Effective Data Science Infrastructure is a hands-on guide to assembling infrastructure for data science and machine learning applications. It reveals the processes used at Netflix and other data driven companies to manage their cutting edge data infrastructure. As you work through this easy-to-follow guide, you'll set up end-to end infrastructure from the ground up, with a fully customizable process you can easily adapt to your company. You'll learn how you can make data scientists more productive with your existing cloud infrastructure, a stack of open source software, and idiomatic Python. Throughout, you'll follow a human-centric approach focused on user experience and meeting the unique needs of data scientists. About the Technology Turning data science projects from small prototypes to sustainable business processes requires scalable and reliable infrastructure. This book lays out the workflows, components, and methods of the full infrastructure stack for data science, from data warehousing and scalable compute to modeling frameworks.

This book contains extended and revised versions of the best papers presented during the fourteenth IFIP TC 10/WG 10.5 International Conference on Very Large Scale Integration. This conference provides a forum to exchange ideas and show industrial and academic research results in microelectronics design. The current trend toward increasing chip integration and technology process advancements brings about stimulating new challenges both at the physical and system-design levels.

This book constitutes refereed proceedings of the 3rd International Conference on Recent Trends in Advanced Computing - Artificial Intelligence and Technologies. This book covers a wide range of topics-vision, analytics, robotics, networking, health care, current pandemic issues of COVID-19, and cutting-edge technologies connected to cybersecurity in digital manufacturing and Industry 4.0. The contents of this book will be useful to researchers from industry and academia. The volume includes novel contributions and the latest developments from researchers across industry and academia. The book will serve as a valuable reference resource for academics and researchers across the globe.

This book offers an accessible introduction and practical guide to Voice over Internet Protocol (VoIP) technology, providing readers with the know-how to solve the problems encountered in applying VoIP technology across all types of network. It incorporates the latest research findings and brings readers up to date with the challenges that are faced by researchers developing novel applications of VoIP. The authors discuss the general architecture of VoIP technology, along with its application and relevance in conventional and emerging wireless communication networks, including Wireless Local Area Networks (WLANs), Worldwide Interoperability for Microwave Access (WiMAX), Long Term Evolution (LTE) and Cognitive Radio Networks. The book also includes Quality of service (QoS) studies under dynamic and unpredictable network conditions, which examine the reliability of both legacy systems And the upcoming pervasive computing systems. Further, it explains how the heuristic-based learning algorithms that are used in VoIP communications may help develop today's technology in the area of autonomous systems. This book is a valuable source of information for academics and researchers, as it provides state-of-theart research in VoIP technology. It is also of interest to network designers, application architects, and service providers looking for a coherent understanding of VoIP across a wide range of devices, network applications and user categories.

Data lakes and warehouses have become increasingly fragile, costly, and difficult to maintain as data gets bigger and moves faster. Data meshes can help your organization decentralize data, giving ownership back to the engineers who produced it. This book provides a concise yet comprehensive overview of data mesh patterns for streaming and real-time data services. Authors Hubert Dulay and Stephen Mooney examine the vast differences between streaming and batch data meshes. Data engineers, architects, data product owners, and those in DevOps and MLOps roles will learn steps for implementing a streaming data mesh, from defining a data domain to building a good data product. Through the course of the book, you'll create a complete self-service data platform and devise a data governance system that enables your mesh to work seamlessly. With this book, you will: Design a streaming data mesh using Kafka Learn how to identify a domain Build your first data product using self-service tools Apply data governance to the data products you create Learn the differences between synchronous and asynchronous data services Implement self-services that support decentralized data

Gives broad perspective on 5G communications with a focus on smart cities Discusses artificial intelligence in future wireless communication and its applications Provides a systemic and comprehensive coverage of 6G technologies, challenges and use cases Explores role of future wireless in safety, health, and transport in smart cities Includes case studies of future wireless communications

In this book, three different methods are presented to enhance the capacity and coverage area in LTE-A cellular networks. The scope involves the evaluation of the effect of the RN location in terms of capacity and the determination of the optimum location of the relay that provides maximum achievable data rate for users with limited interference at the cell boundaries. This book presents a new model to enhance both capacity and coverage area in LTE-A cellular network by determining the optimum location for the RN with limited interference. The new model is designed to enhance the capacity of the relay link by employing two antennas in RN. This design enables the relay link to absorb more users at cell edge regions. An algorithm called the Balance Power Algorithm (BPA) is developed to reduce MR power consumption. The book pertains to postgraduate students and researchers in wireless & mobile communications.

