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.

This book provides a timely and comprehensive study of developing efficient network slicing frameworks in both 5G wireless and core networks. It also presents protocol stack layer perspectives, which includes virtual network topology design, end-to-end delay modeling, dynamic resource slicing, and link-layer and transport-layer protocol customization. This book provides basic principles, concepts and technologies for communication, computing and networking. Optimization and queueing analysis techniques are applied to solving different problems for network slicing illustrated in this book as well. Researchers working in the area of network slicing in 5G networks and beyond, and advanced-level students majoring in electrical engineering, computer engineering and computer science will find this book useful as a reference or secondary textbook. Professionals in industry seeking solutions to resource management for 5G networks and beyond will also want to purchase this book.

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

This book investigates intelligent network resource management for IoV, with the objective of maximizing the communication and computing performance of vehicle users. Focusing on two representative use cases in IoV, i.e., safety message broadcast and autonomous driving, the authors propose link-layer protocol design and application-layer computing task scheduling to achieve the objective given the unique characteristics and requirements of IoV. In particular, this book illustrates the challenges of resource management for IoV due to network dynamics, such as time-varying traffic intensity and vehicle mobility, and presents intelligent resource management solutions to adapt to the network dynamics. The Internet of Vehicles (IoV) enables vehicle-to-everything connectivity and supports a variety of applications for vehicles on the road. Intelligent resource management is critical for satisfying demanding communication and computing requirements on IoV, while the highly dynamic network environments pose challenges to the design of resource management schemes. This book provides insights into the significance of adaptive resource management in improving the performance of IoV. The customized communication protocol and computing scheduling scheme are designed accordingly by taking the network dynamics information as an integral design factor. Moreover, the decentralized designs of the proposed solutions guarantee low signaling overhead and high scalability. A comprehensive literature review summarizing recent resource management schemes in IoV, followed by the customized design of communication and computing solutions for the two IoV use cases is included which can serve as a useful reference for professionals from both academia and industry in the area of IoV and resource management. Researchers working within this field and computer science and electrical engineering students will find this book useful as well.

Machine Learning Approach for Cloud Data Analytics in IoT The book covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications Sustainable computing paradigms like cloud and fog are capable of handling issues related to performance, storage and processing, maintenance, security, efficiency, integration, cost, energy and latency in an expeditious manner. In order to expedite decision-making involved in the complex computation and processing of collected data, IoT devices are connected to the cloud or fog environment. Since machine learning as a service provides the best support in business intelligence, organizations have been making significant investments in this technology. Machine Learning Approach for Cloud Data Analytics in IoT elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book.

This book presents a timely description of currently used and proposed technologies that involve the intelligent transport system to assist the manager of large cities. Therefore, it describes all concepts and technologies that address the challenges, bringing up a top-down approach, which begins from the vehicular network and central infrastructure to a distributed structure. For scientists and researchers, this book will bring together the state-of-the-art of the main techniques that involve intelligent transport systems to assist the manager of big cities. For practitioners and professionals, this book will describe techniques which can be put into practice and use to aid the development of new applications and services. Concerning postgraduate students, this book will provide highlights of main concerns and concepts and explain techniques that can assist students to identify challenges that they can explore, contribute to, and advance the current status of technology.

Smart Cities and Homes: Key Enabling Technologies explores the fundamental principles and concepts of the key enabling technologies for smart cities and homes, disseminating the latest research and development efforts in the field through the use of numerous case studies and examples. Smart cities use digital technologies embedded across all their functions to enhance the wellbeing of citizens. Cities that utilize these technologies report enhancements in power efficiency, water use, traffic congestion, environmental protection, pollution reduction, senior citizens care, public safety and security, literacy rates, and more. This book brings together the most important breakthroughs and advances in a coherent fashion, highlighting the interconnections between the works in different areas of computing, exploring both new and emerging computer networking systems and other computing technologies, such as wireless sensor networks, vehicle ad hoc networks, smart girds, cloud computing, and data analytics and their roles in creating environmentally friendly, secure, and prosperous cities and homes. Intended for researchers and practitioners, the book discusses the pervasive and cooperative computing technologies that will perform a central role for handling the challenges of urbanization and demographic change. - Includes case studies and contributions from prominent researchers and practitioners from around the globe - Explores the latest methodologies, theories, tools, applications, trends, challenges, and strategies needed to build smart cities and homes from the bottom up - Provides a pedagogy that includes PowerPoint slides, key terms, and a comprehensive bibliography