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Learning-based VANET Communication and Security Techniques (Paperback, Softcover reprint of the original 1st ed. 2019)
Loot Price: R2,789
Discovery Miles 27 890
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Learning-based VANET Communication and Security Techniques (Paperback, Softcover reprint of the original 1st ed. 2019)
Series: Wireless Networks
Expected to ship within 10 - 15 working days
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This timely book provides broad coverage of vehicular ad-hoc
network (VANET) issues, such as security, and network selection.
Machine learning based methods are applied to solve these issues.
This book also includes four rigorously refereed chapters from
prominent international researchers working in this subject area.
The material serves as a useful reference for researchers, graduate
students, and practitioners seeking solutions to VANET
communication and security related issues. This book will also help
readers understand how to use machine learning to address the
security and communication challenges in VANETs. Vehicular ad-hoc
networks (VANETs) support vehicle-to-vehicle communications and
vehicle-to-infrastructure communications to improve the
transmission security, help build unmanned-driving, and support
booming applications of onboard units (OBUs). The high mobility of
OBUs and the large-scale dynamic network with fixed roadside units
(RSUs) make the VANET vulnerable to jamming. The anti-jamming
communication of VANETs can be significantly improved by using
unmanned aerial vehicles (UAVs) to relay the OBU message. UAVs help
relay the OBU message to improve the
signal-to-interference-plus-noise-ratio of the OBU signals, and
thus reduce the bit-error-rate of the OBU message, especially if
the serving RSUs are blocked by jammers and/or interference, which
is also demonstrated in this book. This book serves as a useful
reference for researchers, graduate students, and practitioners
seeking solutions to VANET communication and security related
issues.
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