Tabla de Contenidos: “…Device Communications 12 -- 1.4.4 Video Streaming 12 -- 1.4.5 Voice over LTE (VoLTE) 12 -- 1.4.6 Internet of Things 13 -- 1.4.7 Wearable Systems 13 -- 1.4.8 Cloud Computing 13 -- 1.5 Book Organization 14 -- References 16 -- Part I LTE Femtocells 19 -- 2 LTE Femtocells 21 /Ghazanfar Ali Safdar -- 2.1 Introduction 21 -- 2.1.1 Cross?]…”

Tabla de Contenidos: “…3.5.4 Warranty und Utility -- 3.6 Zusammenfassung -- 3.7 Beispielfragen -- 4 Die vier Dimensionen des Service Management in ITIL 4 -- 4.1 Das Vier-Dimensionen-Modell -- 4.2 Organizations and people/Organisationen und Menschen -- 4.2.1 Menschen und Kultur -- 4.2.2 Kommunikation und Kompetenzen -- 4.3 Information and technology/Informationen und Technologie -- 4.3.1 Einsatz von Technologien -- 4.3.2 Informationsmanagement -- 4.3.3 Zusammenwirken der Dimensionen -- 4.4 Partners and suppliers/Partner und Lieferanten -- 4.4.1 Cloud Computing -- 4.4.2 Service Integration and Management (SIAM) -- 4.5 Value streams and processes/Wertströme und Prozesse -- 4.5.1 Wertströme für das Service Management -- 4.5.1.1 Wertstromanalyse und Lean Management -- 4.5.2 Prozesse -- 4.5.3 Wertströme und Prozesse -- 4.6 Externe Faktoren -- 4.7 Zusammenfassung -- 4.8 Beispielfragen -- 5 Das Service Value System in ITIL 4 -- 5.1 Service Value System -- 5.2 Überblick über das SVS und seine Bestandteile -- 5.2.1 Förderung der Zusammenarbeit -- 5.2.2 Organisatorische Agilität und Resilienz -- 5.2.2.1 Agile Softwareentwicklung in Abgrenzung zur agilen Organisation -- 5.2.2.2 Organisatorische Agilität und Resilienz als Erfolgsfaktoren -- 5.2.2.3 ITIL, Agile und DevOps -- 5.3 Inputs und Outcome des SVS: Opportunity, Demand, Value -- 5.4 Governance -- 5.4.1 Governance und IT Governance -- 5.4.2 Governance im ITIL Service Value System -- 5.5 Service Value Chain -- 5.5.1 Plan -- 5.5.2 Improve -- 5.5.3 Engage -- 5.5.4 Design &amp -- Transition -- 5.5.5 Obtain/Build -- 5.5.6 Deliver &amp -- Support -- 5.6 Continual Improvement -- 5.6.1 Das Continual-Improvement-Modell -- 5.6.1.1 Schritt 1: Wie lautet die Vision? …”

“…Während der sieben Jahre bei Microsoft und der zehn Jahre bei Google hat Joe Beda an GUI-Frameworks, Echtzeit-Sprache und Chat, Telefonie, maschinellem Lernen für Anzeigen und Cloud Computing gearbeitet. Vor allem aber hat er bei Google die Google Compute Engine aus der Taufe gehoben und zusammen mit Brendan Burns und Craig McLuckie Kubernetes geschaffen. …”

Tabla de Contenidos: “…5.4.3.2 Optimization of Φ under fixed F and Vm[k] -- 5.4.4 Numerical results -- 5.4.5 Conclusion -- 5.4.6 Proof of Theorem 5.4.1 -- References -- 6 Artificial intelligence technology in the Internet of things -- 6.1 Introduction -- 6.2 Exploiting deep learning for secure transmission in an underlay cognitive radio network -- 6.2.1 System model and problem formulation -- 6.2.2 Conventional optimization based power allocation approach -- 6.2.2.1 Perfect CSI -- 6.3 Q-learning based task offloading and resources optimization for a collaborative computing system -- 6.3.1 System model and problem formulation -- 6.3.1.1 System model -- 6.3.1.2 Computation model -- 6.3.1.3 Local computing -- 6.3.1.4 Collaborative cloud computing -- 6.3.2 Wireless communication model -- 6.3.3 MDP model of offloading decision process -- 6.3.3.1 State space S -- 6.3.3.2 Action set A -- 6.3.3.3 Policy -- 6.3.3.4 Loss function and reward -- 6.3.4 Communication and computation resources optimization -- 6.3.4.1 Uplink transmission power allocation -- References -- 7 Fog/edge computing technology and big data system with IoT -- 7.1 Introduction -- 7.1.1 MEC: overview and resource allocation -- 7.1.1.1 MEC: overview -- 7.1.1.2 Single-user and multiuser MEC -- 7.1.1.3 MIMO-assisted MEC -- 7.1.2 Massive MIMO-assisted MEC -- 7.1.2.1 Motivation -- 7.1.2.2 State-of-the-art -- 7.2 Edge cache-assisted secure low-latency millimeter wave transmission -- 7.2.1 Related works -- 7.2.2 System model and problem formulation -- 7.2.2.1 System model -- 7.2.3 Problem formulation -- 7.2.3.1 Problem solution -- 7.2.3.2 Beamforming design at the fronthaul link -- 7.2.3.3 Beamforming design at the access link -- 7.2.4 Numerical results -- 7.2.5 Conclusion -- 7.3 Delay minimization for massive MIMO assisted mobile edge computing -- 7.3.1 System model and problem formulation -- 7.3.1.1 System model…”

