This introductory user's guide to systems analysis and systems design focuses on building sustainable information systems to meet tomorrow's needs. It shows how practitioners can apply multiple participatory perspectives in development, so as to avoid future problems. As a practical guide, it is presented to be readily comprehensible and is organized to enable users to concentrate on their goals efficiently, and with minimum theoretical elaboration. The chapters follow the sequence involved in planning an information system, explaining key words, the time involved in each step, ending with a tutorial or exercises.

This introductory user's guide to systems analysis and systems design focuses on building sustainable information systems to meet tomorrow's needs. It shows how practitioners can apply multiple participatory perspectives in development, so as to avoid future problems. As a practical guide, it is presented to be readily comprehensible and is organized to enable users to concentrate on their goals efficiently, and with minimum theoretical elaboration. The chapters follow the sequence involved in planning an information system, explaining key words, the time involved in each step, ending with a tutorial or exercises.

This book focuses on domain-specific heterogeneous reconfigurable architectures, demonstrating for readers a computing platform which is flexible enough to support multiple standards, multiple modes, and multiple algorithms. The content is multi-disciplinary, covering areas of wireless communication, computing architecture, and circuit design. The platform described provides real-time processing capability with reasonable implementation cost, achieving balanced trade-offs among flexibility, performance, and hardware costs. The authors discuss efficient design methods for wireless communication processing platforms, from both an algorithm and architecture design perspective. Coverage also includes computing platforms for different wireless technologies and standards, including MIMO, OFDM, Massive MIMO, DVB, WLAN, LTE/LTE-A, and 5G.

System-on-chip (SoC) technology is revolutionizing the way computers are designed and used, driving down their cost and making them more pervasive than ever before. However, it's extremely challenging for designers to get their SoC designs right the first time. ARM System Architecture, Second Edition gives system designers an authoritative, inside perspective on SoC design -- and on ARM, the world's #1, fastest-growing SoC platform for mobile phones and information appliances. The insights in this book will be crucial to every system designer and ARM licensee seeking to build more effective SoC designs -- and get them to market more quickly. KEY TOPICS: In contrast to most ARM documentation, this book explains not only what ARM is, but why -- and how you can leverage it most effectively. Expert system designer and ARM specialist Steve Furber introduces the key design challenges associated with SoC systems, including memory hierarchy, caches, memory management, on-chip debug, and production test. Next, he presents state-of-the-art ARM-based solutions for each key problem. Furber reviews the entire ARM processor family, helping designers choose the most appropriate solutions; and covers both the ARM and Thumb programming models, providing real-world guidance for developing applications more quickly and effectively. The book includes a helpful review of the fundamentals of computer architecture, as well as valuable coverage of related topics such as digital signal processing and asynchronous design. MARKET:

Enterprise Architecture (EA) frameworks such as TOGAF and Zachman are still valid, but enterprise architects also need to adapt to the new reality of agile, DevOps, and overall disruption through digital transformation. This book will help do just that. The Change to Modern Enterprise Architecture will teach you how to use known frameworks in the new world of digital transformation. Over the course of the book, you'll learn how modern EA is helping drive strategic business decisions, create continuous and agile ("floating") architecture for scalability, and how to address quality and speed in architecture using and integrating DevSecOps frameworks in EA. This book is divided into three parts: the first explains what modern enterprise architecture is and why it's important to any business. It covers the different EA frameworks and explains what they are. In the second part, you will learn how to integrate modern development frameworks into EA, and why this knowledge will enable you to deftly respond to various business challenges. The final section of the book is all about scaling the enterprise using modern enterprise architecture. You will also see how the role of the enterprise architect is changing and how to remain in control of your architecture. Upon completing this book, you'll understand why the enterprise architect is no longer just a role overseeing the architecture strategy of a business, but has become more of a leader in driving engineering excellence. What You'll Learn Integrate DevSecOps as artifact to modern EA Use Enterprise Architecture to scale up your business Understand the changing role of the enterprise architect Define a floating architecture to enhance business agility Who This Book Is For Enterprise architects, IT architects, lead engineers, business architects, business leaders, product managers.

