Now in its fifth edition, bridges the gap between the technical specifications and the real world of designing and programming devices that connect over the Universal Serial Bus (USB). Readers will learn how to select the appropriate USB speed, device class, and hardware for a device; communicate with devices using Visual C# and Visual Basic; use standard host drivers to access devices, including devices that perform vendor-defined tasks; save power with USB's built-in power-conserving protocols; and create robust designs using testing and debugging tools. This fully revised edition also includes instruction on how to increase bus speed with SuperSpeed and SuperSpeedPlus, implement wireless communications, and develop for USB On-The-Go and embedded hosts.

A comprehensive overview of the current evolution of research in algorithms, architectures and compilation for parallel systems is provided by this publication.

The contributions focus specifically on domains where embedded systems are required, either oriented to application-specific or to programmable realisations. These are crucial in domains such as audio, telecom, instrumentation, speech, robotics, medical and automotive processing, image and video processing, TV, multimedia, radar and sonar.

The book will be of particular interest to the academic community because of the detailed descriptions of research results presented. In addition, many contributions feature the "real-life" applications that are responsible for driving research and the impact of their specific characteristics on the methodologies is assessed.

The publication will also be of considerable value to senior design engineers and CAD managers in the industrial arena, who wish either to anticipate the evolution of commercially available design tools or to utilize the presented concepts in their own R&D programmes.

This book integrates new ideas and topics from real time systems, embedded systems, and software engineering to give a complete picture of the whole process of developing software for real-time embedded applications. You will not only gain a thorough understanding of concepts related to microprocessors, interrupts, and system boot process, appreciating the importance of real-time modeling and scheduling, but you will also learn software engineering practices such as model documentation, model analysis, design patterns, and standard conformance. This book is split into four parts to help you learn the key concept of embedded systems; Part one introduces the development process, and includes two chapters on microprocessors and interrupts---fundamental topics for software engineers; Part two is dedicated to modeling techniques for real-time systems; Part three looks at the design of software architectures and Part four covers software implementations, with a focus on POSIX-compliant operating systems. With this book you will learn: The pros and cons of different architectures for embedded systems POSIX real-time extensions, and how to develop POSIX-compliant real time applications How to use real-time UML to document system designs with timing constraints The challenges and concepts related to cross-development Multitasking design and inter-task communication techniques (shared memory objects, message queues, pipes, signals) How to use kernel objects (e.g. Semaphores, Mutex, Condition variables) to address resource sharing issues in RTOS applications The philosophy underpinning the notion of "resource manager" and how to implement a virtual file system using a resource manager The key principles of real-time scheduling and several key algorithms

Given their tremendous success in commercial applications, machine learning (ML) models are increasingly being considered as alternatives to science-based models in many disciplines. Yet, these "black-box" ML models have found limited success due to their inability to work well in the presence of limited training data and generalize to unseen scenarios. As a result, there is a growing interest in the scientific community on creating a new generation of methods that integrate scientific knowledge in ML frameworks. This emerging field, called scientific knowledge-guided ML (KGML), seeks a distinct departure from existing "data-only" or "scientific knowledge-only" methods to use knowledge and data at an equal footing. Indeed, KGML involves diverse scientific and ML communities, where researchers and practitioners from various backgrounds and application domains are continually adding richness to the problem formulations and research methods in this emerging field. Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data provides an introduction to this rapidly growing field by discussing some of the common themes of research in KGML using illustrative examples, case studies, and reviews from diverse application domains and research communities as book chapters by leading researchers. KEY FEATURES First-of-its-kind book in an emerging area of research that is gaining widespread attention in the scientific and data science fields Accessible to a broad audience in data science and scientific and engineering fields Provides a coherent organizational structure to the problem formulations and research methods in the emerging field of KGML using illustrative examples from diverse application domains Contains chapters by leading researchers, which illustrate the cutting-edge research trends, opportunities, and challenges in KGML research from multiple perspectives Enables cross-pollination of KGML problem formulations and research methods across disciplines Highlights critical gaps that require further investigation by the broader community of researchers and practitioners to realize the full potential of KGML