Tabla de Contenidos: “…16.1 Introduction 523 -- 16.2 Layering as Optimization Decomposition 524 -- 16.3 Cross-Layer Optimization 533 -- 16.4 Optimization Problem Decomposition Methods 543 -- References 554 -- 17 Network Information Theory 557 -- 17.1 Capacity of Ad Hoc Networks 557 -- 17.2 Information Theory and Network Architectures 569 -- 17.3 Cooperative Transmission in Wireless Multihop Ad Hoc Networks 577 -- References 584 -- 18 Stability of Advanced Network Architectures 585 -- 18.1 Stability of Cooperative Cognitive Wireless Networks 585 -- 18.2 System Model 586 -- 18.4 Optimal Control Policy 592 -- 18.5 Achievable Rates 594 -- 18.6 Stabilizing Transmission Policies 598 -- References 605 -- 19 Multi-Operator Spectrum Sharing 607 -- 19.1 Business Models for Spectrum Sharing 607 -- 19.2 Spectrum Sharing in Multi-hop Networks 638 -- References 656 -- 20 Large Scale Networks and Mean Field Theory 659 -- 20.1 MFT for Large Heterogeneous Cellular Networks 659 -- 20.2 Large Scale Network Model Compression 664 -- 20.3 Mean Field Theory Model of Large Scale DTN Networks 668 -- 20.4 Mean Field Modeling of Adaptive Infection Recovery in Multicast DTN Networks 674 -- 20.5 Mean Field Theory for Scale-Free Random Networks 701 -- 20.6 Spectrum Sharing and MFT 709 -- 20.7 Modeling Dynamics of Complex System 711 -- Appendix A.20 Iterative Algorithm to Solve Systems of Nonlinear ODEs (DiNSE-Algorithm) 721 -- Appendix B.20 Infection Rate of Destinations for DNCM 722 -- Appendix C.20 Infection Rate for Basic Epidemic Routing 722 -- References 722 -- 21 mmWave Networks 726 -- 21.1 mmWave Technology in Subcellular Architecture 726 -- 21.2 Microeconomics of Dynamic mmWave Networks 737 -- References 747 -- 22 Cloud Computing in Wireless Networks 750 -- 22.1 Technology Background 750 -- 22.2 System Model 752 -- 22.3 System Optimization 756 -- 22.4 Dynamic Control Algorithm 758 -- 22.5 Achievable Rates 761 -- 22.6 Stabilizing Control Policies 763 -- References 769 -- 23 Wireless Networks and Matching Theory 771.…”

Tabla de Contenidos: “…-- Understanding SoA -- Differentiating microservices from SoA -- From the monolith to microservices -- Microservices principles -- Defining design principles -- Modelled around business capabilities -- Loosely couple -- Single responsibility -- Hiding implementation -- Isolation -- Independently deployable -- Build for failure -- Upstream -- Downstream -- Logging -- Monitoring -- Alerting -- Recovery -- Fallbacks -- Scalability -- Automation -- Domain-Driven Design -- What is Domain-Driven Design -- Ubiquitous language -- Bounded context -- Context mapping -- Using DDD in microservices -- Reactive microservices -- Reactive programming -- Reactive Manifesto -- Responsive -- Resilient -- Elastic -- Message-driven -- Back pressure -- Reactive frameworks -- Reactive Extensions -- Project Reactor -- Java reactive streams -- Akka -- Reactive microservices -- Cloud Native microservices -- Cloud computing -- Containers -- Deployment models -- Private cloud -- Public cloud -- Hybrid cloud -- Service models -- Infrastructure as a Service -- Platform as a Service -- Software as a Service -- Cloud Native microservices -- Summary -- Chapter 2: Getting Started with Spring Boot 2.0 -- Creating a Spring Boot application -- Setting up -- Installing JDK 8 -- UNIX/Mac OS X -- Windows -- Testing the installation -- Installing Maven 3.5 -- Unix /MacOS X -- Windows -- Testing the installation -- Installing IntelliJ IDEA CE 2017.2 -- Using Spring Initializr -- Understanding basic usage -- Reviewing the generated project files -- Maven Files -- Source files -- Resource files -- Gitignore -- Understanding advanced usage -- Using Maven -- Life cycle phases -- Introduction to Maven goals…”

