Edge Computing Demystified

This book aims to provide a high-level understanding of the status of Edge computing and a guide for navigating across different projects and working groups related to Edge computing topic.

The success of the Internet of Things and rich cloud services have helped create the need for edge computing, in which data processing occurs in part at the network edge, rather than completely in the cloud. In Edge Computing: A Primer the vision and definition of Edge computing is introduced, as well as several key techniques that enable Edge computing. Then, four applications that benefit from Edge computing are presented as case studies, ranging from smart homes and public safety to medical services, followed by a discussion of several open challenges and opportunities in Edge computing. Finally, several key tools for edge computing such as virtualization and resource management are explained.

This book provides an insight into ways of inculcating the need for applying mobile edge data analytics in bioinformatics and medicine. The book is a comprehensive reference that provides an overview of the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to the healthcare field. Topics include deep learning methods for applications in object detection and identification, object tracking, human action recognition, and cross-modal and multimodal data analysis. High performance computing systems for applications in healthcare are also discussed. The contributors also include information on microarray data analysis, sequence analysis, genomics based analytics, disease network analysis, and techniques for big data Analytics and health information technology.

This reference text presents the state-of-the-art in edge computing, its primitives, devices and simulators, applications, and healthcare-based case studies. The text provides integration of blockchain with edge computing systems and integration of edge with Internet of Things (IoT) and cloud computing. It will facilitate readers to setup edge-based environment and work with edge analytics. It covers important topics, including cluster computing, fog computing, networking architecture, edge computing simulators, edge analytics, privacy-preserving schemes, edge computing with blockchain, autonomous vehicles, and cross-domain authentication. Aimed at senior undergraduate, graduate students and professionals in the fields of electrical engineering, electronics engineering, computer science, and information technology, this text: Discusses edge data storage security with case studies and blockchain integration with the edge computing system Covers theoretical methods with the help of applications, use cases, case studies, and examples Provides healthcare real-time case studies elaborated by utilizing the virtues of homomorphic encryption Discusses real-time interfaces, devices, and simulators in detail

In this book, contributors provide insights into the latest developments of Edge Computing/Mobile Edge Computing, specifically in terms of communication protocols and related applications and architectures. The book provides help to Edge service providers, Edge service consumers, and Edge service developers interested in getting the latest knowledge in the area. The book includes relevant Edge Computing topics such as applications; architecture; services; inter-operability; data analytics; deployment and service; resource management; simulation and modeling; and security and privacy. Targeted readers include those from varying disciplines who are interested in designing and deploying Edge Computing. Features the latest research related to Edge Computing, from a variety of perspectives; Tackles Edge Computing in academia and industry, featuring a variety of new and innovative operational ideas; Provides a strong foundation for researchers to advance further in the Edge Computing domain.

Mobile Edge Computing (MEC) provides cloud-like subscription-oriented services at the edge of mobile network. For low latency and high bandwidth services, edge computing assisted IoT (Internet of Things) has become the pillar for the development of smart environments and their applications such as smart home, smart health, smart traffic management, smart agriculture, and smart city. This book covers the fundamental concept of the MEC and its real-time applications. The book content is organized into three parts: Part A covers the architecture and working model of MEC, Part B focuses on the systems, platforms, services and issues of MEC, and Part C emphases on various applications of MEC. This book is targeted for graduate students, researchers, developers, and service providers interested in learning about the state-of-the-art in MEC technologies, innovative applications, and future research directions.

Understand how to use K3s and k3OS for different use cases and discover best practices for building an edge computing system Key FeaturesA guide to implementing an edge computing environmentReduce latency and costs for real-time applications running at the edgeFind stable and relevant cloud native open source software to complement your edge environmentsBook Description Edge computing is a way of processing information near the source of data instead of processing it on data centers in the cloud. In this way, edge computing can reduce latency when data is processed, improving the user experience on real-time data visualization for your applications. Using K3s, a light-weight Kubernetes and k3OS, a K3s-based Linux distribution along with other open source cloud native technologies, you can build reliable edge computing systems without spending a lot of money. In this book, you will learn how to design edge computing systems with containers and edge devices using sensors, GPS modules, WiFi, LoRa communication and so on. You will also get to grips with different use cases and examples covered in this book, how to solve common use cases for edge computing such as updating your applications using GitOps, reading data from sensors and storing it on SQL and NoSQL databases. Later chapters will show you how to connect hardware to your edge clusters, predict using machine learning, and analyze images with computer vision. All the examples and use cases in this book are designed to run on devices using 64-bit ARM processors, using Raspberry Pi devices as an example. By the end of this book, you will be able to use the content of these chapters as small pieces to create your own edge computing system. What you will learnConfigure k3OS and K3s for development and production scenariosPackage applications into K3s for shipped-node scenariosDeploy in occasionally connected scenarios, from one node to one million nodesManage GitOps for applications across different locationsUse open source cloud native software to complement your edge computing systemsImplement observability event-driven and serverless edge applicationsCollect and process data from sensors at the edge and visualize it into the cloudWho this book is for This book is for engineers (developers and/or operators) seeking to bring the cloud native benefits of GitOps and Kubernetes to the edge. Anyone with basic knowledge of Linux and containers looking to learn Kubernetes using examples applied to edge computing and hardware systems will benefit from this book.