In this era of 5G digital communication, the implementation of industry 4.0 is the need of the hour. The main aim of this industrial revolution is to completely automate the industry for better productivity, correct decision making and increased efficiency. All the concepts of industry 4.0 can only be implemented with the help of Cyber Physical System aka CPS. This is a smart system in which complete mechanism is monitored and controlled by computer-based algorithms. Confidentiality, Integrity and Availability are the three major concern for providing the add on security to any organization or a system. It has become a biggest challenge among the security professionals to secure these cyber physical systems. Hackers and bad guys are planning various kinds of attacks on daily basis on these systems. This book addresses the various security and privacy issues involved in the cyber physical system. There is need to explore the interdisciplinary analysis to ensure the resilience of these systems including different types of cyber threats to these systems. The book highlights the importance of security in preventing, detecting, characterizing and mitigating different types of cyber threats on CPS. The book offers a simple to understand various organized chapters related to the CPS and their security for graduate students, faculty, research scholars and industry professionals. The book offers comprehensive coverage of the most essential topics, including: Cyber Physical Systems and Industrial Internet of Things (IIoT) Role of Internet of Things and their security issues in Cyber Physical Systems. Role of Big data analytic to develop real time solution for CPS. DDoS attacks and their solutions in CPS. Emulator Mininet for simulating CPS. Spark-based DDoS Classification System for Cyber-Physical Systems

This book will take you from basic academic knowledge about magnetics to a proficient understanding of the most recent advances in the technology. This book offers the latest information about disk technology, including: the fundamentals of magnetics, MIG heads, thin film heads, magnetoresistive heads, thin film media, electrical and mechanical integration of these components into a drive, and how to record writing and reading processes magnetically. You'll also learn about giant magnetoresistance, contact recording, and future disk drive industry developments. MAGNETIC DISK DRIVE TECHNOLOGY is an excellent guide for practitioners, researchers, and recent graduate engineers in the field of magnetics.

This book will serve as a guide in understanding workflow scheduling techniques on computing systems such as Cluster, Supercomputers, Grid computing, Cloud computing, Edge computing, Fog computing, and the practical realization of such methods. It offers a whole new perspective and holistic approach in understanding computing systems' workflow scheduling. Expressing and exposing approaches for various process-centric cloud-based applications give a full coverage of most systems' energy consumption, reliability, resource utilization, cost, and application stochastic computation. By combining theory with application and connecting mathematical concepts and models with their resource management targets, this book will be equally accessible to readers with both Computer Science and Engineering backgrounds. It will be of great interest to students and professionals alike in the field of computing system design, management, and application. This book will also be beneficial to the general audience and technology enthusiasts who want to expand their knowledge on computer structure.

Heterogeneous Computing with OpenCL 2.0 teaches OpenCL and parallel programming for complex systems that may include a variety of device architectures: multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units (APUs). This fully-revised edition includes the latest enhancements in OpenCL 2.0 including: * Shared virtual memory to increase programming flexibility and reduce data transfers that consume resources * Dynamic parallelism which reduces processor load and avoids bottlenecks * Improved imaging support and integration with OpenGL Designed to work on multiple platforms, OpenCL will help you more effectively program for a heterogeneous future. Written by leaders in the parallel computing and OpenCL communities, this book explores memory spaces, optimization techniques, extensions, debugging and profiling. Multiple case studies and examples illustrate high-performance algorithms, distributing work across heterogeneous systems, embedded domain-specific languages, and will give you hands-on OpenCL experience to address a range of fundamental parallel algorithms.