Tabla de Contenidos: “…Chapter 9: Stream Processing with Apache Flink -- Introduction to streaming execution model -- Data processing using the DataStream API -- Execution environment -- Data sources -- Socket-based -- File-based -- Transformations -- map -- flatMap -- filter -- keyBy -- reduce -- fold -- Aggregations -- window -- Global windows -- Tumbling windows -- Sliding windows -- Session windows -- windowAll -- union -- Window join -- split -- Select -- Project -- Physical partitioning -- Custom partitioning -- Random partitioning -- Rebalancing partitioning -- Rescaling -- Broadcasting -- Event time and watermarks -- Connectors -- Kafka connector -- Twitter connector -- RabbitMQ connector -- Elasticsearch connector -- Cassandra connector -- Summary -- Chapter 10: Visualizing Big Data -- Introduction -- Tableau -- Chart types -- Line charts -- Pie chart -- Bar chart -- Heat map -- Using Python to visualize data -- Using R to visualize data -- Big data visualization tools -- Summary -- Chapter 11: Introduction to Cloud Computing -- Concepts and terminology -- Cloud -- IT resource -- On-premise -- Cloud consumers and Cloud providers -- Scaling -- Types of scaling -- Horizontal scaling -- Vertical scaling -- Cloud service -- Cloud service consumer -- Goals and benefits -- Increased scalability -- Increased availability and reliability -- Risks and challenges -- Increased security vulnerabilities -- Reduced operational governance control -- Limited portability between Cloud providers -- Roles and boundaries -- Cloud provider -- Cloud consumer -- Cloud service owner -- Cloud resource administrator -- Additional roles -- Organizational boundary -- Trust boundary -- Cloud characteristics -- On-demand usage -- Ubiquitous access -- Multi-tenancy (and resource pooling) -- Elasticity -- Measured usage -- Resiliency -- Cloud delivery models -- Infrastructure as a Service…”

Tabla de Contenidos: “…. -- Systems for Different Management Groups -- Spotlight On: Organizations: Carbon Lighthouse Lights Up with the Internet of Things (IoT), Big Data, and Cloud Computing -- Systems for Linking the Enterprise -- E-business, E-commerce, and E-government -- 2-3 Understand why systems for collaboration, social business, and knowledge management are so important and the technologies they use. -- What is Collaboration? …”