When it comes to data analytics, it pays tothink big. PySpark blends the powerful Spark big data processing engine withthe Python programming language to provide a data analysis platform that can scaleup for nearly any task. Data Analysis with Python and PySpark is yourguide to delivering successful Python-driven data projects. Data Analysis with Python and PySpark is a carefully engineered tutorial that helps you use PySpark to deliver your data-driven applications at any scale. This clear and hands-on guide shows you how to enlarge your processing capabilities across multiple machines with data from any source, ranging from Had oop-based clusters to Excel worksheets. You'll learn how to break down big analysis tasks into manageable chunks and how to choose and use the best PySpark data abstraction for your unique needs. The Spark data processing engine is an amazing analytics factory: raw data comes in,and insight comes out. Thanks to its ability to handle massive amounts of data distributed across a cluster, Spark has been adopted as standard by organizations both big and small. PySpark, which wraps the core Spark engine with a Python-based API, puts Spark-based data pipelines in the hands of programmers and data scientists working with the Python programming language. PySpark simplifies Spark's steep learning curve, and provides a seamless bridge between Spark and an ecosystem of Python-based data science tools.

A comprehensive guide to understanding the standard and most recent advances in the design of reliable computer systems. It is organized into three sections, beginning with an in-depth review of existing reliability techniques and evaluation criteria for both hardware and software. also examined are the models for detecting faults and predicting failures, and the financial considerations which are inherent in the design, purchase, operation, and maintenance of a reliable system.

Bring agility, cost savings, and a competitive edge to your business by migrating your IT infrastructure to AWS. With this practical book, executive and senior leadership and engineering and IT managers will examine the advantages, disadvantages, and common pitfalls when moving your company's operations to the cloud. Author Jeff Armstrong brings years of practical hands-on experience helping dozens of enterprises make this corporate change. You'll explore real-world examples from many organizations that have made-or attempted to make-this wide-ranging transition. Once you read this guide, you'll be better prepared to evaluate your migration objectively before, during, and after the process in order to ensure success. Learn the benefits and drawbacks of migrating to AWS, including the risks to your business and technology Begin the process by discovering the applications and servers in your environment Examine the value of AWS migration when building your business case Address your operational readiness before you migrate Define your AWS account structure and cloud governance controls Create your migration plan in waves of servers and applications Refactor applications that will benefit from using more cloud native resources

In the world of information technology, it is no longer the computer in the classical sense where the majority of IT applications is executed; computing is everywhere. More than 20 billion processors have already been fabricated and the majority of them can be assumed to still be operational. At the same time, virtually every PC worldwide is connected via the Internet. This combination of traditional and embedded computing creates an artifact of a complexity, heterogeneity, and volatility unmanageable by classical means. Each of our technical artifacts with a built-in processor can be seen as a ''Thing that Thinks," a term introduced by MIT's Thinglab. It can be expected that in the near future these billions of Things that Think will become an ''Internet of Things," a term originating from ETH Zurich. This means that we will be constantly surrounded by a virtual "organism" of Things that Think. This organism needs novel, adequate design, evolution, and management means which is also one of the core challenges addressed by the recent German priority research program on Organic Computing.

CUDA for Engineers gives you direct, hands-on engagement with personal, high-performance parallel computing, enabling you to do computations on a gaming-level PC that would have required a supercomputer just a few years ago. The authors introduce the essentials of CUDA C programming clearly and concisely, quickly guiding you from running sample programs to building your own code. Throughout, you'll learn from complete examples you can build, run, and modify, complemented by additional projects that deepen your understanding. All projects are fully developed, with detailed building instructions for all major platforms. Ideal for any scientist, engineer, or student with at least introductory programming experience, this guide assumes no specialized background in GPU-based or parallel computing. In an appendix, the authors also present a refresher on C programming for those who need it. Coverage includes Preparing your computer to run CUDA programs Understanding CUDA's parallelism model and C extensions Transferring data between CPU and GPU Managing timing, profiling, error handling, and debugging Creating 2D grids Interoperating with OpenGL to provide real-time user interactivity Performing basic simulations with differential equations Using stencils to manage related computations across threads Exploiting CUDA's shared memory capability to enhance performance Interacting with 3D data: slicing, volume rendering, and ray casting Using CUDA libraries Finding more CUDA resources and code Realistic example applications include Visualizing functions in 2D and 3D Solving differential equations while changing initial or boundary conditions Viewing/processing images or image stacks Computing inner products and centroids Solving systems of linear algebraic equations Monte-Carlo computations

