Network hardware Books

Book SynopsisThis book introduces readers to the fundamentals of the cross-technology coexistence problem in heterogeneous wireless networks. It also highlights a range of mechanisms designed to combat this problem and improve network performance, including protocol design, theoretical analysis, and experimental evaluation.In turn, the book proposes three mechanisms that can be combined to combat the cross-technology coexistence problem and improve network performance. First, the authors present a fast signal identification method. It provides the basis for the subsequent protocol design and allows heterogeneous devices to adopt proper transmission strategies. Second, the authors present two cross-technology interference management mechanisms in both the time domain and the frequency domain, which can mitigate interference and increase transmission opportunities for heterogeneous devices, thus improving network performance. Third, they present a cross-technology communication mechanism based on symbol-level energy modulation, which allows heterogeneous devices to transmit information directly without a gateway, improving transmission efficiency and paving the way for new applications in IoT scenarios. Lastly, they outline several potential research directions to further improve the efficiency of cross-technology coexistence. This book is intended for researchers, computer scientists, and engineers who are interested in the research areas of wireless networking, wireless communication, mobile computing, and Internet of Things. Advanced-level students studying these topics will benefit from the book as well.Table of Contents1. Introduction 1.1 Overview 1.2 Background 1.2.1 The Channel Specifications 1.2.2 The PHY Layer Specifications 1.2.3 The MAC Layer Specifications 1.3 Cross-technology coexistence problem 1.4 Book structure 2. Heterogeneous Signal Identification 2.1 Introduction 2.2 Motivation 2.3 System design 2.3.1 Dataset Construction 2.3.2 Signal identification through FFT features 2.3.3 Signal identification through deep learning 2.4 Experimental evaluation 2.5 Summary 3. Cross-Technology Communication through Symbol-Level Energy Modulation 3.1 Introduction 3.2 Motivation 3.3 System design 3.3.1 Overview 3.3.1 CTC design at the transmitter side 3.3.2 CTC design at the receiver side 3.4 Theoretical analysis 3.5 Experimental evaluation 3.6 Summary 4. Cross-Technology Interference Management in Frequency domain 4.1 Introduction 4.2 Motivation 4.3 System design 4.3.1 Overview 4.3.2 Standard WiFi transmission process 4.3.3 Payload encoding at WiFi transmitter 4.3.4 Process at WiFi transmitter 4.4 Experimental evaluation 4.5 Summary 5. Cross-Technology Interference Management in Time Domain 5.1 Introduction 5.2 Motivation 5.3 System design 5.3.1 Overview 5.3.2 E-CCA design 5.4 Performance Evaluation 5.5 Summary 6. Conclusion and Future Work 6.1 Conclusions 6.2 Future research directions