Tabla de Contenidos: “…Machine generated contents note: Contents Forward Preface 1 -- INTRODUCTIONS AND MOTIVATION 1.1 Introduction 1.2 The book 1.2.1 Objectives 1.2.2 Benefits 1.2.3 Organization 1.2.4 Book Cover 1.2.5 Impact of C-IoT 1.2.6 Summary 1.3 C-IoT Terms of References 1.3.1 Introduction 1.3.2 Need for IoT Framework 1.3.3 C-IoT Domains and Business Apps Model 1.3.4 C-IoT Roadmap 1.3.5 C-IoT Platform and Developer Community 1.3.6 C-IoT Opportunities for Business apps, solutions and systems 1.4 The Future 1.4.1 General Trends 1.4.2 Point Solutions 1.4.3 Collaborative IoT 1.4.4 C-IoT and RFID 1.4.5 C-IoT and Nanotechnology 1.4.6 Cyber-Collaborative IoT (C2-IoT) 1.4.7 C2-IoT and EBOLA Case 1.4.8 Summary 2 -- APPLICATION REQUIREMENTS 2.1 C-IOT Landscape 2.1.1 C-IoT Model and Architecture Layers 2.1.2 C-IoT Model and Enabling Technologies 2.1.3 Definition of key elements 2.1.4 Requirement Considerations 2.1.5 C-IoT System Solution - Requirement Considerations 2.2 Applications Requirement - Use Cases 2.3 Health & Fitness (Lead Example) 2.3.1 Landscape 2.3.2 Health & Fitness - Sensing Requirements 2.3.3 Health & Fitness - Gateway Requirements 2.3.4 Health & Fitness - Service Requirements 2.3.5 Health & Fitness - Solution Considerations 2.3.6 Health & Fitness - System Considerations 2.3.7 Health & Fitness and Hospitals 2.4 Video Surveillance 2.4.1 Landscape 2.4.2 Video Surveillance - Across Home, Industry and Infrastructure 2.4.3 Video Surveillance - Sensing Requirements 2.4.4 Video Surveillance - Gateway Requirements 2.4.5 Video Surveillance - Services 2.4.6 Example: Red Light Camera - Photo Enforcement Camera 2.4.7 Conclusion 2.5 Smart Home & Building 2.5.1 Landscape 2.5.2 Requirement 2.5.3 Home - Sensing Requirements 2.5.4 Home - Gateway Requirements 2.5.5 Home - Services 2.6 Smart Energy 2.6.1 Landscape 2.6.2 Requirements 2.6.3 Smart Energy - Sensing Requirements 2.6.4 Smart Energy - Gateway Requirements 2.6.5 Smart Energy - Services 2.6.6 The Smart Energy App 2.6.7 Smart Energy and Network Security 2.7 Track & Monitor 2.7.1 Landscape 2.7.2 Track & Monitory - Sensing Requirements 2.7.3 Track & Monitor - Services 2.7.4 Track & Monitor - Solution Considerations 2.7.5 Track & Monitor - Examples 2.8 Smart Factory/Manufacturing 2.8.1 Factory Automation - Robot 2.8.2 Caregiver and Robot 2.8.3 Industrial Robot 2.9 Others: Smart Car, Smart Truck and Smart City 2.9.1 Smart Car 2.9.2 Smart Roadside 2.9.3 Drone 2.9.4 Machine Vision 2.9.5 Smart City 3 -- C-IOT APPLICATIONS AND SERVICES 3.1 Smart IoT Application Use Cases 3.1.1 Health monitoring - Individual level (Fitness/Health Tracking wearables) 3.1.2 Health Monitoring at Business level (used in clinic) 3.1.3 Home and Building Automation - Individual level (Smart Home) 3.1.3.1 Smart Thermostat (Smart Energy Management) 3.1.3.2 Smart Smoke Alarm (Safety) 3.1.3.3 Smart IP Camera for Video Surveillance (Security) 3.1.3.4 Smart Service Robots at Consumer level - Roombas iRobot 3.1.3.5 Smart Home Gateway (Scalable for Smart Building Automation) 3.1.3.6 Smart Building Automation 3.1.4 Smart Energy and Smart Grid 3.1.5 Smart Energy Gateways 3.1.6 Industrial and Factory Automation 3.1.7 Smart Transportation & Fleet Logistics (Connected Cars - V2X: V2V, V2I) 3.1.8 Smart City 3.2 Smart IoT Platform 3.2.2 Smart IoT Software Gateway Platform 3.2.3 Smart Sensor Fusion Platform 3.3 Secured C-IoT Software Platform 3.3.1 C-IoT Security - Example on Smart Energy 3.3.2 Securing NAN (Metrology-to-Concentrator) 3.3.3 Securing Home Area Network (HAN) 3.3.4 Securing WAN (Concentrator-to-Sub Station/Utility Servers) 3.3.5 Platform Solution for Concentrator 3.3.6 Platform Solution for Sub Station/Utility Servers 3.3.7 Network Topology and IP Addressing: WAN 3.3.8 Security on the Concentrator and Utility Servers 3.3.9 Summary on C-IoT Security 4 -- IOT REFERENCE DESIGN KIT 5 -- C-IOT CLOUD-BASED SERVICES AND END DEVICE DIVERSIITY 5.1 C-IoT Cloud Based Services 5.1.1 Introduction and Drivers to C-IoT Service Platform 5.1.2 Classes of C-IoT Cloud Computing 5.1.3 C-IoT Innovative and Collaborative Services 5.1.4 The Emerging Data Centre LAN 5.2 C-IoT User Device Diversity 5.2.1 Introduction 5.2.2 C-IoT Developers/Platform 5.2.3 Wearable Devices - Individual 5.2.4 Harvesting (Self-powered nodes) - Infrastructure Applications 5.2.5 Embedded Devices and Servers 5.2.6 Performing Sentiment Analysis Using Big Data 5.2.7 Far-Reaching Consequence 5.2.8 Collaboration 6 -- IMPACT OF C-IOT AND TIPS 6.1 Impact on Business Process Productivity and Smart of Digital Life 6.1.1 Individual 6.1.2 Industry 6.1.3 Infrastructure 6.2 Considerations of developing Differentiated C-IoT Solutions 6.2.1 Software Processes and Platform 6.2.3 Standardization 6.2.4 Advertising Ecosystem Value Exchange 6.2.5 Opportunity with Industry Supply Chain for Material Handling 6.3 Practical Tips in maintaining Digital Life Style 6.3.1 Mobile and Wearable Computing 6.3.2 Robotics and Automation 6.3.3 Sensors and C-IoT 6.3.4 BIG Data and Predictive Analysis 6.3.5 The Changing Workforce 6.3.6 Sustainability 7 -- CONCLUSION 7.1 Simple C-IoT Domains and Model 7.2 Disruptive Business Applications of C-IoT 7.3 A New LifeStyle 7.4 Development Platform 7.5 C-IoT emerging Standards, Consortiums and other Initiatives 7.5.1 C-IoT Emerging Standards 7.5.2 C-IoT Emerging Consortiums 7.5.3 Forums, Workshops, and other Initiatives 7.5.4 C-IoT and Radio Communications 7.5.5 C-IoT and Nanotechnology 7.5.6 C-IoT and Security 7.6 Final Note References About the Authors Index …”

Tabla de Contenidos: “…. -- 2.8.Social media -- 2.9.Comercio electrónico -- 2.10.Movilidad -- 2.11.Puesto de trabajo digital -- 2.12.Técnica de carrera: lo que tienes que interiorizar -- Capítulo 3 Tendencias digitales -- 3.1.Esto se mueve -- 3.2.Cloud computing -- ¿Qué es eso de la nube? -- La TI como servicio -- Nubes privadas, públicas e híbridas -- Bases tecnológicas. …”

