Intelligent Workloads at the Edge PDF Download

Author: Indraneel Mitra
Publisher: Packt Publishing Ltd
ISBN: 1801818878
Category : Computers
Languages : en
Pages : 374

View

Book Description
Explore IoT, data analytics, and machine learning to solve cyber-physical problems using the latest capabilities of managed services such as AWS IoT Greengrass and Amazon SageMaker Key FeaturesAccelerate your next edge-focused product development with the power of AWS IoT GreengrassDevelop proficiency in architecting resilient solutions for the edge with proven best practicesHarness the power of analytics and machine learning for solving cyber-physical problemsBook Description The Internet of Things (IoT) has transformed how people think about and interact with the world. The ubiquitous deployment of sensors around us makes it possible to study the world at any level of accuracy and enable data-driven decision-making anywhere. Data analytics and machine learning (ML) powered by elastic cloud computing have accelerated our ability to understand and analyze the huge amount of data generated by IoT. Now, edge computing has brought information technologies closer to the data source to lower latency and reduce costs. This book will teach you how to combine the technologies of edge computing, data analytics, and ML to deliver next-generation cyber-physical outcomes. You'll begin by discovering how to create software applications that run on edge devices with AWS IoT Greengrass. As you advance, you'll learn how to process and stream IoT data from the edge to the cloud and use it to train ML models using Amazon SageMaker. The book also shows you how to train these models and run them at the edge for optimized performance, cost savings, and data compliance. By the end of this IoT book, you'll be able to scope your own IoT workloads, bring the power of ML to the edge, and operate those workloads in a production setting. What you will learnBuild an end-to-end IoT solution from the edge to the cloudDesign and deploy multi-faceted intelligent solutions on the edgeProcess data at the edge through analytics and MLPackage and optimize models for the edge using Amazon SageMakerImplement MLOps and DevOps for operating an edge-based solutionOnboard and manage fleets of edge devices at scaleReview edge-based workloads against industry best practicesWho this book is for This book is for IoT architects and software engineers responsible for delivering analytical and machine learning–backed software solutions to the edge. AWS customers who want to learn and build IoT solutions will find this book useful. Intermediate-level experience with running Python software on Linux is required to make the most of this book.

Author: Pethuru Raj
Publisher: CRC Press
ISBN: 1000552691
Category : Computers
Languages : en
Pages : 329

View

Book Description
The strategically sound combination of edge computing and artificial intelligence (AI) results in a series of distinct innovations and disruptions enabling worldwide enterprises to visualize and realize next-generation software products, solutions and services. Businesses, individuals, and innovators are all set to embrace and experience the sophisticated capabilities of Edge AI. With the faster maturity and stability of Edge AI technologies and tools, the world is destined to have a dazzling array of edge-native, people-centric, event-driven, real-time, service-oriented, process-aware, and insights-filled services. Further on, business workloads and IT services will become competent and cognitive with state-of-the-art Edge AI infrastructure modules, AI algorithms and models, enabling frameworks, integrated platforms, accelerators, high-performance processors, etc. The Edge AI paradigm will help enterprises evolve into real-time and intelligent digital organizations. Applied Edge AI: Concepts, Platforms, and Industry Use Cases focuses on the technologies, processes, systems, and applications that are driving this evolution. It examines the implementation technologies; the products, processes, platforms, patterns, and practices; and use cases. AI-enabled chips are exclusively used in edge devices to accelerate intelligent processing at the edge. This book examines AI toolkits and platforms for facilitating edge intelligence. It also covers chips, algorithms, and tools to implement Edge AI, as well as use cases. FEATURES The opportunities and benefits of intelligent edge computing Edge architecture and infrastructure AI-enhanced analytics in an edge environment Encryption for securing information An Edge AI system programmed with Tiny Machine learning algorithms for decision making An improved edge paradigm for addressing the big data movement in IoT implementations by integrating AI and caching to the edge Ambient intelligence in healthcare services and in development of consumer electronic systems Smart manufacturing of unmanned aerial vehicles (UAVs) AI, edge computing, and blockchain in systems for environmental protection Case studies presenting the potential of leveraging AI in 5G wireless communication

Author: Anwesha Mukherjee
Publisher: Springer Nature
ISBN: 3030698939
Category : Computers
Languages : en
Pages : 598

View

Book Description
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.

Author: Hwaiyu Geng
Publisher: John Wiley & Sons
ISBN: 1118436636
Category : Computers
Languages : en
Pages : 720

View

Book Description
Provides the fundamentals, technologies, and best practices in designing, constructing and managing mission critical, energy efficient data centers Organizations in need of high-speed connectivity and nonstop systems operations depend upon data centers for a range of deployment solutions. A data center is a facility used to house computer systems and associated components, such as telecommunications and storage systems. It generally includes multiple power sources, redundant data communications connections, environmental controls (e.g., air conditioning, fire suppression) and security devices. With contributions from an international list of experts, The Data Center Handbook instructs readers to: Prepare strategic plan that includes location plan, site selection, roadmap and capacity planning Design and build "green" data centers, with mission critical and energy-efficient infrastructure Apply best practices to reduce energy consumption and carbon emissions Apply IT technologies such as cloud and virtualization Manage data centers in order to sustain operations with minimum costs Prepare and practice disaster reovery and business continuity plan The book imparts essential knowledge needed to implement data center design and construction, apply IT technologies, and continually improve data center operations.