Over the last fifteen years GIS has become a fully-fledged technology, deployed across a range of application areas. However, although computer advances in performance appear to continue unhindered, data volumes and the growing sophistication of analysis procedures mean that performance will increasingly become a serious concern in GIS. Parallel computing offers a potential solution. However, traditional algorithms may not run effectively in a parallel environment, so utilization of parallel technology is not entirely straightforward. This groundbreaking book examines some of the current strategies facing scientists and engineers at this crucial interface of parallel computing and GIS.; The book begins with an introduction to the concepts, terminology and techniques of parallel processing, with particular reference to GIS. High level programming paradigms and software engineering issues underlying parallel software developments are considered and emphasis is given to designing modular reusable software libraries. The book continues with problems in designing parallel software for GIS applications, potential vector and raster data structures and details the algorithmic design for some major GIS operations. An implementation case study is included, based around a raster generalization problem, which illustrates some of the principles involved. Subsequent chapters review progress in parallel database technology in a GIS environment and the use of parallel techniques in various application areas, dealing with both algorithmic and implementation issues.; "Parallel Processing Algorithms for GIS" should be a useful text for a new generation of GIS professionals whose principal concern is the challenge of embracing major computer performance enhancements via parallel computing. Similarly, it should be an important volume for parallel computing professionals who are increasingly aware that GIS offers a major application domain for their technology.

The latest edition of the definitive guide to the Ada language covers the full details of the core language Ada 2012 as updated by the 2016 ISO Corrigendum and introduces the key new features in Ada 2022. The book is in four parts. It begins by introducing the fundamental concepts for newcomers, before moving onto algorithmic aspects and then structural features such as OOP and multitasking. The fourth part gives details of the standard library and interaction with the external environment. Six complete executable programs illustrate the core features of the language in action. The book concludes with an appendix focussing on the new features in Ada 2022. These new features aid program proof and the efficient use of multicore architectures.

This book discusses and compares several new trends that can be used to overcome Moore's law limitations, including Neuromorphic, Approximate, Parallel, In Memory, and Quantum Computing. The author shows how these paradigms are used to enhance computing capability as developers face the practical and physical limitations of scaling, while the demand for computing power keeps increasing. The discussion includes a state-of-the-art overview and the essential details of each of these paradigms.

Intelligent Vehicular Network and Communications: Fundamentals, Architectures and Solutions begins with discussions on how the transportation system has transformed into today's Intelligent Transportation System (ITS). It explores the design goals, challenges, and frameworks for modeling an ITS network, discussing vehicular network model technologies, mobility management architectures, and routing mechanisms and protocols. It looks at the Internet of Vehicles, the vehicular cloud, and vehicular network security and privacy issues. The book investigates cooperative vehicular systems, a promising solution for addressing current and future traffic safety needs, also exploring cooperative cognitive intelligence, with special attention to spectral efficiency, spectral scarcity, and high mobility. In addition, users will find a thorough examination of experimental work in such areas as Controller Area Network protocol and working function of On Board Unit, as well as working principles of roadside unit and other infrastructural nodes. Finally, the book examines big data in vehicular networks, exploring various business models, application scenarios, and real-time analytics, concluding with a look at autonomous vehicles.

Navigation Design and SEO for Content-Intensive Websites: A Guide for an Efficient Digital Communication presents the characteristics and principal guidelines for the analysis and design of efficient navigation and information access systems on content-intensive websites, such as magazines and other media publications. Furthermore, the book aims to present the tools of information processing, including information architecture (IA) and content categorization systems, so that such designs can ensure a good navigation experience based on the semantic relations between content items. The book also presents best practices in the design of information access systems with regard to their main structures, including search query forms and search result pages. Finally, the book describes the foundations of search engine optimization (SEO), emphasizing SEO oriented to publications focused on communication and the coverage of current affairs, including images and videos.

The dramatic increase in computer performance has been extraordinary, but not for all computations: it has key limits and structure. Software architects, developers, and even data scientists need to understand how exploit the fundamental structure of computer performance to harness it for future applications. Ideal for upper level undergraduates, Computer Architecture for Scientists covers four key pillars of computer performance and imparts a high-level basis for reasoning with and understanding these concepts: Small is fast - how size scaling drives performance; Implicit parallelism - how a sequential program can be executed faster with parallelism; Dynamic locality - skirting physical limits, by arranging data in a smaller space; Parallelism - increasing performance with teams of workers. These principles and models provide approachable high-level insights and quantitative modelling without distracting low-level detail. Finally, the text covers the GPU and machine-learning accelerators that have become increasingly important for mainstream applications.