Tabla de Contenidos: “…s Method 7.5 Discussion 7.6 Conclusion References Part Four Multiobjective Optimization 8 Interactive Approaches Applied to Multiobjective Evolutionary Algorithms 8.1 Introduction 8.1.1 Methods Analyzed in this Chapter 8.2 Basic Concepts and Notation 8.2.1 Multiobjective Optimization Problems 8.2.2 Classical Interactive Methods 8.3 MOEAs Based on Reference Point Methods 8.3.1 A Weighted Distance Metric 8.3.2 Light Beam Search Combined with NSGA-II 8.3.3 Controlling the Accuracy of the Pareto Front Approximation 8.3.4 Light Beam Search Combined with PSO 8.3.5 A Preference Relation Based on a Weighted Distance Metric 8.3.6 The Chebyshev Preference Relation 8.4 MOEAs Based on Value Function Methods 8.4.1 Progressive Approximation of a Value Function 8.4.2 Value Function by Ordinal Regression 8.5 Miscellaneous Methods 8.5.1 Desirability Functions 8.6 Conclusions and Future Work References 9 Generalized DEA and Computational Intelligence in Multiple Criteria Decision Making 9.1 Introduction 9.2 Generalized Data Envelopment Analysis 9.2.1 Basic DEA Models: CCR, BCC and FDH Models 9.2.2 GDEA Model 9.3 Generation of Pareto Optimal Solutions using Generalized DEA and Computational Intelligence 9.3.1 GDEA in Fitness Evaluation 9.3.2 GDEA in Deciding the Parameters of Multi-objective PSO 9.3.3 Expected Improvement for Multi-objective Optimization Using GDEA 9.4 Summary References 10 Fuzzy Multiobjective Optimization 10.1 Introduction 10.2 Solution Concepts for Multiobjective Programming 10.3 Interactive Multiobjective Linear Programming 10.4 Fuzzy Multiobjective Linear Programming 10.5 Interactive Fuzzy Multiobjective Linear Programming 10.6 Interactive Fuzzy Multiobjective Linear Programming with Fuzzy Parameters 10.7 Interactive Fuzzy Stochastic Multiobjective Linear Programming 10.8 Related Works and Applications References Part Five Applications in Management and Engineering 11 MCDA & Agents: Supporting Effective Resource Federation in Virtual Organizations 11.1 Introduction 11.2 The Intuition of Multiple Criteria Decision Aid in Multi-agent Systems 11.3 Resource Federation Applied 11.3.1 Describing the Problem in a Cloud Computing Context 11.3.2 Problem Modeling 11.3.3 Assessing Agents' Value Function for Resource Federation 11.4 An Illustrative Example 11.5 Conclusions References 12 Fuzzy AHP Using Type II Fuzzy Sets: An Application to Warehouse Location Selection 12.1 Introduction 12.2 Multicriteria Selection 12.2.1 The ELECTRE (E<U+00cc><U+0081>limination Et Choix Traduisant la Realite) Method 12.2.2 PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluations) 12.2.3 TOPSIS (Technique for Order Preference by Similarity to Ideal Situation) 12.2.4 The WSM (Weighted Sum Model) Method 12.2.5 MAUT (Multi-attribute Utility Theory) 12.2.6 AHP (Analytic Hierarchy Process) 12.3 Literature Review on Fuzzy AHP 12.4 Buckley's Type-1 Fuzzy AHP 12.5 Type-2 Fuzzy Sets 12.6 Type-2 Fuzzy AHP 12.7 An Application: Warehouse Location Selection 12.8 Conclusion References 13 Applying Genetic Algorithms to Optimize Energy Efficiency in Buildings 13.1 Introduction 13.2 State-of-the-Art Review 13.3 An Example Case Study 13.3.1 Basic Principles and Problem Definition 13.3.2 Decision Variables 13.3.3 Decision Criteria 13.3.4 Decision Model 13.4 Development and Application of a Genetic Algorithm for the Example Case Study 13.4.1 Development of the Genetic Algorithm 13.4.2 Application of the Genetic Algorithm, Analysis of Results and Discussion 13.5 Conclusions References 14 Nature-Inspired Intelligence for Pareto Optimality Analysis in Portfolio Optimization 14.1 Introduction 14.2 Literature Review 14.3 Methodological Issues 14.4 Pareto Optimal Sets in Portfolio Optimization 14.4.1 Pareto Efficiency 14.4.2 Mathematical Formulation of the Portfolio Optimization Problem 14.5 Computational Results 14.5.1 Experimental Setup 14.5.2 Efficient Frontier 14.6 Conclusion References Index…”