Most emerging applications in imaging and machine learning must perform immense amounts of computation while holding to strict limits on energy and power. To meet these goals, architects are building increasingly specialized compute engines tailored for these specific tasks. The resulting computer systems are heterogeneous, containing multiple processing cores with wildly different execution models. Unfortunately, the cost of producing this specialized hardware-and the software to control it-is astronomical. Moreover, the task of porting algorithms to these heterogeneous machines typically requires that the algorithm be partitioned across the machine and rewritten for each specific architecture, which is time consuming and prone to error. Over the last several years, the authors have approached this problem using domain-specific languages (DSLs): high-level programming languages customized for specific domains, such as database manipulation, machine learning, or image processing. By giving up generality, these languages are able to provide high-level abstractions to the developer while producing high-performance output. The purpose of this book is to spur the adoption and the creation of domain-specific languages, especially for the task of creating hardware designs. In the first chapter, a short historical journey explains the forces driving computer architecture today. Chapter 2 describes the various methods for producing designs for accelerators, outlining the push for more abstraction and the tools that enable designers to work at a higher conceptual level. From there, Chapter 3 provides a brief introduction to image processing algorithms and hardware design patterns for implementing them. Chapters 4 and 5 describe and compare Darkroom and Halide, two domain-specific languages created for image processing that produce high-performance designs for both FPGAs and CPUs from the same source code, enabling rapid design cycles and quick porting of algorithms. The final section describes how the DSL approach also simplifies the problem of interfacing between application code and the accelerator by generating the driver stack in addition to the accelerator configuration. This book should serve as a useful introduction to domain-specialized computing for computer architecture students and as a primer on domain-specific languages and image processing hardware for those with more experience in the field.

It's All Analytics! The Foundations of AI, Big Data and Data Science Landscape for Professionals in Healthcare, Business, and Government (978-0-367-35968-3, 325690) Professionals are challenged each day by a changing landscape of technology and terminology. In recent history, especially in the last 25 years, there has been an explosion of terms and methods that automate and improve decision-making and operations. One term, "analytics," is an overarching description of a compilation of methodologies. But AI (artificial intelligence), statistics, decision science, and optimization, which have been around for decades, have resurged. Also, things like business intelligence, online analytical processing (OLAP) and many, many more have been born or reborn. How is someone to make sense of all this methodology and terminology? This book, the first in a series of three, provides a look at the foundations of artificial intelligence and analytics and why readers need an unbiased understanding of the subject. The authors include the basics such as algorithms, mental concepts, models, and paradigms in addition to the benefits of machine learning. The book also includes a chapter on data and the various forms of data. The authors wrap up this book with a look at the next frontiers such as applications and designing your environment for success, which segue into the topics of the next two books in the series.

This book provides a comprehensive overview of blockchain for 6G-enabled network-based applications. Following the key services of blockchain technology, this book will be instrumental to ideate and understand the necessities, challenges, and various case studies of different 6G-based applications. The emphasis is on understanding the contributions of blockchain technology in 6G-enabled applications, and its aim is to give insights into evolution, research directions, challenges, and the ways to empower 6G applications through blockchain. The book consistently emphasizes the missing connection between blockchain and 6G-enabled network applications. The entire ecosystem between these two futuristic technologies is explained in a comprehensive manner. The book constitutes a one-stop guide to students, researchers, and industry professionals. The book progresses from a general introduction toward more technical aspects while remaining easy to understand throughout. Comprehensive elaboration of material is supplemented with examples and diagrams, followed by easily understandable approaches with regard to technical information given thereon. Blockchain and its applications in 6G-enabled applications can drive many powerful solutions to real-world technical, scientific, and social problems. This book presents the most recent and exciting advances in blockchain for 6G-enabled network applications. Overall, this book is a complete outlet and is designed exclusively for professionals, scientists, technologists, developers, designers, and researchers in network technologies around blockchain integration with IoT, blockchain technology, information technology, and 6G-enabled industrial applications. Secondary readers include professionals involved in policy making and administration, security of public data and law, network policy developers, blockchain technology experts, regulators, and decision makers in government administrations.

Written by an author that has real world experience in launching a cyber consulting company. Comprehensive coverage ranging all the way from the legal formation to be used to which segment of the Cybersecurity Industry should be targeted. Explains how CISOs can market their services and get key customers.