This book provides an overview of the latest research and development of new technologies for cognitive radio, mobile communications, and wireless networks. The contributors discuss the research and requirement analysis and initial standardization work towards 5G cellular systems and the capacity problems it presents. They show how cognitive radio, with the capability to flexibly adapt its parameters, has been proposed as the enabling technology for unlicensed secondary users to dynamically access the licensed spectrum owned by legacy primary users on a negotiated or an opportunistic basis. They go on to show how cognitive radio is now perceived in a much broader paradigm that will contribute to solve the resource allocation problem that 5G requirements raise. The chapters represent hand-selected expanded papers from EAI sponsored and hosted conferences such as the 12th EAI International Conference on Mobile and Ubiquitous Systems, the 11th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, the 10th International Conference on Cognitive Radio Oriented Wireless Networks, the 8th International Conference on Mobile Multimedia Communications, and the EAI International Conference on Software Defined Wireless Networks and Cognitive Technologies for IoT.

This book presents the basics of both NAND flash storage and machine learning, detailing the storage problems the latter can help to solve. At a first sight, machine learning and non-volatile memories seem very far away from each other. Machine learning implies mathematics, algorithms and a lot of computation; non-volatile memories are solid-state devices used to store information, having the amazing capability of retaining the information even without power supply. This book will help the reader understand how these two worlds can work together, bringing a lot of value to each other. In particular, the book covers two main fields of application: analog neural networks (NNs) and solid-state drives (SSDs). After reviewing the basics of machine learning in Chapter 1, Chapter 2 shows how neural networks can mimic the human brain; to accomplish this result, neural networks have to perform a specific computation called vector-by-matrix (VbM) multiplication, which is particularly power hungry. In the digital domain, VbM is implemented by means of logic gates which dictate both the area occupation and the power consumption; the combination of the two poses serious challenges to the hardware scalability, thus limiting the size of the neural network itself, especially in terms of the number of processable inputs and outputs. Non-volatile memories (phase change memories in Chapter 3, resistive memories in Chapter 4, and 3D flash memories in Chapter 5 and Chapter 6) enable the analog implementation of the VbM (also called "neuromorphic architecture"), which can easily beat the equivalent digital implementation in terms of both speed and energy consumption. SSDs and flash memories are strictly coupled together; as 3D flash scales, there is a significant amount of work that has to be done in order to optimize the overall performances of SSDs. Machine learning has emerged as a viable solution in many stages of this process. After introducing the main flash reliability issues, Chapter 7 shows both supervised and un-supervised machine learning techniques that can be applied to NAND. In addition, Chapter 7 deals with algorithms and techniques for a pro-active reliability management of SSDs. Last but not least, the last section of Chapter 7 discusses the next challenge for machine learning in the context of the so-called computational storage. No doubt that machine learning and non-volatile memories can help each other, but we are just at the beginning of the journey; this book helps researchers understand the basics of each field by providing real application examples, hopefully, providing a good starting point for the next level of development.

The high failure rate of enterprise resource planning (ERP) projects is a pressing concern for both academic researchers and industrial practitioners. The challenges of an ERP implementation are particularly high when the project involves designing and developing a system from scratch. Organizations often turn to vendors and consultants for handling such projects but, every aspect of an ERP project is opaque for both customers and vendors. Unlocking the mysteries of building a large-scale ERP system, The Adventurous and Practical Journey to a Large-Scale Enterprise Solution tells the story of implementing an applied enterprise solution. The book covers the field of enterprise resource planning by examining state-of-the-art concepts in software project management methodology, design and development integration policy, and deployment framework, including: A hybrid project management methodology using waterfall as well as a customized Scrum-based approach A novel multi-tiered software architecture featuring an enhanced flowable process engine A unique platform for coding business processes efficiently Integration to embed ERP modules in physical devices A heuristic-based framework to successfully step into the Go-live period Written to help ERP project professionals, the book charts the path that they should travel from project ideation to systems implementation. It presents a detailed, real-life case study of implementing a large-scale ERP and uses storytelling to demonstrate incorrect and correct decisions frequently made by vendors and customers. Filled with practical lessons learned, the book explains the ins and outs of adopting project methodologies. It weaves a tale that features both real-world and scholarly aspects of an ERP implementation.