A comprehensive guide to Fog and Edge applications, architectures, and technologies Recent years have seen the explosive growth of the Internet of Things (IoT): the internet-connected network of devices that includes everything from personal electronics and home appliances to automobiles and industrial machinery. Responding to the ever-increasing bandwidth demands of the IoT, Fog and Edge computing concepts have developed to collect, analyze, and process data more efficiently than traditional cloud architecture. Fog and Edge Computing: Principles and Paradigms provides a comprehensive overview of the state-of-the-art applications and architectures driving this dynamic field of computing while highlighting potential research directions and emerging technologies. Exploring topics such as developing scalable architectures, moving from closed systems to open systems, and ethical issues rising from data sensing, this timely book addresses both the challenges and opportunities that Fog and Edge computing presents. Contributions from leading IoT experts discuss federating Edge resources, middleware design issues, data management and predictive analysis, smart transportation and surveillance applications, and more. A coordinated and integrated presentation of topics helps readers gain thorough knowledge of the foundations, applications, and issues that are central to Fog and Edge computing. This valuable resource: Provides insights on transitioning from current Cloud-centric and 4G/5G wireless environments to Fog Computing Examines methods to optimize virtualized, pooled, and shared resources Identifies potential technical challenges and offers suggestions for possible solutions Discusses major components of Fog and Edge computing architectures such as middleware, interaction protocols, and autonomic management Includes access to a website portal for advanced online resources Fog and Edge Computing: Principles and Paradigms is an essential source of up-to-date information for systems architects, developers, researchers, and advanced undergraduate and graduate students in fields of computer science and engineering.

Gain in-depth knowledge of cloud computing concepts and apply them to accelerate your career in any cloud engineering role Key FeaturesGet to grips with key cloud computing concepts, cloud service providers, and best practicesExplore demonstrations for cloud computing models using real-world examplesAdopt the self-paced learning strategy and get industry-ready for cloud engineering rolesPurchase of the print or Kindle book includes a free eBook in the PDF formatBook Description If you want to upskill yourself in cloud computing domains to thrive in the IT industry, then you've come to the right place. Cloud Computing Demystified for Aspiring Professionals helps you to master cloud computing essentials and important technologies offered by cloud service providers needed to succeed in a cloud-centric job role. This book begins with an overview of transformation from traditional to modern-day cloud computing infrastructure, and various types and models of cloud computing. You'll learn how to implement secure virtual networks, virtual machines, and data warehouse resources including data lake services used in big data analytics — as well as when to use SQL and NoSQL databases and how to build microservices using multi-cloud Kubernetes services across AWS, Microsoft Azure, and Google Cloud. You'll also get step-by-step demonstrations of infrastructure, platform, and software cloud services and optimization recommendations derived from certified industry experts using hands-on tutorials, self-assessment questions, and real-world case studies. By the end of this book, you'll be ready to successfully implement cloud computing standardized concepts, services, and best practices in your workplace. What you will learnGain insights into cloud computing essentials and public, private, hybrid, and multi-cloud deployment modelsExplore core cloud computing services such as IaaS, PaaS, and SaaSDiscover major public cloud providers such as AWS, Microsoft, and GoogleUnlock the power of IaaS, PaaS, and SaaS with AWS, Azure, and GCPCreate secure networks, containers, Kubernetes, compute, databases, and API services on cloudDevelop industry-based cloud solutions using real-world examplesGet recommendations on exam preparation for cloud accreditationsWho this book is for The book is for aspiring cloud engineers, as well as college graduates, IT enthusiasts, and beginner-level cloud practitioners looking to get into cloud computing or transforming their career and upskilling themselves in a cloud engineering role in any industry. A basic understanding of networking, database development, and data analysis concepts and experience in programming languages such as Python and C# will help you get the most out of this book.

Edge computing and analytics are fascinating the whole world of computing. Industry and business are keenly embracing this sound concept to develop customer-centric solutions by enhancing their operations, offerings, and outputs. There is a bevy of advancements in this domain that came with the arrival of IoT devices. The seamless convergence of microservices and serverless computing creates vast opportunities. With the help of IoT devices and these other developments, there has become a deep interest in business automation and additional improvisations in edge computing. With the steady growth of edge devices and applications of IoT fog/edge computing and analytics, there are also distinct challenges and threats. Research has been keenly focused on identifying and understanding these issues and shortcomings to bring viable solution approaches and algorithms. Cases on Edge Computing and Analytics describes the latest innovations, improvements, and transformations happening with edge devices and computing. It addresses the key concerns of the edge computing paradigm, how they are processed, and the various technologies and tools empowering edge computing and analytics. While highlighting topics within edge computing such as the key drivers for implementation, computing capabilities, security considerations, and use-cases, this book is ideal for IT industry professionals and project managers, computer scientists, computer engineers, and practitioners, stakeholders, researchers, academicians, and students looking for research on the latest trends and transitions in edge computing.