Tabla de Contenidos: “…11.2 Organization of the I/O Function -- 11.3 Operating System Design Issues -- 11.4 I/O Buffering -- 11.5 Disk Scheduling -- 11.6 RAID -- 11.7 Disk Cache -- 11.8 UNIX SVR4 I/O -- 11.9 Linux I/O -- 11.10 Windows I/O -- 11.11 Summary -- 11.12 Key Terms, Review Questions, and Problems -- Chapter 12 File Management -- 12.1 Overview -- 12.2 File Organization and Access -- 12.3 B-Trees -- 12.4 File Directories -- 12.5 File Sharing -- 12.6 Record Blocking -- 12.7 Secondary Storage Management -- 12.8 UNIX File Management -- 12.9 Linux Virtual File System -- 12.10 Windows File System -- 12.11 Android File Management -- 12.12 Summary -- 12.13 Key Terms, Review Questions, and Problems -- PART 6 EMBEDDED SYSTEMS -- Chapter 13 Embedded Operating Systems -- 13.1 Embedded Systems -- 13.2 Characteristics of Embedded Operating Systems -- 13.3 Embedded Linux -- 13.4 TinyOS -- 13.5 Key Terms, Review Questions, and Problems -- Chapter 14 Virtual Machines -- 14.1 Virtual Machine Concepts -- 14.2 Hypervisors -- 14.3 Container Virtualization -- 14.4 Processor Issues -- 14.5 Memory Management -- 14.6 I/O Management -- 14.7 VMware ESXi -- 14.8 Microsoft Hyper-V and Xen Variants -- 14.9 Java VM -- 14.10 Linux Vserver Virtual Machine Architecture -- 14.11 Summary -- 14.12 Key Terms, Review Questions, and Problems -- Chapter 15 Operating System Security -- 15.1 Intruders and Malicious Software -- 15.2 Buffer Overflow -- 15.3 Access Control -- 15.4 UNIX Access Control -- 15.5 Operating Systems Hardening -- 15.6 Security Maintenance -- 15.7 Windows Security -- 15.8 Summary -- 15.9 Key Terms, Review Questions, and Problems -- Chapter 16 Cloud and IoT Operating Systems -- 16.1 Cloud Computing -- 16.2 Cloud Operating Systems -- 16.3 The Internet of Things -- 16.4 IoT Operating Systems -- 16.5 Key Terms and Review Questions -- APPENDICES -- Appendix A Topics in Concurrency…”

Tabla de Contenidos: “…Using the Internet: Making the Most of the Web's Resources -- Part 1: Collaborating and Working on the Web -- Learning Outcome 3.1 You will be able to explain how the Internet works and how it is used for collaboration, communication, commerce, and entertainment purposes -- The Internet and How It Works -- The Origin of the Internet -- Objective 3.1 Describe how the Internet got its start -- How the Internet Works -- Objective 3.2 Explain how data travels on the Internet -- Collaborating and Communicating on the Web -- Mass Communication and Collaboration -- Objective 3.3 Evaluate the tools and technologies used to communicate and collaborate with large groups of people on the web -- Bits&amp -- Bytes: Social Media Influencers -- Sound Byte: Blogging -- Personal Communication on the Web -- Objective 3.4 Summarize the technologies used for personal communications over the web -- Conducting Business on the Web -- Being Productive with Cloud Technologies -- Objective 3.5 Describe how cloud technologies are used to create, store, and share files -- Dig Deeper: Artificial Intelligence and Cloud Computing -- Conducting Business Online -- Objective 3.6 Describe how business is conducted using the Internet -- Bits&amp -- Bytes: Looking for Extra Money? …”

Tabla de Contenidos: “…-- Representation -- Evaluation -- Optimization -- Generalization -- Feature engineering with IoT data -- Dealing with missing values -- Centering and scaling -- Time series handling -- Validation methods -- Cross-validation -- Test set -- Precision, recall, and specificity -- Understanding the bias-variance tradeoff -- Bias -- Variance -- Trade-off and complexity -- Comparing different models to find the best fit using R -- ROC curves -- Area Under the Curve (AUC) -- Random forest models using R -- Random forest key concepts -- Random forest R examples -- Gradient Boosting Machines (GBM) using R -- GBM key concepts -- The Gradient Boosting Machines R example -- Ensemble -- Anomaly detection using R -- Forecasting using ARIMA -- Using R to forecast time series IoT data -- Deep learning -- Use cases for deep learning with IoT data -- A Nickel Tour of deep learning -- Setting up TensorFlow on AWS -- Summary -- Chapter 11: Strategies to Organize Data for Analytics -- Linked Analytical Datasets -- Analytical datasets -- Building analytic datasets -- Linking together datasets -- Managing data lakes -- When data lakes turn into data swamps -- Data refineries -- Developing a progression process -- The data retention strategy -- Goals -- Retention strategies for IoT data -- Reducing accessibility -- Reducing the number of fields -- Reduce the number of records -- The retention strategy example -- Summary -- Chapter 12: The Economics of IoT Analytics -- The economics of cloud computing and open source -- Variable versus fixed costs -- The option to quit -- Cloud costs can escalate quickly -- Monitoring cloud billing closely…”

Tabla de Contenidos: “…Drawbacks, obstacles and issues in edge computing -- 2.10. Edge computing, cloud computing and Internet of Things: some concerns -- 2.11. …”