Whether the source is more industry-based or academic research, there certainly appears to be a growing interest in the field of cryptocurrency. The New York Times had a cover story on March 24, 2022, titled "Time to Enter the Crypto Zone?," and they talked about institutional investors pouring billions into digital tokens, salaries being taken in Bitcoins, and even Bitcoin ATMs in grocery stores. Certainly, there have been ups and downs in crypto, but it has a kind of alluring presence that tempts one to include crypto as part of one’s portfolio. Those who are "prime crypto-curious" investors are usually familiar with the tech/pop culture and feel they want to diversify a bit in this fast-moving market. Even universities are beginning to offer more courses and create "Centers on Cryptocurrency." Some universities are even requiring their students who take a crypto course to pay the course tuition via cryptocurrency. In response to the growing interest and fascination about the crypto industry and cryptocurrency in general, Cryptocurrency Concepts, Technology, and Applications brings together many leading worldwide contributors to discuss a broad range of issues associated with cryptocurrency. The book covers a wide array of crypto-related topics, including: Blockchain NFTs Data analytics and AI Crypto crime Crypto industry and regulation Crypto and public choice Consumer confidence Bitcoin and other cryptocurrencies. Presenting various viewpoints on where the crypto industry is heading, this timely book points out both the advantages and limitations of this emerging field. It is an easy-to-read, yet comprehensive, overview of cryptocurrency in the U.S. and international markets.

This book provides insights on how to approach and utilize data science tools, technologies and methodologies related to artificial intelligence (AI) in industrial contexts. It explains the essence of distributed computing and AI-technologies, and their inter-connections. Description of various technology and methodology approaches, and their purpose and benefits when developing AI-solution in industrial contexts is included. In addition, it summarizes experiences from AI technology deployment projects from several industrial sectors. Features: Presents compendium of methodologies and technologies in Industrial AI and digitalization. Illustrates sensor to actuation approach showing complete cycle, that defines and differences AI and digitalization concept. Covers a broad range of academic and industrial issues within the field of asset management. Discusses impact of Industry 4.0 in other sectors. Includes a dedicated chapter on real-time case studies. This book is aimed at researchers and professionals in industrial and software engineering, network security, AI and ML, engineering managers, operational and maintenance specialists, asset managers, digital and AI manufacturing specialists.

This book provides holistic yet concise information on what modern cognitive radio networks are, how they work, and the possible future directions for them. The authors first present the most generic models of modern cognitive radio networks, taking into consideration their different architectural designs and classifications. While the spectrum resource is shown to be the most important resource for the cognitive radio networks, the book exposes the importance of the other resources that are needed to help drive the technology. The book then discusses in-depth the key tools (such as optimization and queuing theory) and techniques (such as cooperative diversity and relaying) that are being employed to formulate resource problems, investigate solutions, and interpret such solutions for useful and practical modern cognitive radio networks realization. Further, the book studies the impact of modern cognitive radio networks on other emerging technologies -- such as 5G, Internet of Things, and advanced wireless sensor networks -- and discusses the role that cognitive radio networks play in the evolution of smart cities and in the realization of a highly interconnected world. In discussing the future of the cognitive radio networks, the book emphasizes the need to advance new or improved tools, techniques, and solutions to address lingering problems in the aspects of resource realization and utilization, network complexity, network security, etc., which can potentially limit the cognitive radio networks in their stride to becoming one of the most promising technologies for the immediate and near future.

Introduction to Network Simulator NS2 is a primer providing materials for NS2 beginners, whether students, professors, or researchers for understanding the architecture of Network Simulator 2 (NS2) and for incorporating simulation modules into NS2. The authors discuss the simulation architecture and the key components of NS2 including simulation-related objects, network objects, packet-related objects, and helper objects. The NS2 modules included within are nodes, links, SimpleLink objects, packets, agents, and applications. Further, the book covers three helper modules: timers, random number generators, and error models. Also included are chapters on summary of debugging, variable and packet tracing, result compilation, and examples for extending NS2. Two appendices provide the details of scripting language Tcl, OTcl and AWK, as well object oriented programming used extensively in NS2.

