Distributed systems intertwine with our everyday lives. The benefits and current shortcomings of the underpinning technologies are experienced by a wide range of people and their smart devices. With the rise of large-scale IoT and similar distributed systems, cloud bursting technologies, and partial outsourcing solutions, private entities are encouraged to increase their efficiency and offer unparalleled availability and reliability to their users. Applying Integration Techniques and Methods in Distributed Systems is a critical scholarly publication that defines the current state of distributed systems, determines further goals, and presents architectures and service frameworks to achieve highly integrated distributed systems and presents solutions to integration and efficient management challenges faced by current and future distributed systems. Highlighting topics such as multimedia, programming languages, and smart environments, this book is ideal for system administrators, integrators, designers, developers, researchers, and academicians.

If you look around you will find that all computer systems, from your portable devices to the strongest supercomputers, are heterogeneous in nature. The most obvious heterogeneity is the existence of computing nodes of different capabilities (e.g. multicore, GPUs, FPGAs, ...). But there are also other heterogeneity factors that exist in computing systems, like the memory system components, interconnection, etc. The main reason for these different types of heterogeneity is to have good performance with power efficiency. Heterogeneous computing results in both challenges and opportunities. This book discusses both. It shows that we need to deal with these challenges at all levels of the computing stack: from algorithms all the way to process technology. We discuss the topic of heterogeneous computing from different angles: hardware challenges, current hardware state-of-the-art, software issues, how to make the best use of the current heterogeneous systems, and what lies ahead. The aim of this book is to introduce the big picture of heterogeneous computing. Whether you are a hardware designer or a software developer, you need to know how the pieces of the puzzle fit together. The main goal is to bring researchers and engineers to the forefront of the research frontier in the new era that started a few years ago and is expected to continue for decades. We believe that academics, researchers, practitioners, and students will benefit from this book and will be prepared to tackle the big wave of heterogeneous computing that is here to stay.

Deep Learning through Sparse Representation and Low-Rank Modeling bridges classical sparse and low rank models-those that emphasize problem-specific Interpretability-with recent deep network models that have enabled a larger learning capacity and better utilization of Big Data. It shows how the toolkit of deep learning is closely tied with the sparse/low rank methods and algorithms, providing a rich variety of theoretical and analytic tools to guide the design and interpretation of deep learning models. The development of the theory and models is supported by a wide variety of applications in computer vision, machine learning, signal processing, and data mining. This book will be highly useful for researchers, graduate students and practitioners working in the fields of computer vision, machine learning, signal processing, optimization and statistics.

Vehicular networks were first developed to ensure safe driving and to extend the Internet to the road. However, we can now see that the ability of vehicles to engage in cyber-activity may result in tracking and privacy violations through the interception of messages, which are frequently exchanged on road. This book serves as a guide for students, developers and researchers who are interested in vehicular networks and the associated security and privacy issues. It facilitates the understanding of the technologies used and their various types, highlighting the importance of privacy and security issues and the direct impact they have on the safety of their users. It also explains various solutions and proposals to protect location and identity privacy, including two anonymous authentication methods that preserve identity privacy and a total of five schemes that preserve location privacy in the vehicular ad hoc networks and the cloud-enabled internet of vehicles, respectively.

Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications covers timely topics, including the neural network (NN), particle swarm optimization (PSO), evolutionary algorithm (GA), fuzzy sets (FS) and rough sets (RS), etc. Furthermore, the book highlights recent research on representative techniques to elaborate how a data-centric system formed a powerful platform for the processing of cloud hosted multimedia big data and how it could be analyzed, processed and characterized by CI. The book also provides a view on how techniques in CI can offer solutions in modeling, relationship pattern recognition, clustering and other problems in bioengineering. It is written for domain experts and developers who want to understand and explore the application of computational intelligence aspects (opportunities and challenges) for design and development of a data-centric system in the context of multimedia cloud, big data era and its related applications, such as smarter healthcare, homeland security, traffic control trading analysis and telecom, etc. Researchers and PhD students exploring the significance of data centric systems in the next paradigm of computing will find this book extremely useful.