Unique selling point: Exploration of the societal and ethical issues surrounding the use and development of digital technology Core audience: IT managers and executives; academic researchers; students of IT Place in the market: Professional title with appeal to academics and students

The Internet of Things (IoT) is an interconnection of several devices, networks, technologies, and human resources to achieve a common goal. A variety of IoT-based applications are being used in different sectors and have succeeded in providing huge benefits to the users. As a revolution, IoT overtook the entire global landscape with its presence in almost every sector, including smart cities, smart grid, intelligent transportation, healthcare, education, and so on. This technological revolution also moved to the machines, converting them into intelligent computers that can make real-time decisions and communicate with each other, forming an Internet of Systems/Machines. The use of secure light-weight protocols will help us in developing environment-friendly and energy-efficient IoT systems. IoT is an emerging and recent area of research, adopted for many applications, and there is a need to investigate further challenges in all aspects of it. This book will provide information on fundamentals, architectures, communication protocols, use of AI, existing applications, and emerging research trends in IoT. It follows a theoretical approach to describe the fundamentals for beginners as well as a practical approach with the implementation of case studies for intermediate and advanced readers. The book will be beneficial for academicians, researchers, developers, and engineers who work in or are interested in fields related to IoT. This book serves as a reference for graduate and postgraduate courses in computer science, computer engineering, and information technology streams.

Written by an author that has real world experience in launching a cyber consulting company. Comprehensive coverage ranging all the way from the legal formation to be used to which segment of the Cybersecurity Industry should be targeted. Explains how CISOs can market their services and get key customers.

This book provides a unified overview of network-on-chip router micro-architecture, the corresponding design opportunities and challenges, and existing solutions to overcome these challenges. The discussion focuses on the heart of a NoC, the NoC router, and how it interacts with the rest of the system. Coverage includes both basic and advanced design techniques that cover the entire router design space including router organization, flow control, pipelined operation, buffering architectures, as well as allocators' structure and algorithms. Router micro-architectural options are presented in a step-by-step manner beginning from the basic design principles. Even highly sophisticated design alternatives are categorized and broken down to simpler pieces that can be understood easily and analyzed. This book is an invaluable reference for system, architecture, circuit, and EDA researchers and developers, who are interested in understanding the overall picture of NoC routers' architecture, the associated design challenges, and the available solutions.

Introduces edge computing, hardware for edge computing AI, edge virtualization techniques Explores edge intelligence and deep learning applications, training and optimization Explains machine learning algorithms for edge Reviews AI on IoT Discusses future edge computing needs

the first book on Unity for embedded systems design and robotics a comprehensive step-by-step guide packed with illustrations each chapter contains a real project

the first book on Unity for embedded systems design and robotics a comprehensive step-by-step guide packed with illustrations each chapter contains a real project

As long as humans write software, the key to successful software security is making the software development program process more efficient and effective. Although the approach of this textbook includes people, process, and technology approaches to software security, Practical Core Software Security: A Reference Framework stresses the people element of software security, which is still the most important part to manage as software is developed, controlled, and exploited by humans. The text outlines a step-by-step process for software security that is relevant to today's technical, operational, business, and development environments. It focuses on what humans can do to control and manage a secure software development process using best practices and metrics. Although security issues will always exist, students learn how to maximize an organization's ability to minimize vulnerabilities in software products before they are released or deployed by building security into the development process. The authors have worked with Fortune 500 companies and have often seen examples of the breakdown of security development lifecycle (SDL) practices. The text takes an experience-based approach to apply components of the best available SDL models in dealing with the problems described above. Software security best practices, an SDL model, and framework are presented in this book. Starting with an overview of the SDL, the text outlines a model for mapping SDL best practices to the software development life cycle (SDLC). It explains how to use this model to build and manage a mature SDL program. Exercises and an in-depth case study aid students in mastering the SDL model. Professionals skilled in secure software development and related tasks are in tremendous demand today. The industry continues to experience exponential demand that should continue to grow for the foreseeable future. This book can benefit professionals as much as students. As they integrate the book's ideas into their software security practices, their value increases to their organizations, management teams, community, and industry.