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Book SynopsisThis two-volume set LNAI 13995 and LNAI 13996 constitutes the refereed proceedings of the 15th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2023, held in Phuket, Thailand, during July 24–26, 2023.The 65 full papers presented in these proceedings were carefully reviewed and selected from 224 submissions. The papers of the 2 volume-set are organized in the following topical sections: Case-Based Reasoning and Machine Comprehension; Computer Vision; Data Mining and Machine Learning; Knowledge Integration and Analysis; Speech and Text Processing; and Resource Management and Optimization.Table of Contents​Case-Based Reasoning and Machine Comprehension.- On the improvement of the reasoning cycle in case-based reasoning.- Exploring incompleteness in Case-Based Reasoning: a strategy for overcoming challenge.- Leveraging both Successes and Failures in Case-Based Reasoning for Optimal Solutions.- Transfer Learning for Abnormal Behaviors Identification in Examination Room from Surveillance Videos: A Case Study in Vietnam.- A Novel Question-Context Interaction Method for Machine Reading Comprehension.- Granular Computing to Forecast Alzheimer’s Disease Distinctive Individual Development.- Computer Vision.- AdVLO: Region selection via Attention-driven for Visual LiDAR Odometry.- Intelligent Retrieval System on Legal Information.- VSNet: Vehicle State Classification for Drone Image with Mosaic Augmentation and Soft-label Assignment.- Creating High-Resolution Adversarial Images against Convolutional Neural Networks with the Noise Blowing-Up Method.- Faster Imputation Using Singular Value Decomposition for Sparse Data.- Combination of deep learning and ambiguity rejection for improving image-based disease diagnosis.- Data Mining and Machine Learning.- Towards Developing an Automated Chatbot for Predicting Legal Case Outcomes: A Deep Learning Approach.- Fuzzy-Based Factor Evaluation System for Momentum Overweight Trading Strategy.- Enhancing Abnormal-Behavior-based Stock Trend Prediction Algorithm with Cost-sensitive Learning Using Genetic Algorithms.- Leveraging Natural Language Processing in Persuasive Marketing.- Direction of the Difference between Bayesian Model Averaging and the Best-Fit Model on Scarce-Data Low-Correlation Churn Prediction.- Tree-based Unified Temporal Erasable-itemset Mining.- Design Recovery of Data Model Hidden in JSON File.- Accurate lightweight calibration methods for mobile low-cost particulate matter sensors.- Generating music for video games with real-time adaptation to gameplay pace.- Detecting Sensitive Data with GANs and Fully Convolutional Networks.- An Unsupervised Deep Learning Framework for Anomaly Detection.- Extracting top-k high utility patterns from multi-level transaction databases.- Lightweight and Efficient Privacy-Preserving Multimodal Representation Inference via Fully Homomorphic Encryption.- Neural Machine Translation with Diversity-enabled Translation Memory.- GIFT4Rec: An effective side Information Fusion Technique apply to Graph neural network for cold-start recommendation.- A Decision Support System for Improving Lung Cancer Prediction based on ANN.- Emotion detection from text in social networks.- Finite Libby-Novick Beta Mixture Model: An MML-Based Approach.- Artificial Intelligences on Automated Context-Brain Recognition with Mobile Detection Devices.- A Novel Meta-Heuristic Search Based on Mutual Information for Filter-Based Feature Selection.- Discovering prevalent co-location patterns without collecting co-location instances.- Integrating Geospatial Tools for Air Pollution Prediction: A Synthetic City Generator Framework for Efficient Modeling and Visualization.- Design of an Automated CNN Composition Scheme with Lightweight Depth-Correlated Convolution for Space-Limited Applications.

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Book SynopsisThis two-volume set LNAI 13995 and LNAI 13996 constitutes the refereed proceedings of the 15th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2023, held in Phuket, Thailand, during July 24–26, 2023. The 65 full papers presented in these proceedings were carefully reviewed and selected from 224 submissions. The papers of the 2 volume-set are organized in the following topical sections: Case-Based Reasoning and Machine Comprehension; Computer Vision; Data Mining and Machine Learning; Knowledge Integration and Analysis; Speech and Text Processing; and Resource Management and Optimization.Table of ContentsKnowledge Integration and Analysis.- A New Data Transformation and Resampling Approach for Prediction of Yield Strength of High-Entropy Alloys.- A Semi-Formal Approach to Describing Semantics of Data Modeling Patterns.- Obfuscating LLVM IR with the Application of Lambda Calculus.- Structural and Compact Latent Representation Learning on Sparse Reward Environments.- A Survey of Explainable Artificial Intelligence Approaches for Sentiment Analysis.- Social collective model of non-internet social networks.- A Data-driven Scheduling Strategy for Mobile Air Quality Monitoring Devices.- Hybrid approaches to sentiment analysis of social media data.- Integrating Ontology-based Knowledge to Improve BiomedicalMulti-Document Summarization Model.- An Improvement of Diachronic Embedding for Temporal Knowledge Graph Completion.- DCA-based weighted bagging: A new ensemble learning approach.- Deep-learning- and GCN-based Aspect-level Sentiment Analysis Methods on Balanced and Unbalanced Datasets.- Applying the Malmquist productivity index model to assess the performance of the coffee enterprise in DakLak Vietnam.- A Cluster-Constrained Graph Convolutional Network for Protein– Protein Association networks.- Fuzzy logic framework for ontology concepts alignment.- Can Ensemble Calibrated Learning enhance Link Prediction? A Study on Commonsense Knowledge.- Multi-criteria Approaches to Explaining Black Box Machine Learning Models.- Improving Loss Function for Polyp Detection Problem.- Flow Plugin Network for Conditional Generation.- Speech and Text Processing.- Investigating the Impact of Parkinson’s Disease on Brain Computations An Online Study of Healthy Controls and PD Patients.- Speech Enhancement using Dynamical Variational AutoEncoder.- Vietnamese Multidocument Summarization using Subgraph Selection-based Approach with Graph-informed Self-attention mechanism.- NegT5: A Cross-Task Text-to-Text Framework for Negation in Question Answering.- An Empirical Study on Punctuation Restoration for English, Mandarin, and Code-switching Speech.- Novel Topic Models for Parallel Topics Extraction from Multilingual Text.- Adapting Code-Switching Language Models with Statistical-Based Text Augmentation.- Improving Hotel Customer Sentiment Prediction by Fusing Review Titles and Contents.- Resource management and optimization.- In support of push-based streaming for the computing continuum.- Effective method of implementing constrained optimization problems using data instances.- Scheduling Deep Learning Training in GPU Cluster Using the Model-similarity-based Policy.

