicular Networks -- Resource Management in Vehicular Networks -- MEC-Assisted Vehicular Networks -- Spectrum Resource Management in MEC-Assisted ADVNETs -- Multi-Dimensional Resource Management in MVNETs -- Multi-Dimensional Resource Management in UAV-Assisted MVNETs -- Conclusion.
This book provides a comprehensive investigation on new technologies for future vehicular networks. The authors propose different schemes to efficiently manage the multi-dimensional resources for supporting diversified applications. The authors answer the questions of why connected and automated vehicle technology should be considered; how the multi-access edge computing (MEC) and unmanned aerial vehicle (UAV) technologies can be helpful to vehicular networks; how to efficiently manage the multi-dimensional resources to support different vehicular applications with guaranteed quality-of-service (QoS) requirements; and how to adopt optimization and AI technologies to achieve resource management in vehicular networks. The book is pertinent to researchers, professionals, academics and students in vehicular technologies. Provides a comprehensive resource management design for vehicular networks; Includes multi-resource management studies in highly dynamic wireless networks; Features applications of AI technologies in multi-dimensional resource management.
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