Wireless communication is continuously evolving to improve and be a part of our daily communication. This leads to improved quality of services and applications supported by networking technologies. We are now able to use LTE, LTE-Advanced, and other emerging technologies due to the enormous efforts that are made to improve the quality of service in cellular networks. As the future of networking is uncertain, the use of deep learning and big data analytics is a point of focus as it can work in many capacities at a variety of levels for wireless communications. Implementing Data Analytics and Architectures for Next Generation Wireless Communications addresses the existing and emerging theoretical and practical challenges in the design, development, and implementation of big data algorithms, protocols, architectures, and applications for next generation wireless communications and their applications in smart cities. The chapters of this book bring together academics and industrial practitioners to exchange, discuss, and implement the latest innovations and applications of data analytics in advanced networks. Specific topics covered include key encryption techniques, smart home appliances, fog communication networks, and security in the internet of things. This book is valuable for technologists, data analysts, networking experts, practitioners, researchers, academicians, and students.

Provides a comprehensive introduction to the latest research in networking Explores implementation issues and research challenges Focuses on applications and enabling technologies Covers wireless technologies, Big Data, IoT, and other emerging research areas Features contributions from worldwide experts

In recent years, wireless communication has become an integral part of daily life, allowing people across the world to communicate with each other easily, regardless of their geographical location. As these technologies develop, innovations are made in the ways in which they are constructed. Emerging trends in smart material usage in wireless technology requires further investigation for the optimization of next-generation communication technology. Innovative Smart Materials Used in Wireless Communication Technology focuses on the advancements of smart material usage in wireless communication technologies. It analyzes the design, usage, and construction of these smart materials for wireless applications. Covering topics such as millimeter wave antennas, semiconductor materials, and wearable applications, this premier reference source is an essential resource for material engineers and scientists, communications scientists, manufacturers, students and educators of higher education, librarians, researchers, and academicians.

Enabling Technologies for Next Generation Wireless Communications provides up-to-date information on emerging trends in wireless systems, their enabling technologies and their evolving application paradigms. This book includes the latest trends and developments toward next generation wireless communications. It highlights the requirements of next generation wireless systems, limitations of existing technologies in delivering those requirements and the need to develop radical new technologies. It focuses on bringing together information on various technological developments that are enablers vital to fulfilling the requirements of future wireless communication systems and their applications. Topics discussed include spectrum issues, network planning, signal processing, transmitter, receiver, antenna technologies, channel coding, security and application of machine learning and deep learning for wireless communication systems. The book also provides information on enabling business models for future wireless systems. This book is useful as a resource for researchers and practitioners worldwide, including industry practitioners, technologists, policy decision-makers, academicians, and graduate students.

This book presents state-of-the-art optimization algorithms followed by Internet of Things (IoT) fundamentals. The applications of machine learning and IoT are explored, with topics including optimization, algorithms and machine learning in image processing and IoT. Applications of Optimization and Machine Learning in Image Processing and IoT is a complete reference source, providing the latest research findings and solutions for optimization and machine learning algorithms. The chapters examine and discuss the fields of machine learning, IoT and image processing. KEY FEATURES: • Includes fundamental concepts towards advanced applications in machine learning and IoT. • Discusses potential and challenges of machine learning for IoT and optimization • Reviews recent advancements in diverse researches on computer vision, networking and optimization field. • Presents latest technologies such as machine learning in image processing and IoT This book has been written for readers in academia, engineering, IT specialists, researchers, industrial professionals and students, and is a great reference for those just starting out in the field as well as those at an advanced level.

Enormous developments have been made in the field of information and communication technologies (ICT) during the past four decades as ICT has spread rapidly in the world and become a significant part of daily life for economic units. ICT development and penetration are continuing to affect all aspects of societies and have led to significant changes in almost all disciplines such as education, environment, economics, management, energy, health, and medical care. Economic and Social Implications of Information and Communication Technologies explores the economic and social implications of ICT development and penetration from a multidisciplinary perspective. Covering key topics such as sustainability, public health, and economic growth, this reference work is ideal for managers, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.

In the past decades, cyber-physical systems (CPSs) have been widely applied to fields such as smart grids, environment monitoring, aerospace, smart transportation, and industrial automation. Great strides have been made in CPSs to improve the computing mechanism, communication, and quality of service by applying optimization algorithms. Currently, these efforts are integrated with the applications of machine learning (ML) and artificial intelligence (AI). To maintain system reliability and stability, CPSs such as smart grids face numerous challenges, including large-scale Internet-of-Things (IoT) device adaptation, ever-increasing demands of electrical energy, and the rise of a wide range of security threats. These challenges bring forth the need to find sustainable and advanced solutions to guarantee reliable and secure operations in these systems. The goal of this book is to foster transformative, multidisciplinary, and novel approaches that ensure CPS security by taking into consideration the unique security challenges present in the environment. This book attracts contributions in all aspects pertaining to this multidisciplinary paradigm, which includes the development and implementation of Smart CPS, Supervisory Control and Data Acquisition (SCADA) systems, CPS for Industry 4.0, CPS architecture for IoT applications, and CPS forensics. This book: Discusses concepts including wireless sensor networks (WSNs), CPSs, and the IoT in a comprehensive manner. Covers routing protocols in sensor networks, attacks, and vulnerabilities in WSNs, the Internet of Cyber-Physical Things, and CPSs for industrial applications. Highlights technological advances, practical solutions, emerging trends, and prototypes related to privacy in CPSs and the IoT. Presents a pathway and architecture for proactive security schemes in CPSs to counter vulnerabilities, including phishing attacks, malware injection, internal stealing of data, and hacking. Discusses the most recent research and development on the enabling technologies for IoT-based CPSs. Owing to the scope and diversity of topics covered, the book will be of interest not only to researchers and theorists but also to professionals, material developers, technology specialists, and methodologists dealing with the multifarious aspects of data privacy and security enhancement in CPSs. The book will provide these professionals an overview of CPS security and privacy design, as well as enlighten them to promising solutions to research problems such as cyberattacks in CPS, risk identification and management in CPS, ML-based trust computational models for CPSs, nature-inspired algorithms for CPSs, and distributed consensus algorithms for event detection in CPSs. The secondary target audience of this book includes legal practitioners, hackers, cyber law policymakers, cyber forensic analysts, and global security consortiums who may use it to further their research exposure to pertinent topics in cybersecurity.