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Book SynopsisThis book constitutes the refereed proceedings of the 22nd International Conference on Cryptology and Network Security, CANS 2023, which was held in October/November 2023 in Augusta, GA, USA.The 25 papers presented were thoroughly revised and selected from the 54 submissions. They are organized in the following topical sections: Schemes I; Basic Primitives; Security; MPC with Cards; Blockchain; MPC and Secret Sharing; Schemes II.Table of ContentsSchemes I.- Forward Security under Leakage Resilience, Revisited.- Anonymous Broadcast Authentication with Logarithmic-order Ciphertexts from LWE.- Signatures with Delegation.- Basic Primitives.- How to Enumerate LWE Keys as Narrow as in Kyber/Dilithium.- Towards Minimizing Non-linearity in Type-II Generalized Feistel Networks.- Hardness of Learning AES with Gradient-based Methods.- Security.- Privacy-Preserving Digital Vaccine Passport .- Exploiting Android Browser.- Are Current CCPA Compliant Banners Conveying User’s Desired Opt-Out Decisions? An Empirical Study of Cookie Consent Banners.- MPC with Cards.- Upper Bounds on the Number of Shuffl for Two-Helping-Card Multi-Input AND Protocols.- Free-XOR in Card-based Garbled Circuits.- Hidden Stream Ciphers and TMTO Attacks on TLS 1.3, DTLS 1.3, QUIC, and Signal.- Differetial cryptanalysis with SAT, SMT, MILP, and CP: a detailed comparison for bit-oriented primitives.- Key Filtering in Cube Attacks from the Implementation Aspect.- New Techniques for Modeling SBoxes: An MILP Approach.- Blockchain.- LucidiTEE: A TEE-Blockchain System for Policy-Compliant Multiparty Computation with Fairness.- Improving Privacy of Anonymous Proof-of-Stake Protocols.- Compact Stateful Deterministic Wallet from Isogeny-based Signature featuring Uniquely Rerandomizable Public Keys.- CTA: Confidetial Transactions Protocol with State Accumulator.- MPC and Secret Sharing.- A Plug-n-Play Framework for Scaling Private Set Intersection to Billion-sized Sets.- Lower Bounds on the Share Size of Leakage Resilient Cheating Detectable Secret Sharing.- Schemes II.- Lattice-based Key-Value Commitment scheme with key-binding and key-hiding.- A Practical Forward-Secure DualRing.- Computable Cryptographic Accumulators and Their Application to Attribute Based Encryption.- A Minor Note on Obtaining Simpler iO Constructions via Depleted Obfuscators.

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Book SynopsisThis book constitutes the refereed proceedings of the 19th Principle and Practice of Data and Knowledge Acquisition Workshop, PKAW 2023, held in conjunction with the 20th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2023), in November 2023, in Jakarta, Indonesia. The 9 full papers and 2 short papers included in this volume were carefully reviewed and selected from 28 initial submissions. They are organized in the topical section such as machine learning, natural language processing, and intelligent systems.Table of ContentsPredicting Peak Demand Days for Asthma-Related Emergency Hospitalisations: A Machine Learning Approach.- Discovering Maximal High Utility Co-location Patterns from Spatial Data.- Exploring the Potential of Image Overlay in Self-Supervised Learning: A Study on SimSiam Networks and Strategies for Preventing Model Collapse.- BoCB: Performance Benchmarking by Analysing Impacts of Cloud Platforms on Consortium Blockchain.- Automated Cattle Behavior Classification Using Wearable Sensors and Machine Learning Approach.- LexiFusedNet: A Unified Approach for Imbalanced Short-text Classification using Lexicon-based Feature Extraction, Transfer Learning and One Class Classifiers.- Information Gerrymandering in Elections.- An Assessment of the Influence of Interaction and Recommendation Approaches on the Formation of Information Filter Bubbles.- Blockchain as a Collaborative Technology - Case Studies in the Real Estate Sector in Vietnam.- Indonesian Forest Fire Data Clustering using Spatiotemporal Data Using Grid Density-Based Clustering Algorithm.