Quickly and efficiently prepare for the Google Associate Cloud Engineer certification with the proven Sybex method In the newly updated Second Edition of Google Cloud Certified Associate Cloud Engineer Study Guide, expert engineer and tech educator Dan Sullivan delivers an essential handbook for anyone preparing for the challenging Associate Cloud Engineer exam offered by Google and for those seeking to upgrade their Google Cloud engineering skillset. The book provides readers with coverage of every domain and competency tested by the Associate Cloud Engineer exam, including how to select the right Google compute service from the wide variety of choices, how to choose the best storage option for your services, and how to implement appropriate security controls and network functionality. This guide also offers: A strong emphasis on transforming readers into competent, job-ready applicants, with a focus on building skills in high demand by contemporary employers Concrete test-taking strategies, techniques, and tips to help readers conquer exam anxiety Complimentary access to a comprehensive online learning environment, complete with practice tests A must-have resource for practicing and aspiring Google Cloud engineers, Google Cloud Certified Associate Cloud Engineer Study Guide allows you to prepare for this challenging certification efficiently and completely.

This book reviews the concept of Software-Defined Networking (SDN) by studying the SDN architecture. It provides a detailed analysis of state-of-the-art distributed SDN controller platforms by assessing their advantages and drawbacks and classifying them in novel ways according to various criteria. Additionally, a thorough examination of the major challenges of existing distributed SDN controllers is provided along with insights into emerging and future trends in that area. Decentralization challenges in large-scale networks are tackled using three novel approaches, applied to the SDN control plane presented in the book. The first approach addresses the SDN controller placement optimization problem in large-scale IoT-like networks by proposing novel scalability and reliability aware controller placement strategies. The second and third approaches tackle the knowledge sharing problem between the distributed controllers by suggesting adaptive multilevel consistency models following the concept of continuous Quorum-based consistency. These approaches have been validated using different SDN applications, developed from real-world SDN controllers.

1. Covers latest concepts in intelligent analytics for industry 4.0. 2. Presents the applications of intelligent analytics for various industry 4.0 domains. 3. Covers latest research topics in the field. 4. Written in a comprehensive and simple manner. 5. The text is accompanied by tables and illustrative figures for better understanding of the topic.

‘Mathematically beautiful and elegant yet has much practical application’ — Professor Richard Weber The first mathematical analysis of a queueing problem concerned the use of early telephone switches. Since then, emerging technologies such as those in telecommunications and the manufacturing industry have prompted considerable interest and activity in the field. Much of the current research has been enabled by recent, rapid advances in computer technology making large scale simulations and complex approximations possible. Today, queueing systems play an integral role in the performance evaluation and optimization of computer, communication. manufacturing and transportation systems. Includes:

• Discussion on the fundamental structures of queueing network models
• The latest developments in the field
• Thorough examination of numerous applications
• Exercises at the end of each chapter
• Coverage of queueing networks with signals
• Discussion of future research developments

With the advances in information technology, many networks have, in addition to conventional jobs, signals and messages circulating throughout the system. A signal carries information and instructions and may trigger complex simultaneous events. The objective of this book is to present, in a unified framework, the latest developments in queueing networks with signals, After introducing the foundations in the first four chapters, Chapters 5 through to 8 cover a number of different queueing network models with various features. Chapters 9 to 11 focus on more fundamental structures of queueing networks and Chapter 12 presents a framework for discrete time queueing network models. The text is illustrated throughout with numerous examples. Graduate students in operations research, computer science, electrical engineering and applied mathematics will find this text accessible and invaluable. An essential reference for operation researchers and computer scientists working on queueing problems in computing, manufacturing and communications networks.

In recent decades, the world has witnessed, unprecedented in terms of speed and geographic coverage, diffusion of new information and communication technologies (ICT). The on-going digital revolution pervasively impacts and reshapes societies and economies and therefore deserves special attention and interest. This book provides extensive evidence on information and communication technologies development patterns and dynamics of this process across developed economies over the period 1980 to the present day. It adopts newly developed methodology to identification of the 'critical mass' and isolation of technological takeoff intervals, which are intimately related to the process of technology diffusion. The statistically robust analysis of country-specific data demonstrates the key economic, social and institutional prerequisites of ICT diffusion across examined countries, indicating what factors significantly foster or - reversely - hinder the process.

