Bøger i Computing and Networks serien

This book combines experimental and theoretical research on big data recommender systems to help computer scientists develop new concepts and methodologies for complex applications. It includes original scientific contributions in the form of theoretical foundations, comparative analysis, surveys, case studies, techniques and tools.

The authors present a comprehensive review of fog computing systems including energy efficiency and quality of service issues, reliability and fault tolerance, load balancing, and scheduling, utilizing mobile edge computing, internet of things, resource estimation and virtualization in fog computing environments for smart applications.

Intelligent multimedia processing and computer vision have seen an upsurge in interest over the last few years. This book reviews cutting edge research in the areas of intelligent multimedia processing and computer vision techniques and applications with a particular emphasis on interdisciplinary approaches and novel solutions.

This book covers cybersecurity, privacy and control methods and technologies integrated with blockchain and multimedia AI, including encryption and watermarking techniques, wearable-based IoT security methods, multimedia data forensics and video monitoring.

Personal knowledge graphs (PKGs) support the development of innovative digitalized personalized applications, which keep users updated, help them manage their day-to-day activities and facilitate informed decisions. This book systematically explores the global advanced research around PKGs from methodologies to tools and applications.

This book focuses on Explainable AI (XAI) concepts, tools, frameworks, techniques and applications. It introduces knowledge graphs (KG) to support the need for trust and transparency into the functioning of AI systems, and shows how Intelligent applications can be used to greater effect in finance and healthcare.

This edited book reviews the intertwining disciplines of nature-inspired optimization algorithms and bio-inspired soft-computing for real world applications, with the interaction between metaheuristics with complex systems. The authors present methods and techniques in IoT, image processing, smart manufacturing and healthcare.

This book provides an overview of multimedia technologies used in finance and banking, including ML and DL techniques for financial data analysis, fraud and cyber operation countermeasures, concrete applications of NPR for financial data, self-supervised, unsupervised & semi-supervised learning methods and real-world case studies.

Using machine and deep learning techniques the authors introduce pre-processing methods applied to satellite images to identify land cover features, detect object, classify crops, recognize targets, and monitor and support earth resources. Readers will need a basic understanding of computing, remote sensing and image interpretation.

This book covers state of the art interdisciplinary research on key disruptive and interrelated technologies such as Big Data, Edge computing, IoT and Cloud computing. The authors address the challenges from a distributed system perspective, with clear contributions in theory and applications.

In this edited book, the authors present the challenges, technologies, applications and future trends of the artificial intelligence-enabled internet of things (AIoT) in realizing smart and intelligent environments.

This book covers challenges and solutions of autonomic computing trustworthiness from methods and techniques to achieve consistent and reliable system self-management. This is an ideal tutorial guide for independent study with simple and well documented diagrams to explain techniques and processes.

Presenting a comprehensive view of blockchain technologies for network security from principles to core technologies and applications, this book offers unprecedented insights into recent advances and developments in these areas, and how they can make blockchain technologies associated with networks more secure and fit-for-purpose.

This edited book covers analytical techniques for handling the huge amount of data generated by the Internet of Things, from architectures and platforms to security and privacy issues, applications, and challenges as well as future directions.

The primary aim of this book is to provide a timely and coherent account of the recent advances in many-core computing research. Starting with programming models, operating systems and their applications; it presents runtime management techniques, followed by system modelling, verification and testing methods, and architectures and systems.

Big Data Analytics and Software Defined Networking (SDN) are helping to drive the management of data usage of the extraordinary increase of computer processing power provided by Cloud Data Centres (CDCs). This new book investigates areas where Big-Data and SDN can help each other in delivering more efficient services.

Intellectual Property Rights for Engineers explains the general principles behind the law protecting innovation, quoting cases from the engineering domain in order to clarify legal issues.

This book shows how innovations in network analytics, IoTs and cloud computing platforms are being used to ingest, analyse and correlate a myriad of big data across the entire network stack in order to increase quality of service and quality of experience (QoS/QoE) and to improve network performance.

The needs of future digital data and computer systems are expected to be two to three orders of magnitude larger than for today's systems, to take account of unprecedented amounts of heterogeneous hardware, lines of source code, numbers of users, and volumes of data. Ultrascale computing systems (UCS) are a solution. Envisioned as large-scale complex systems joining parallel and distributed computing systems, which can be located at multiple sites and cooperate to provide the required resources and performance to the users, these technologies will extend individual systems to provide the resources that are very much needed.Based on the research work in the COST Action IC 1305 Network for Sustainable Ultrascale Computing (NESUS) this book presents important results and methods towards achieving sustainable UCS. The authors present a wide range of emerging programming models that facilitate the task of scaling and extracting performance on continuously evolving platforms, while providing resilience and fault-tolerant mechanisms to tackle the increasing probability of failures throughout the entire software stack. These methods are needed to achieve scale handling, better programmability and adaptation to rapidly changing underlying computing architecture, data centric programming models, resilience, and energy-efficiency.

In this book, the authors articulate the challenges associated with streaming data and analytics, describe data analytics algorithms and approaches, present edge and fog computing concepts and technologies and show how streaming analytics can be accomplished in edge device clouds. They also delineate several industry use cases.