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Book SynopsisThis book constitutes the refereed proceedings of the International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT) which was held in Jeju, Korea in August, 2023. The papers of this volume are organized in topical sections on wired and wireless communication systems, high dimensional data representation and processing, networks and information security, computing techniques for efficient networks design, electronic circuits for communication systems.Table of ContentsTrack 1. Networking and Architectures.- Track 2. Software Systems and Technologies.- Track 3. Algorithms and Applications.- Track 4. Security and Privacy

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Book SynopsisThe 13-volume set LNCS 14425-14437 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023, held in Xiamen, China, during October 13–15, 2023. The 532 full papers presented in these volumes were selected from 1420 submissions. The papers have been organized in the following topical sections: Action Recognition, Multi-Modal Information Processing, 3D Vision and Reconstruction, Character Recognition, Fundamental Theory of Computer Vision, Machine Learning, Vision Problems in Robotics, Autonomous Driving, Pattern Classification and Cluster Analysis, Performance Evaluation and Benchmarks, Remote Sensing Image Interpretation, Biometric Recognition, Face Recognition and Pose Recognition, Structural Pattern Recognition, Computational Photography, Sensing and Display Technology, Video Analysis and Understanding, Vision Applications and Systems, Document Analysis and Recognition, Feature Extraction and Feature Selection, Multimedia Analysis and Reasoning, Optimization and Learning methods, Neural Network and Deep Learning, Low-Level Vision and Image Processing, Object Detection, Tracking and Identification, Medical Image Processing and Analysis. Table of ContentsRSID: A remote sensing image dehazing network.- ContextNet: Learning Context Information for Texture-less Light Field Depth Estimation.- An Efficient Way for Active None-line-of-sight: End-to-end Learned Compressed NLOS Imaging.- DFAR-Net: Dual-Input Three-Branch Attention Fusion Reconstruction Network for Polarized Non-Line-of-Sight Imaging.- EVCPP:Example-driven Virtual Camera Pose Prediction for cloud performing arts scenes.- RBSR: Efficient and Flexible Recurrent Network for Burst Super-Resolution.- WDU-Net: Wavelet-Guided Deep Unfolding Network for Image Compressed Sensing Reconstruction.- Memory-Augmented Spatial-Temporal Consistency Network for Video Anomaly Detection.- Frequency and Spatial Domain Filter Network for Visual Object Tracking.- Enhancing Feature Representation for Anomaly Detection via Local-and-Global Temporal Relations and a Multi-Stage Memory.- DFAformer: A Dual Filtering Auxiliary Transformer for Efficient Online Action Detection in Streaming Videos.- Relation-guided Multi-stage Feature Aggregation Network for Video Object Detection.- Multimodal Local Feature Enhancement Network for Video Summarization.- Asymmetric Attention Fusion for Unsupervised Video Object Segmentatio.- Flow-Guided Diffusion Autoencoder for Unsupervised Video Anomaly detection.- Prototypical Transformer for Weakly Supervised Action Segmentation.- Unimodal-Multimodal Collaborative Enhancement for Audio-Visual Event Localization.- Dual-memory feature aggregation for video object detection.- Going Beyond Closed Sets: A Multimodal Perspective for Video Emotion Analysis.- Temporal-Semantic Context Fusion for Robust Weakly Supervised Video Anomaly Detection.- A Survey: the Sensor-based Method for Sign Language Recognition.- Utilizing Video Word Boundaries and Feature-based Knowledge Distillation Improving Sentence-level Lip Reading.- Denoised Temporal Relation Network for Temporal Action Segmentation.- 3D Lightweight Spatial-Spectral Attention Network for Hyperspectral Image Classification.- Deepfake Detection via Fine-Grained Classification and Global-Local Information Fusion.- Unsupervised Image-to-Image Translation with Style Consistency.- SemanticCrop: Boosting Contrastive Learning via Semantic-cropped Views.- Transformer-based multi-object tracking in unmanned aerial vehicles.- HEI-GAN: A Human-Environment Interaction based GAN for Multimodal Human Trajectory Prediction.- CenterMatch: A Center Matching Method for Semi-supervised Facial Expression Recognition.- Cross-Dataset Distillation with Multi-Tokens for Image Quality Assessment.- Quality-Aware CLIP for Blind Image Quality Assessment.- Multi-Agent Perception via Co-Attentive Communication Mechanism.- DBRNet:Dual-Branch Real-Time Segmentation NetWork For Metal Defect Detection.- MaskDiffuse: Text-guided Face Mask Removal based on Diffusion Models.- Image Generation Based Intra-class Variance Smoothing for Fine-grained Visual Classification.- Cross-Domain Soft Adaptive Teacher for Syn2Real Object Detection.- Dynamic Graph-Driven Heat Diffusion: Enhancing Industrial Semantic Segmentation.- EKGRL: Entity-based Knowledge Graph Representation Learning for Fact-based Visual Question Answering.- Disentangled Attribute Features Vision Transformer for Pedestrian Attribute Recognition.- A high-resolution network based on feature redundancy reduction and attention mechanism.