ATM Network Performance, Second Edition, describes approaches to computer and communication network management at the ATM layer of the protocol hierarchy. The focus is on satisfying quality-of-service requirements for individual connections. Results in both areas of bandwidth scheduling and traffic control are explained. Recent results in end-to-end performance, provisioning for video connections and statistical multiplexing are also described. All of the material has been updated where appropriate and new references added and expanded. Timely updates: Entirely new chapter on ATM switches with an emphasis on scalable-to-terabit switching. New material on round-robin scheduling, jitter control, QoS paradigms as well as special treatment of fluid modeling and variable bit rate channel capacity. Expanded coverage of CBR channels, IP over ATM, and guaranteed-rate performance. Substantial increase in end-of-chapter exercises. Solutions for selected exercises in separate appendix. Complete solutions for all exercises also available from author.

This book provides scientific understanding of the most central techniques used in speech coding both for advanced students as well as professionals with a background in speech audio and or digital signal processing. It provides a clear connection between the Why's?, How's?, and What's, such that the necessity, purpose and solutions provided by tools should be always within sight, as well as their strengths and weaknesses in each respect. Equivalently, this book sheds light on the following perspectives for each technology presented: Objective: What do we want to achieve and especially why is this goal important? Resource / Information: What information is available and how can it be useful? Resource / Platform: What kind of platforms are we working with and what are the capabilities/restrictions of those platforms? This includes properties such as computational, memory, acoustic and transmission capacity of devices used. Solutions: Which solutions have been proposed and how can they be used to reach the stated goals? Strengths and weaknesses: In which ways do the solutions fulfill the objectives and where are they insufficient? Are resources used efficiently? This book concentrates solely on code excited linear prediction and its derivatives since mainstream speech codecs are based on linear prediction It also concentrates exclusively on time domain techniques because frequency domain tools are to a large extent common with audio codecs.

Focusses on prospective scenarios in health to foresight possible futures Addresses the urgent needs of the key population, socio-technical, and health themes Covers health innovative practices as 3D models for surgeries, big data to treat rare diseases, AI robot for heart treatments Explores telemedicine using big data, deep learning, robotics, mobile and remote applications Reviews public health based on predictive analytics and disease trends

This book gives a broad look at both fundamental networking technology and new areas that support it and use it. It is a concise introduction to the most prominent, recent technological topics in computer networking. Topics include network technology such as wired and wireless networks, enabling technologies such as data centers, software defined networking, cloud and grid computing and applications such as networks on chips, space networking and network security. The accessible writing style and non-mathematical treatment makes this a useful book for the student, network and communications engineer, computer scientist and IT professional.

Mobile communications havepermeated the globe in both business and social cultures. In only af ew short years, Japan aloneh ash ad more than ten million subscribers enter the mobilem arket. Such explosive popularity is an indication ofa strong commercial demand for communications in both the tethered and tetherless environments. Accompanying the vibrant growth in mobile communications is the growth in multimedia communications, includingthe Internet. Mobile and multime dia communications technologies are merging, making mobile computing ak ey phrasei n the coming advanced information communication era. Thegrowth i n these dynamic industries shows that achange in our chosen method of commu nications is already well advanced. Reading e mail and connecting to various information feeds have already become a part ofdaily business activities. We are trying to grasp theo verall picture of mobile computing. Its shape and form are just starting to appear as personal digital assistants (PDA), handheld personal computers (HPC), wireless data communication services, and com mercial software designed for mobile environments. We are at the cusp of vast popularization of "computers on the go. " "Any time Anywhere Computing" provides the reader with an understand able explanationo ft he current developments and commercialization of mobile computing. Thec oret ec hnologies and applications needed to un derstand the industry are comprehensively addressed. Thebook emphasizes three infrastruc tures: (1) wireless communication network infrastructure, (2) terminal devices (or "computers on the go"), and (3) software middleware and architectures that support wireless and mobile computing.

This book presents a range of cloud computing platforms for data-intensive scientific applications. It covers systems that deliver infrastructure as a service, including: HPC as a service; virtual networks as a service; scalable and reliable storage; algorithms that manage vast cloud resources and applications runtime; and programming models that enable pragmatic programming and implementation toolkits for eScience applications. Many scientific applications in clouds are also introduced, such as bioinformatics, biology, weather forecasting and social networks. Most chapters include case studies. Cloud Computing for Data-Intensive Applications targets advanced-level students and researchers studying computer science and electrical engineering. Professionals working in cloud computing, networks, databases and more will also find this book useful as a reference.