Information Security Science: Measuring the Vulnerability to Data Compromises provides the scientific background and analytic techniques to understand and measure the risk associated with information security threats. This is not a traditional IT security book since it includes methods of information compromise that are not typically addressed in textbooks or journals. In particular, it explores the physical nature of information security risk, and in so doing exposes subtle, yet revealing, connections between information security, physical security, information technology, and information theory. This book is also a practical risk management guide, as it explains the fundamental scientific principles that are directly relevant to information security, specifies a structured methodology to evaluate a host of threats and attack vectors, identifies unique metrics that point to root causes of technology risk, and enables estimates of the effectiveness of risk mitigation. This book is the definitive reference for scientists and engineers with no background in security, and is ideal for security analysts and practitioners who lack scientific training. Importantly, it provides security professionals with the tools to prioritize information security controls and thereby develop cost-effective risk management strategies.

Big Data: Principles and Paradigms captures the state-of-the-art research on the architectural aspects, technologies, and applications of Big Data. The book identifies potential future directions and technologies that facilitate insight into numerous scientific, business, and consumer applications. To help realize Big Data's full potential, the book addresses numerous challenges, offering the conceptual and technological solutions for tackling them. These challenges include life-cycle data management, large-scale storage, flexible processing infrastructure, data modeling, scalable machine learning, data analysis algorithms, sampling techniques, and privacy and ethical issues.

Any organization with valuable data has been or will be attacked, probably successfully, at some point and with some damage. And, don't all digitally connected organizations have at least some data that can be considered "valuable"? Cyber security is a big, messy, multivariate, multidimensional arena. A reasonable "defense-in-depth" requires many technologies; smart, highly skilled people; and deep and broad analysis, all of which must come together into some sort of functioning whole, which is often termed a security architecture. Secrets of a Cyber Security Architect is about security architecture in practice. Expert security architects have dozens of tricks of their trade in their kips. In this book, author Brook S. E. Schoenfield shares his tips and tricks, as well as myriad tried and true bits of wisdom that his colleagues have shared with him. Creating and implementing a cyber security architecture can be hard, complex, and certainly frustrating work. This book is written to ease this pain and show how to express security requirements in ways that make the requirements more palatable and, thus, get them accomplished. It also explains how to surmount individual, team, and organizational resistance. The book covers: What security architecture is and the areas of expertise a security architect needs in practice The relationship between attack methods and the art of building cyber defenses Why to use attacks and how to derive a set of mitigations and defenses Approaches, tricks, and manipulations proven successful for practicing security architecture Starting, maturing, and running effective security architecture programs Secrets of the trade for the practicing security architecture Tricks to surmount typical problems Filled with practical insight, Secrets of a Cyber Security Architect is the desk reference every security architect needs to thwart the constant threats and dangers confronting every digitally connected organization.

This book brings together a selection of the best papers from the fifteenth edition of the Forum on specification and Design Languages Conference (FDL), which was held in September 2012 at Vienna University of Technology, Vienna, Austria. FDL is a well-established international forum devoted to dissemination of research results, practical experiences and new ideas in the application of specification, design and verification languages to the design, modeling and verification of integrated circuits, complex hardware/software embedded systems, and mixed-technology systems.

Since the publication of the first edition, parallel computing technology has gained considerable momentum. A large proportion of this has come from the improvement in VLSI techniques, offering one to two orders of magnitude more devices than previously possible. A second contributing factor in the fast development of the subject is commercialization. The supercomputer is no longer restricted to a few well-established research institutions and large companies. A new computer breed combining the architectural advantages of the supercomputer with the advance of VLSI technology is now available at very attractive prices. A pioneering device in this development is the transputer, a VLSI processor specifically designed to operate in large concurrent systems.
Parallel Computers 2: Architecture, Programming and Algorithms reflects the shift in emphasis of parallel computing and tracks the development of supercomputers in the years since the first edition was published. It looks at large-scale parallelism as found in transputer ensembles. This extensively rewritten second edition includes major new sections on the transputer and the OCCAM language. The book contains specific information on the various types of machines available, details of computer architecture and technologies, and descriptions of programming languages and algorithms. Aimed at an advanced undergraduate and postgraduate level, this handbook is also useful for research workers, machine designers, and programmers concerned with parallel computers. In addition, it will serve as a guide for potential parallel computer users, especially in disciplines where large amounts of computer time are regularly used.