Tabla de Contenidos: “…. -- 7.1 Introduction and literature review -- 7.2 Materials and methods -- 7.2.1 Logistic regression -- 7.2.2 Gaussian naive Bayes -- 7.2.3 K-Nearest neighbors -- 7.2.4 Support vector classification -- 7.2.5 Radial basis function -- 7.2.6 Artificial neural network -- 7.2.7 Cart algorithm -- 7.2.8 Random forest -- 7.2.9 Gradient boosting machines -- 7.2.10 XGBoost -- 7.2.11 LightGBM -- 7.2.12 CatBoost -- 7.3 Experimental results -- 7.4 Conclusion and future work -- References -- 8 Healthcare cybersecurity challenges: a look at current and future trends -- 8.1 Introduction -- 8.2 The amount of prior works -- 8.3 Difficulties -- 8.3.1 Security assurance for remote work -- 8.3.2 Endpoint device administration -- 8.3.3 The role of humans in cybersecurity -- 8.3.4 A disregard for security -- 8.3.5 Ineffective risk assessment communication at the board level -- 8.3.6 Poor business continuity strategies -- 8.3.7 Ineffective incident response coordination -- 8.3.8 A tight budget and the requirement to provide healthcare services uninterrupted -- 8.3.9 Dangerous medical cyber-physical systems -- 8.4 A review of current and future trends in cybersecurity challenges in healthcare -- 8.5 Discussion -- 8.5.1 Cyber-physical medical systems -- 8.5.2 Data privacy, confidentiality, and consent -- 8.5.3 Cloud computing -- 8.5.4 Malware -- 8.5.5 Security of health application (or "app") -- 8.5.6 Insider danger -- 8.6 Cybersecurity tools, defenses, and mitigation techniques -- 8.6.1 Cryptographic systems or other technological advances -- 8.6.2 Governance and risk assessment -- 8.6.3 Laws or other regulations -- 8.6.4 A comprehensive strategy for proactive cybersecurity culture -- 8.6.5 Instruction and simulated settings…”

Tabla de Contenidos: “…8.5 Advanced MPI functionality to simplify code and enable optimizations -- 8.5.1 Using custom MPI data types for performance and code simplification -- 8.5.2 Cartesian topology support in MPI -- 8.5.3 Performance tests of ghost cell exchange variants -- 8.6 Hybrid MPI plus OpenMP for extreme scalability -- 8.6.1 The benefits of hybrid MPI plus OpenMP -- 8.6.2 MPI plus OpenMP example -- 8.7 Further explorations -- 8.7.1 Additional reading -- 8.7.2 Exercises -- Summary -- Part 3 GPUs: Built to accelerate -- 9 GPU architectures and concepts -- 9.1 The CPU-GPU system as an accelerated computational platform -- 9.1.1 Integrated GPUs: An underused option on commodity-based systems -- 9.1.2 Dedicated GPUs: The workhorse option -- 9.2 The GPU and the thread engine -- 9.2.1 The compute unit is the streaming multiprocessor (or subslice) -- 9.2.2 Processing elements are the individual processors -- 9.2.3 Multiple data operations by each processing element -- 9.2.4 Calculating the peak theoretical flops for some leading GPUs -- 9.3 Characteristics of GPU memory spaces -- 9.3.1 Calculating theoretical peak memory bandwidth -- 9.3.2 Measuring the GPU stream benchmark -- 9.3.3 Roofline performance model for GPUs -- 9.3.4 Using the mixbench performance tool to choose the best GPU for a workload -- 9.4 The PCI bus: CPU to GPU data transfer overhead -- 9.4.1 Theoretical bandwidth of the PCI bus -- 9.4.2 A benchmark application for PCI bandwidth -- 9.5 Multi-GPU platforms and MPI -- 9.5.1 Optimizing the data movement between GPUs across the network -- 9.5.2 A higher performance alternative to the PCI bus -- 9.6 Potential benefits of GPU-accelerated platforms -- 9.6.1 Reducing time-to-solution -- 9.6.2 Reducing energy use with GPUs -- 9.6.3 Reduction in cloud computing costs with GPUs -- 9.7 When to use GPUs -- 9.8 Further explorations -- 9.8.1 Additional reading…”

Tabla de Contenidos: “…-- 1.3.7 Advantages and Disadvantages of AI in Post COVID Era -- 1.4 Conclusion -- References -- 2 Healthcare System 4.0 Perspectives on COVID-19 Pandemic -- 2.1 Introduction -- 2.2 Key Techniques of HCS 4.0 for COVID-19 -- 2.2.1 Artificial Intelligence (AI) -- 2.2.2 The Internet of Things (IoT) -- 2.2.3 Big Data -- 2.2.4 Virtual Reality (VR) -- 2.2.5 Holography -- 2.2.6 Cloud Computing -- 2.2.7 Autonomous Robots -- 2.2.8 3D Scanning -- 2.2.9 3D Printing Technology -- 2.2.10 Biosensors -- 2.3 Real World Applications of HCS 4.0 for COVID-19 -- 2.4 Opportunities and Limitations -- 2.5 Future Perspectives -- 2.6 Conclusion -- References -- 3 Analysis and Prediction on COVID-19 Using Machine Learning Techniques -- 3.1 Introduction -- 3.2 Literature Review -- 3.3 Types of Machine Learning…”