Industrial internet of things (IIoT) is changing the face of industry by completely redefining the way stakeholders, enterprises, and machines connect and interact with each other in the industrial digital ecosystem. Smart and connected factories, in which all the machinery transmits real-time data, enable industrial data analytics for improving operational efficiency, productivity, and industrial processes, thus creating new business opportunities, asset utilization, and connected services. IIoT leads factories to step out of legacy environments and arcane processes towards open digital industrial ecosystems. Innovations in the Industrial Internet of Things (IIoT) and Smart Factory is a pivotal reference source that discusses the development of models and algorithms for predictive control of industrial operations and focuses on optimization of industrial operational efficiency, rationalization, automation, and maintenance. While highlighting topics such as artificial intelligence, cyber security, and data collection, this book is ideally designed for engineers, manufacturers, industrialists, managers, IT consultants, practitioners, students, researchers, and industrial industry professionals.

Society is continually transforming into a digitally powered reality due to the increased dependence of computing technologies. The landscape of cyber threats is constantly evolving because of this, as hackers are finding improved methods of accessing essential data. Analyzing the historical evolution of cyberattacks can assist practitioners in predicting what future threats could be on the horizon. Real-Time and Retrospective Analyses of Cyber Security is a pivotal reference source that provides vital research on studying the development of cybersecurity practices through historical and sociological analyses. While highlighting topics such as zero trust networks, geopolitical analysis, and cyber warfare, this publication explores the evolution of cyber threats, as well as improving security methods and their socio-technological impact. This book is ideally designed for researchers, policymakers, strategists, officials, developers, educators, sociologists, and students seeking current research on the evolution of cybersecurity methods through historical analysis and future trends.

Technologies in today's society are rapidly developing at a pace that is challenging to stay up to date with. As an increasing number of global regions are implementing smart methods and strategies for sustainable development, they are continually searching for modern advancements within computer science, sensor networks, software engineering, and smart technologies. A compilation of research is needed that displays current applications of computing methodologies in the progression of global cities and how smart technologies are being utilized. Sensor Network Methodologies for Smart Applications is a collection of innovative research on the methods of intelligent systems and technologies and their various applications within sustainable development practices. While highlighting topics including machine learning, network security, and optimization algorithms, this book is ideally designed for researchers, scientists, developers, programmers, engineers, educators, policymakers, geographers, planners, and students seeking current research on smart technologies and sensor networks.

Safety and security are crucial to the operations of nuclear power plants, but cyber threats to these facilities are increasing significantly. Instrumentation and control systems, which play a vital role in the prevention of these incidents, have seen major design modifications with the implementation of digital technologies. Advanced computing systems are assisting in the protection and safety of nuclear power plants; however, significant research on these computational methods is deficient. Cyber Security and Safety of Nuclear Power Plant Instrumentation and Control Systems is a pivotal reference source that provides vital research on the digital developments of instrumentation and control systems for assuring the safety and security of nuclear power plants. While highlighting topics such as accident monitoring systems, classification measures, and UAV fleets, this publication explores individual cases of security breaches as well as future methods of practice. This book is ideally designed for engineers, industry specialists, researchers, policymakers, scientists, academicians, practitioners, and students involved in the development and operation of instrumentation and control systems for nuclear power plants, chemical and petrochemical industries, transport, and medical equipment.

Modern society has become dependent on technology, allowing personal information to be input and used across a variety of personal and professional systems. From banking to medical records to e-commerce, sensitive data has never before been at such a high risk of misuse. As such, organizations now have a greater responsibility than ever to ensure that their stakeholder data is secured, leading to the increased need for cybersecurity specialists and the development of more secure software and systems. To avoid issues such as hacking and create a safer online space, cybersecurity education is vital and not only for those seeking to make a career out of cybersecurity, but also for the general public who must become more aware of the information they are sharing and how they are using it. It is crucial people learn about cybersecurity in a comprehensive and accessible way in order to use the skills to better protect all data. The Research Anthology on Advancements in Cybersecurity Education discusses innovative concepts, theories, and developments for not only teaching cybersecurity, but also for driving awareness of efforts that can be achieved to further secure sensitive data. Providing information on a range of topics from cybersecurity education requirements, cyberspace security talents training systems, and insider threats, it is ideal for educators, IT developers, education professionals, education administrators, researchers, security analysts, systems engineers, software security engineers, security professionals, policymakers, and students.