Author: David Jensen
Publisher: Apress
ISBN: 1484245369
Category : Computers
Languages : en
Pages : 273

View

Book Description
Use a step-by-step process to create and deploy your first Azure IoT Edge solution. Modern day developers and architects in today’s cloud-focused world must understand when it makes sense to leverage the cloud. Computing on the edge is a new paradigm for most people. The Azure IoT Edge platform uses many existing technologies that may be familiar to developers, but understanding how to leverage those technologies in an edge computing scenario can be challenging. Beginning Azure IoT Edge Computing demystifies computing on the edge and explains, through concrete examples and exercises, how and when to leverage the power of intelligent edge computing. It introduces the possibilities of intelligent edge computing using the Azure IoT Edge platform, and guides you through hands-on exercises to make edge computing approachable, understandable, and highly useful. Through user-friendlydiscussion you will not only understand how to build edge solutions, but also when to build them. By explaining some common solution patterns, the decision on when to use the cloud and when to avoid the cloud will become much clearer. What You'll Learn Create and deploy Azure IoT Edge solutions Recognize when to leverage the intelligent edge pattern and when to avoid it Leverage the available developer tooling to develop and debug IoT Edge solutions Know which off-the-shelf edge computing modules are available Become familiar with some of the lesser-known device protocols used in conjunction with edge computing Understand how to securely deploy and bootstrap an IoT Edge deviceExplore related topics such as containers and secure device provisioning Who This Book Is For Developers or architects who want to understand edge computing and when and where to use it. Readers should be familiar with C# or Python and have a high-level understanding of the Azure IoT platform.

Author: Soumya Sen
Publisher: John Wiley & Sons
ISBN: 1118611667
Category : Technology & Engineering
Languages : en
Pages : 533

View

Book Description
A comprehensive text addressing the high demand for network, cloud, and content services through cutting-edge research on data pricing and business strategies Smart Data Pricing tackles the timely issue of surging demand for network, cloud, and content services and corresponding innovations in pricing these services to benefit consumers, operators, and content providers. The pricing of data traffic and other services is central to the core challenges of network monetization, growth sustainability, and bridging the digital divide. In this book, experts from both academia and industry discuss all aspects of smart data pricing research and development, including economic analyses, system development, user behavior evaluation, and business strategies. Smart Data Pricing: • Presents the analysis of leading researchers from industry and academia surrounding the pricing of network services and content. • Discusses current trends in mobile and wired data usage and their economic implications for content providers, network operators, end users, government regulators, and other players in the Internet ecosystem. • Includes new concepts and background technical knowledge that will help researchers and managers effectively monetize their networks and improve user quality-of-experience. • Provides cutting-edge research on business strategies and initiatives through a diverse collection of perspectives. • Combines academic and industry expertise from multiple disciplines and business organizations. The ideas and background of the technologies and economic principles discussed within these chapters are of real value to practitioners, researchers, and managers in identifying trends and deploying new pricing and network management technologies, and will help support managers in identifying new business directions and innovating solutions to challenging business problems.

Author: Qiang Yang
Publisher: Springer Nature
ISBN: 3030630765
Category : Computers
Languages : en
Pages : 291

View

Book Description
This book provides a comprehensive and self-contained introduction to federated learning, ranging from the basic knowledge and theories to various key applications. Privacy and incentive issues are the focus of this book. It is timely as federated learning is becoming popular after the release of the General Data Protection Regulation (GDPR). Since federated learning aims to enable a machine model to be collaboratively trained without each party exposing private data to others. This setting adheres to regulatory requirements of data privacy protection such as GDPR. This book contains three main parts. Firstly, it introduces different privacy-preserving methods for protecting a federated learning model against different types of attacks such as data leakage and/or data poisoning. Secondly, the book presents incentive mechanisms which aim to encourage individuals to participate in the federated learning ecosystems. Last but not least, this book also describes how federated learning can be applied in industry and business to address data silo and privacy-preserving problems. The book is intended for readers from both the academia and the industry, who would like to learn about federated learning, practice its implementation, and apply it in their own business. Readers are expected to have some basic understanding of linear algebra, calculus, and neural network. Additionally, domain knowledge in FinTech and marketing would be helpful.”