Enterprise developers face several challenges when it comes to building serverless applications, such as integrating applications and building container images from source. With more than 60 practical recipes, this cookbook helps you solve these issues with Knative--the first serverless platform natively designed for Kubernetes. Each recipe contains detailed examples and exercises, along with a discussion of how and why it works. If you have a good understanding of serverless computing and Kubernetes core resources such as deployment, services, routes, and replicas, the recipes in this cookbook show you how to apply Knative in real enterprise application development. Authors Kamesh Sampath and Burr Sutter include chapters on autoscaling, build and eventing, observability, Knative on OpenShift, and more. With this cookbook, you'll learn how to: Efficiently build, deploy, and manage modern serverless workloads Apply Knative in real enterprise scenarios, including advanced eventing Monitor your Knative serverless applications effectively Integrate Knative with CI/CD principles, such as using pipelines for faster, more successful production deployments Deploy a rich ecosystem of enterprise integration patterns and connectors in Apache Camel K as Kubernetes and Knative components

An all-inclusive survey of the fundamentals of parallel and distributed computing. The use of parallel and distributed computing has increased dramatically over the past few years, giving rise to a variety of projects, implementations, and buzzwords surrounding the subject. Although the areas of parallel and distributed computing have traditionally evolved separately, these models have overlapping goals and characteristics. Parallel and Distributed Computing surveys the models and paradigms in this converging area of parallel and distributed computing and considers the diverse approaches within a common text. Covering a comprehensive set of models and paradigms, the material also skims lightly over more specific details and serves as both an introduction and a survey. Novice readers will be able to quickly grasp a balanced overview with the review of central concepts, problems, and ideas, while the more experienced researcher will appreciate the specific comparisons between models, the coherency of the parallel and distributed computing field, and the discussion of less well-known proposals. Other topics covered include:

• Data parallelism
• Shared-memory programming
• Message passing
• Client/server computing
• Code mobility
• Coordination, object-oriented, high-level, and abstract models
• And much more

Parallel and Distributed Computing is a perfect tool for students and can be used as a foundation for parallel and distributed computing courses. Application developers will find this book helpful to get an overview before choosing a particular programming style to study in depth, and researchers and programmers will appreciate the wealth of information concerning the various areas of parallel and distributed computing.

Model checking is one of the most successful verification techniques and has been widely adopted in traditional computing and communication hardware and software industries. This book provides the first systematic introduction to model checking techniques applicable to quantum systems, with broad potential applications in the emerging industry of quantum computing and quantum communication as well as quantum physics. Suitable for use as a course textbook and for self-study, graduate and senior undergraduate students will appreciate the step-by-step explanations and the exercises included. Researchers and engineers in the related fields can further develop these techniques in their own work, with the final chapter outlining potential future applications.

By adopting the micro frontends approach and designing your web apps as systems of features, you can deliver faster feature development, easier upgrades, and pick and choose the technology you use in your stack. Micro Frontends in Action is your guide to simplifying unwieldy frontends by composing them from small, well-defined units. You'll learn to integrate web applications made up of smaller fragments using tools such as web components or server side includes, how to solve the organizational challenges of micro frontends, and how to create a design system that ensures an end user gets a consistent look and feel for your application. Key Features * Applying integration strategies with iframes, AJAX, server-side includes, web components and the app-shell approach * Optimizing for performance and asset delivery strategies * Designing coherent user interfaces * Migrating to a micro frontends architecture For intermediate web developers, team leaders, and software architects. About the technology The micro frontends approach extends the principles of microservices to frontend development. The application is divided into multiple independent vertical slices-from the database right up to the UI-then integrated using standards such as web components into a single user-facing frontend. Thanks to the smaller scope of a micro frontend, teams can deliver features faster, upgrade more easily, and make their own choices about their technology stack. Michael Geers is a software developer specializing in building user interfaces. He has written software for the web since he was a teenager. In the last few years, he has worked on various customer projects with verticalized architectures. He shares his experiences on this topic at international conferences, in a series of magazine articles, and website.