Tabla de Contenidos: “…Frontcover -- Half Title Page -- River Publishers Series in Communications -- Title Page - Digitising the Industry Internet of Things Connecting the Physical, Digital and Virtual Worlds -- Copyright Page -- Dedication -- Contents -- Preface -- Editors Biography -- List of Figures -- List of Tables -- Chapter 1 - Introduction -- Chapter 2 - IoT Ecosystems Implementing Smart Technologies to Drive Innovation for Future Growth and Development -- 2.1 Introduction -- 2.2 Support for IoT Ecosystem Creation -- 2.3 Spurring Innovation in Lead Markets -- 2.4 Outlook -- Chapter 3 - IoT Digital Value Chain Connecting Research, Innovation and Deployment -- 3.1 Internet of Things Vision -- 3.1.1 IoT Common Definition -- 3.1.2 Artificial Intelligence and Cognitive IoT -- 3.1.3 IoT of Robotic Things -- 3.2 IoT Strategic Research and Innovation Directions -- 3.3 IoT Smart Environments and Applications -- 3.3.1 Wearables -- 3.3.2 Smart Health,Wellness and AgeingWell -- 3.3.3 Smart Clothing -- 3.3.4 Smart Buildings and Architecture -- 3.3.5 Smart Energy -- 3.3.6 Smart Mobility and Transport -- 3.3.7 Industrial IoT and Smart Manufacturing -- 3.3.8 Smart Cities -- 3.3.8.1 Open Data and Ecosystem for Smart Cities -- 3.3.8.2 Citizen Centric Smart Cities IoT Applications and Deployments -- 3.3.9 Smart Farming and Food Security -- 3.3.9.1 Business Models and Innovation Ecosystems -- 3.3.9.2 Societal Aspects -- 3.3.9.3 Coordination among Different DGs, Programmes and Member States -- 3.3.9.4 Policy and Regulations -- 3.4 IoT and Related Future Internet Technologies -- 3.4.1 Cloud Computing -- 3.4.2 Edge Computing -- 3.5 Networks and Communication -- 3.5.1 Network Technology -- 3.5.2 Communication Technology -- 3.6 IoT Standardisation -- 3.7 IoT Security -- 3.7.1 IoT Security Framework based on Artificial Intelligence Concepts…”

Tabla de Contenidos: “…Kapitel 8: Verfügbarkeitsmanagement -- 8.1 Kapitelzusammenfassung -- 8.2 Einführung -- 8.3 Richtlinie zum Verfügbarkeitsmanagement -- 8.4 Verfügbarkeit -- 8.4.1 Klassifizierung von Verfügbarkeit -- 8.4.2 Vorgehensweise -- 8.4.3 Berechnung der Verfügbarkeit -- 8.5 Ausfallsicherheit -- 8.6 Ausprägungen von Redundanz -- 8.6.1 Strukturelle Redundanz -- 8.6.2 Funktionelle Redundanz oder unterstützende Redundanz -- 8.6.3 Informationsredundanz -- 8.7 Redundante Hard- und Software -- 8.8 Virtualisierung -- 8.9 Bauliche Maßnahmen zur Steigerung der Verfügbarkeit -- Kapitel 9: Technische IT-Security -- 9.1 Kapitelzusammenfassung -- 9.2 Einführung -- 9.3 Technisch-Organisatorische Maßnahmen -- 9.3.1 Zugangskontrolle -- 9.3.2 Zugriffskontrolle -- 9.3.3 Übertragungskontrolle und Transportkontrolle -- 9.3.4 Eingabekontrolle -- 9.3.5 Verfügbarkeitskontrolle, Wiederherstellbarkeit und Zuverlässigkeit -- 9.3.6 Datenintegrität -- 9.4 Verschlüsselung -- 9.4.1 Begriffsbestimmungen -- 9.4.2 Symmetrische Verschlüsselungssysteme -- 9.4.3 Asymmetrische Verschlüsselungsverfahren -- 9.5 Cloud Computing -- 9.5.1 Dienstleistungen in der Cloud -- 9.5.2 Risikofaktoren -- 9.5.3 Datenschutzrechtliche Aspekte -- 9.5.4 Vertragliche Vereinbarungen -- 9.5.5 Sinnvolle Freigabeprozesse -- 9.6 Betrieb von Firewalls -- 9.6.1 Paketfilter und Application-Gateways -- 9.6.2 Firewall-Regelwerk -- 9.6.3 Internet-Proxyserver -- 9.7 Internetzugang und Nutzung von E-Mail -- 9.7.1 Risikofaktor E-Mail -- 9.7.2 Verschlüsselung von E-Mails -- 9.7.3 Risikofaktor Internetbrowser -- 9.8 Penetrationstests -- 9.9 Digitale Signatur -- 9.10 Intrusion-Detection-Systeme -- 9.11 Wireless LAN -- Kapitel 10: IT-Risikomanagement -- 10.1 Kapitelzusammenfassung -- 10.2 Einführung -- 10.3 IT-Risikomanagement im Unternehmenskontext -- 10.4 Akzeptanz des IT-Risikomanagements -- 10.5 Operatives IT-Risikomanagement…”