Learning-based VANET Communication and Security Techniques
Language: English
Published by Springer, Springer Dez 2019, 2019
- Softcover
- New
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
AbeBooks seller since January 23, 2017
Condition: New
£ 94.61
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Add to basketItem description from seller
This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 144 pp. Englisch.…
Seller Inventory # 9783030131920
- Title
- Learning-based VANET Communication and Security Techniques
- Author
- Liang Xiao
- Publisher
- Springer, Springer Dez 2019
- Publication year
- 2019
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 3030131920
- ISBN 13
- 9783030131920
- Item weight
- 230 grams
- Dimensions
- 235x155x9 mm
- Series
- Book 28 of 58: Wireless Networks
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.
"Synopsis" may belong to another edition of this title.
buchversandmimpf2000
Emtmannsberg, BAYE, Germany
AbeBooks seller since January 23, 2017
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