Author: Sireesha Muppala
Publisher: Packt Publishing Ltd
ISBN: 1801077762
Category : Computers
Languages : en
Pages : 348

View

Book Description
Overcome advanced challenges in building end-to-end ML solutions by leveraging the capabilities of Amazon SageMaker for developing and integrating ML models into production Key FeaturesLearn best practices for all phases of building machine learning solutions - from data preparation to monitoring models in productionAutomate end-to-end machine learning workflows with Amazon SageMaker and related AWSDesign, architect, and operate machine learning workloads in the AWS CloudBook Description Amazon SageMaker is a fully managed AWS service that provides the ability to build, train, deploy, and monitor machine learning models. The book begins with a high-level overview of Amazon SageMaker capabilities that map to the various phases of the machine learning process to help set the right foundation. You'll learn efficient tactics to address data science challenges such as processing data at scale, data preparation, connecting to big data pipelines, identifying data bias, running A/B tests, and model explainability using Amazon SageMaker. As you advance, you'll understand how you can tackle the challenge of training at scale, including how to use large data sets while saving costs, monitoring training resources to identify bottlenecks, speeding up long training jobs, and tracking multiple models trained for a common goal. Moving ahead, you'll find out how you can integrate Amazon SageMaker with other AWS to build reliable, cost-optimized, and automated machine learning applications. In addition to this, you'll build ML pipelines integrated with MLOps principles and apply best practices to build secure and performant solutions. By the end of the book, you'll confidently be able to apply Amazon SageMaker's wide range of capabilities to the full spectrum of machine learning workflows. What you will learnPerform data bias detection with AWS Data Wrangler and SageMaker ClarifySpeed up data processing with SageMaker Feature StoreOvercome labeling bias with SageMaker Ground TruthImprove training time with the monitoring and profiling capabilities of SageMaker DebuggerAddress the challenge of model deployment automation with CI/CD using the SageMaker model registryExplore SageMaker Neo for model optimizationImplement data and model quality monitoring with Amazon Model MonitorImprove training time and reduce costs with SageMaker data and model parallelismWho this book is for This book is for expert data scientists responsible for building machine learning applications using Amazon SageMaker. Working knowledge of Amazon SageMaker, machine learning, deep learning, and experience using Jupyter Notebooks and Python is expected. Basic knowledge of AWS related to data, security, and monitoring will help you make the most of the book.

Author: Yan Zhang
Publisher: Springer Nature
ISBN: 3030839443
Category : Computers
Languages : en
Pages : 123

View

Book Description
This is an open access book. It offers comprehensive, self-contained knowledge on Mobile Edge Computing (MEC), which is a very promising technology for achieving intelligence in the next-generation wireless communications and computing networks.The book starts with the basic concepts, key techniques and network architectures of MEC. Then, we present the wide applications of MEC, including edge caching, 6G networks, Internet of Vehicles, and UAVs. In the last part, we present new opportunities when MEC meets blockchain, Artificial Intelligence, and distributed machine learning (e.g., federated learning). We also identify the emerging applications of MEC in pandemic, industrial Internet of Things and disaster management.The book allows an easy cross-reference owing to the broad coverage on both the principle and applications of MEC. The book is written for people interested in communications and computer networks at all levels. The primary audience includes senior undergraduates, postgraduates, educators, scientists, researchers, developers, engineers, innovators and research strategists.

Author: Perry Lea
Publisher: Packt Publishing Ltd
ISBN: 1839218878
Category : Computers
Languages : en
Pages : 633

View

Book Description
Learn to design, implement, and secure your IoT infrastructure. Revised and expanded for edge computing. Key FeaturesBuild a complete IoT system that's the best fit for your organizationLearn about different concepts, tech, and trade-offs in the IoT architectural stackUnderstand the theory and implementation of each element that comprises IoT designBook Description Industries are embracing IoT technologies to improve operational expenses, product life, and people's well-being. An architectural guide is needed if you want to traverse the spectrum of technologies needed to build a successful IoT system, whether that's a single device or millions of IoT devices. IoT and Edge Computing for Architects, Second Edition encompasses the entire spectrum of IoT solutions, from IoT sensors to the cloud. It examines modern sensor systems, focusing on their power and functionality. It also looks at communication theory, paying close attention to near-range PAN, including the new Bluetooth® 5.0 specification and mesh networks. Then, the book explores IP-based communication in LAN and WAN, including 802.11ah, 5G LTE cellular, Sigfox, and LoRaWAN. It also explains edge computing, routing and gateways, and their role in fog computing, as well as the messaging protocols of MQTT 5.0 and CoAP. With the data now in internet form, you'll get an understanding of cloud and fog architectures, including the OpenFog standards. The book wraps up the analytics portion with the application of statistical analysis, complex event processing, and deep learning models. The book then concludes by providing a holistic view of IoT security, cryptography, and shell security in addition to software-defined perimeters and blockchains. What you will learnUnderstand the role and scope of architecting a successful IoT deploymentScan the landscape of IoT technologies, from sensors to the cloud and moreSee the trade-offs in choices of protocols and communications in IoT deploymentsBecome familiar with the terminology needed to work in the IoT spaceBroaden your skills in the multiple engineering domains necessary for the IoT architectImplement best practices to ensure reliability, scalability, and security in your IoT infrastructureWho this book is for This book is for architects, system designers, technologists, and technology managers who want to understand the IoT ecosphere, technologies, and trade-offs, and develop a 50,000-foot view of IoT architecture. An understanding of the architectural side of IoT is necessary.