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Intelligent Vehicular Networks and Communications

Fundamentals, Architectures and Solutions

  • 1st Edition - September 1, 2016
  • Latest edition
  • Authors: Anand Paul, Naveen Chilamkurti, Alfred Daniel, Seungmin Rho
  • Language: English

Intelligent Vehicular Network and Communications: Fundamentals, Architectures and Solutions begins with discussions on how the transportation system has transformed into today’s I… Read more

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Description

Intelligent Vehicular Network and Communications: Fundamentals, Architectures and Solutions begins with discussions on how the transportation system has transformed into today’s Intelligent Transportation System (ITS). It explores the design goals, challenges, and frameworks for modeling an ITS network, discussing vehicular network model technologies, mobility management architectures, and routing mechanisms and protocols. It looks at the Internet of Vehicles, the vehicular cloud, and vehicular network security and privacy issues.

The book investigates cooperative vehicular systems, a promising solution for addressing current and future traffic safety needs, also exploring cooperative cognitive intelligence, with special attention to spectral efficiency, spectral scarcity, and high mobility. In addition, users will find a thorough examination of experimental work in such areas as Controller Area Network protocol and working function of On Board Unit, as well as working principles of roadside unit and other infrastructural nodes.

Finally, the book examines big data in vehicular networks, exploring various business models, application scenarios, and real-time analytics, concluding with a look at autonomous vehicles.

Key features

  • Proposes cooperative, cognitive, intelligent vehicular networks
  • Examines how intelligent transportation systems make more efficient transportation in urban environments
  • Outlines next generation vehicular networks technology

Readership

Vehicular and Wireless Network researchers, instructors, students, designers, and engineers

Table of contents

  • Preface
  • Chapter 1: Introduction: intelligent vehicular communications
    • Abstract
    • 1.1. Background of transportation networks
    • 1.2. Evolution of transportation models
    • 1.3. Vehicular network standardization
    • 1.4. Vehicular communication technologies
    • 1.5. Concluding statement
  • Chapter 2: Intelligent transportation systems
    • Abstract
    • 2.1. Intelligent transportation systems
    • 2.2. ITS applications and enabling technologies
    • 2.3. Emerging ITS applications
    • 2.4. ITS market segmentation
    • 2.5. Case study
    • 2.6. Conclusions
  • Chapter 3: Vehicular network (VN) model
    • Abstract
    • 3.1. Cluster-based vehicular networks
    • 3.2. Vehicle platooning
    • 3.3. Vehicular cloud
    • 3.4. Hybrid sensor–vehicular networks
    • 3.5. Information distribution
    • 3.6. Internet of Vehicles
    • 3.7. Chapter summary
  • Chapter 4: Evaluation of vehicular network models
    • Abstract
    • 4.1. Data dissemination in vehicular networks
    • 4.2. Mobility management: IPv6-based Internet
    • 4.3. A seamless flow mobility management architecture for vehicular communication networks
    • 4.4. A seamless flow mobility management architecture
    • 4.5. Vehicular-delay tolerant network
    • 4.6. Formal model of human driving behavior
  • Chapter 5: Cognitive radio in vehicular network
    • Abstract
    • 5.1. Cognitive radio for vehicular networks
    • 5.2. Cooperative cognitive radio networks
    • 5.3. Concluding comments
  • Chapter 6: Theory and application of vehicular networks
    • Abstract
    • 6.1. Automotive context-aware in vehicular network
    • 6.2. A novel vehicular information network architecture based on named data networking
    • 6.3. Vehicular cloud networking: architecture and design principles
    • 6.4. Trust-based information dissemination framework for vehicular networks
    • 6.5. Knowledge-based intelligent transportation system
    • 6.6. Hybrid sensor and vehicular networks
    • 6.7. Intravehicle networks
    • 6.8. Vision-based vehicle behavior analysis
    • 6.9. Networked vehicle surveillance in ITS
    • 6.10. Conclusions
  • Chapter 7: Vehicular network as business model in Big Data
    • Abstract
    • 7.1. Big Data technology in vehicular networks
    • 7.2. Data validation in Big Data
    • 7.3. Real-time analysis of Data in VANET
    • 7.4. Vehicular density analysis using Big Data
    • 7.5. Vehicular carriers for Big Data
  • Chapter 8: Big Data collision analysis framework
    • Abstract
    • 8.1. Road traffic data
    • 8.2. Collision rate model
    • 8.3. Design of road traffic Big Data collision analysis processing framework
    • 8.4. Vehicle XML device collaboration with Big Data
    • 8.5. Big Data technologies in support of real-time capturing and understanding of electric vehicles
    • 8.6. Conclusions
  • Chapter 9: Future trends and challenges in ITS
    • Abstract
    • 9.1. Next generation vehicular networks
    • 9.2. Framework definition
    • 9.3. Supporting augmented floating car data through smartphone-based crowd-sensing
    • 9.4. Enabling vehicular mobility in citywide IEEE 802.11 networks through predictive handovers
    • 9.5. Real-time path planning based on hybrid-VANET-enhanced transportation system
    • 9.6. Recent advances in cryptographic solutions for vehicular networks
    • 9.7. Standards harmonization efforts on future ITS
    • 9.8. A novel vehicular mobility modeling technique for developing ITS applications
    • 9.9. Conclusions
  • References
  • Index