As long as humans write software, the key to successful software security is making the software development program process more efficient and effective. Although the approach of this textbook includes people, process, and technology approaches to software security, Practical Core Software Security: A Reference Framework stresses the people element of software security, which is still the most important part to manage as software is developed, controlled, and exploited by humans. The text outlines a step-by-step process for software security that is relevant to today's technical, operational, business, and development environments. It focuses on what humans can do to control and manage a secure software development process using best practices and metrics. Although security issues will always exist, students learn how to maximize an organization's ability to minimize vulnerabilities in software products before they are released or deployed by building security into the development process. The authors have worked with Fortune 500 companies and have often seen examples of the breakdown of security development lifecycle (SDL) practices. The text takes an experience-based approach to apply components of the best available SDL models in dealing with the problems described above. Software security best practices, an SDL model, and framework are presented in this book. Starting with an overview of the SDL, the text outlines a model for mapping SDL best practices to the software development life cycle (SDLC). It explains how to use this model to build and manage a mature SDL program. Exercises and an in-depth case study aid students in mastering the SDL model. Professionals skilled in secure software development and related tasks are in tremendous demand today. The industry continues to experience exponential demand that should continue to grow for the foreseeable future. This book can benefit professionals as much as students. As they integrate the book's ideas into their software security practices, their value increases to their organizations, management teams, community, and industry.

This book equips readers with tools for computer architecture of high performance, low power, and high reliability memory hierarchy in computer systems based on emerging memory technologies, such as STTRAM, PCM, FBDRAM, etc. The techniques described offer advantages of high density, near-zero static power, and immunity to soft errors, which have the potential of overcoming the "memory wall." The authors discuss memory design from various perspectives: emerging memory technologies are employed in the memory hierarchy with novel architecture modification; hybrid memory structure is introduced to leverage advantages from multiple memory technologies; an analytical model named "Moguls" is introduced to explore quantitatively the optimization design of a memory hierarchy; finally, the vulnerability of the CMPs to radiation-based soft errors is improved by replacing different levels of on-chip memory with STT-RAMs.

Network infrastructures are growing rapidly to meet the needs of business, but the required repolicing and reconfiguration provide challenges that need to be addressed. The software-defined network (SDN) is the future generation of Internet technology that can help meet these challenges of network management. This book includes quantitative research, case studies, conceptual papers, model papers, review papers, and theoretical backing on SDN. This book investigates areas where SDN can help other emerging technologies deliver more efficient services, such as IoT, industrial IoT, NFV, big data, blockchain, cloud computing, and edge computing. The book demonstrates the many benefits of SDNs, such as reduced costs, ease of deployment and management, better scalability, availability, flexibility and fine-grained control of traffic, and security. The book demonstrates the many benefits of SDN, such as reduced costs, ease of deployment and management, better scalability, availability, flexibility and fine-grained control of traffic, and security. Chapters in the volume address: Design considerations for security issues and detection methods State-of-the-art approaches for mitigating DDos attacks using SDN Big data using Apache Hadoop for processing and analyzing large amounts of data Different tools used for attack simulation Network policies and policy management approaches that are widely used in the context of SDN Dynamic flow tables, or static flow table management A new four-tiered architecture that includes cloud, SDN-controller, and fog computing Architecture for keeping computing resources available near the industrial IoT network through edge computing The impact of SDN as an innovative approach for smart city development More. The book will be a valuable resource for SDN researchers as well as academicians, research scholars, and students in the related areas.

Cloud Computing and Big Data technologies have become the new descriptors of the digital age. The global amount of digital data has increased more than nine times in volume in just five years and by 2030 its volume may reach a staggering 65 trillion gigabytes. This explosion of data has led to opportunities and transformation in various areas such as healthcare, enterprises, industrial manufacturing and transportation. New Cloud Computing and Big Data tools endow researchers and analysts with novel techniques and opportunities to collect, manage and analyze the vast quantities of data. In Cloud and Big Data Analytics, the two areas of Swarm Intelligence and Deep Learning are a developing type of Machine Learning techniques that show enormous potential for solving complex business problems. Deep Learning enables computers to analyze large quantities of unstructured and binary data and to deduce relationships without requiring specific models or programming instructions. This book introduces the state-of-the-art trends and advances in the use of Machine Learning in Cloud and Big Data Analytics. The book will serve as a reference for Data Scientists, systems architects, developers, new researchers and graduate level students in Computer and Data science. The book will describe the concepts necessary to understand current Machine Learning issues, challenges and possible solutions as well as upcoming trends in Big Data Analytics.

Features contributions from thought leaders across academia, industry, and government Focuses on novel algorithms and practical applications