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Book SynopsisThis book provides solutions, best practices, tips, and workarounds to plan, design, customize, implement, and manage Microsoft Teams in any environment. This revised edition has been updated to reflect all the latest techniques and products, including migration from Skype for Business On-Prem to Microsoft Teams, along with Teams for Education, which includes a range of features and tools that enable teachers and students to collaborate, communicate, and learn in a virtual environment.The book begins with an overview of Microsoft Teams, including its architecture, teams/channels, audio/video meetings, and the phone system. The authors then take you deeper into deployment and management of teams, clients, guests and external access, and live events, followed by a walk-through of network assessment and bandwidth planning for Teams. Here, you will learn about deployment of quality of service and how to configure your phone systems using direct routing and calling plans. Moving forward, you will learn Microsoft Teams administration and policy management along with the migration process of Skype from Business On-Prem to Microsoft Teams. To wrap things up, the authors demonstrate some troubleshooting techniques for call quality issues in Teams, and walk you through various features of Teams for Education and how to utilize them. By the time you turn the last page of Understanding Microsoft Teams Administration, you'll be fully equipped to configure, customize, and control Teams with confidence. Don't just adapt to the future of collaboration—lead it. What You Will Learn Kickstart your journey: Get acquainted with the Teams architecture, from teams and channels to audio/video conferencing and beyond Master the mechanics: Dive deep into deployment, including crucial aspects like guest access, such as events, and network assessment Elevate call quality: Learn the nuts and bolts of Quality of Service (QoS) and phone systems, including direct routing and calling plans Admin like a pro: Gain insights into robust policy management, and understand how to navigate the Teams admin portal with finesse Get a grip on network assessment and bandwidth planning tailored specifically for Teams Unlock secrets of quality of service, direct routing, and customized calling plans Migration simplified: Seamlessly shift from Skype for Business On-Prem to Teams without missing a beat Edu-tech unveiled: Explore Teams for Education and how its myriad features can enrich virtual learning experiences for teachers and students alike What's new: A dedicated chapter exclusively covering Microsoft Teams for Education, focusing on empowering both educators and students Who This Book Is For Administrators and technical consultants focused on Microsoft Teams. This book serves as an invaluable resource for those looking to optimize team collaboration and communication within their organizations.Table of ContentsChapter 1: Microsoft Teams Overview.- Chapter 2: Managing and controlling Microsoft Teams.- Chapter 3: Organization Readiness for Microsoft Teams.- Chapter 4: Teams Audio Conferencing and Phone system management.- Chapter 5: Microsoft Teams Governance and lifecycle management.- Chapter 6: Migration from Skype for Business (Lync) on-prem and online to Microsoft Teams.- Chapter 7: Microsoft Teams troubleshooting approaches.- Chapter 8: Teams Reporting and Monitoring. – Chapter 9: Microsoft Teams for Education. - Chapter 10: Microsoft Teams Learning to the Next Level and Get Certified.