Product details

  • Edition: 1
  • Latest edition
  • Published: September 1, 2016
  • Language: English

About the authors

AP

Anand Paul

Anand Paul is an Associate Professor with the Biostatistics and Data Science Program at Louisiana State University Health Science Center. He obtained his Ph.D. degree from the School of Electrical and Computer Engineering at National Cheng Kung University, Taiwan, R.O.C. in 2010. His research focuses on Big Data Analytics and Mathematical Modelling of Machine Learning models, He has done extensive work on Big data/IoT based Smart Cities. Dr. Paul is the founder and director of the Centre for Resilient and Evolving Intelligence at Kyungpook National University, South Korea, where he served from 2012 to 2024. He has been recognized as one of the top 2% scientists globally by both Stanford University and Elsevier Publisher for the years 2021 and 2022. He has been an IEEE Senior Member since 2015 and has held editorial roles in prestigious publications including Editor in Chief of the International Journal of Smart Vehicles and Smart Transportation (IGI Global) from 2019 to 2021, and as Associate Editor in IEEE Access, IET Wireless Sensor Systems, ICT Express, PeerJ Computer Science, ACM Applied Computing Reviews, Cyber Physical Systems (Taylor & Francis), and International Journal of Interactive Multimedia & Artificial Intelligence. Dr. Paul also served as the track chair for Smart Human-Computer Interaction in ACM SAC from 2014 to 2019.

Affiliations and expertise
Louisiana State University, United States

NC

Naveen Chilamkurti

Naveen Chilamkurti is Acting Head of Department, Computer Science and Computer Engineering, La Trobe University, Melbourne, Australia. He is Editor-in-Chief of International Journal of Wireless Networks and Broadband Technologies, and Associate Editor of several other international journals. Dr. Naveen has published more than 165 journal and conference papers, and his research includes intelligent transport systems, wireless multimedia, and wireless sensor networks.
Affiliations and expertise
La Trobe University, Melbourne, Australia

AD

Alfred Daniel

Alfred Daniel is currently an assistant professor of Research and Cloud Computing at SNS College of Technology in Coimbatore, India. His research interests incllude Computer Architecture, artificial intelligence, and computer networks.
Affiliations and expertise
SNS College of Technology, India

SR

Seungmin Rho

Dr. Seungmin Rho, Ph.D. is a faculty of Department of Media Software at Sungkyul University in Korea. In 2012, he was an assistant professor at Division of Information and Communication in Baekseok University. In 2009-2011, he had been working as a Research Professor at School of Electrical Engineering in Korea University. In 2008-2009, he was a Postdoctoral Research Fellow at the Computer Music Lab of the School of Computer Science in Carnegie Mellon University. He gained his B.Science. (2001) in Computer Science from Ajou University, Korea (South), M.Science. (2003) and Ph.D. (2008) in Information and Communication Technology from the Graduate School of Information and Communication at Ajou University. He visited Multimedia Systems and Networking Lab. in Univ. of Texas at Dallas from Dec. 2003 to March 2004. Before he joined the Computer Sciences Department of Ajou University, he spent two years in industry. His current research interests include database, big data analysis, music retrieval, multimedia systems, machine learning, knowledge management as well as computational intelligence.
Affiliations and expertise
Sungkyul University, Korea

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