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Book SynopsisExamine the complexities of detecting ransomware and the potential rocky road to recover after it has infected a system environment. This book addresses the topic of Disaster and Ransomware Recovery in the VMware Cloud. You'll start by examining the challenge of implementing a robust disaster recovery solution, and how to address it through a Disaster Recovery-as-a-service (DRaaS) approach. The book then introduces the basics of the VMware Live Cyber Recovery solution and how it is fully integrated with VMware Cloud on AWS to offer an easy-to-use SaaS-based solution with a pay-as-you-go model for a faster recovery at a very low TCO. It also provides a technical deep dive into VMware Live Cyber Recovery architecture by detailing the features and capabilities of the solution including the concepts of Protected Sites, Protection Groups, Disaster Recovery Plans, and Failover testing. In subsequent chapters, you'll review in depth the Ransomware recovery case where you will learn more on the impact of Ransomware on IT organizations and how to address ransomware recovery. Finally, you'll take a deep dive into the technical architecture and features of the VMware Live Cyber Recovery Ransomware recovery capabilities, and how it can address ransomware threats with a very flexible, on-demand and easy-to-use SaaS delivery model with cloud economics. Mastering VMware Cloud Disaster Recovery and Ransomware Resilience provides you with the best practices on how to recover from ransomware. What You'll LearnReview the different concepts of VMware Live Cyber RecoveryUnderstand the complexity of ransomware attacks and how it can impact your business. Recover data after a ransomware attackImplement a ransomware recovery solution. Who This Book Is ForIT managers, IT architects, Cloud architects, network engineers, security officers, backup administrators, and infrastructure managers

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Book SynopsisVMware Workstation is a software solution that provides a type-2 hypervisor, or desktop hypervisor, that runs on x64 Windows and Linux-based operating systems. It enables users to create and run virtual machines, containers, and Kubernetes clusters simultaneously on their physical devices without having to reformat or dual-boot the underlying device. There are several use cases for VMware Workstation. For IT pros, it allows them to test applications andoperating system builds, as well as enable remote control of vSphere datacenter infrastructure. Developers can run multiple different operating systems or different versions of operating systems on a single device giving them the platform flexibility to test, develop, and troubleshoot applications cost-effectively. Finally, for the greater workforce, VMware Workstation can enable BYOD device initiatives allowing employees to run a full corporate environment on their device without deleting or reformatting it. Learning VMware Workstation Pro for Windows Part 2 provides the reader with a practical, step-by-step guide to creating and managing virtual machines using VMware Workstation, starting with an overview of hypervisors and desktop hypervisors. Next, it talks about each resource, such as CPU, memory, and networking, and how these are configured in a virtual environment. After that, it demonstrates the installation of VMware Workstation, configuration, and then building and managing different virtual machines running on different operating systems such as ChromeOS, and Linux, and building an ESXi lab environment. Towards the end, readers will learn how to use command line tools, such as the REST API, and vmrun, before going on to discuss upgrading and troubleshooting your VMware Workstation environment. By the end of this book, readers will have full knowledge of VMware Workstation Pro. This book is a continuation of Learning VMware Workstation Pro for Windows Part 1 where readers learn how to build and manage different virtual machines running on different operating systems and build an ESXi lab environment with VMware Workstation.You Will:Learn how to run containers on a VMware workstationUnderstand how to use the command line to configure and control Workstation Pro and virtual machinesPractice the use of REST API for Workstation ProThis book is for: Developers, IT professionals, VMware certified professionals both remote and Bring your device (BYOD).

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Book SynopsisIntroduction Chapter 1: The quest for effectiveness.- Chapter 2: Foundations: Making sense of change.- Chapter 3: Foundations: The art and science  of change.- Chapter 4: Foundations: The patterns of change.- Chapter 5: Foundations: The layers of change.- Chapter 6: Foundations: The cycles of change.-Chapter 7: Foundations: The practice of change.- Chapter 8: Step 1: Identify the enterprise.- Chapter 9: Step 2: Get ready for action.- Chapter 10: Step 3: Set out the stall.- Chapter 11: Step 4: Interact with the market.- Chapter 12: Step 5: Interact with the enterprise.- Chapter 13: Engaging others in the architecture.- Chapter 14: Wrapping up.- Appendix A: Glossary.- Appendix B: Sources and Resources.

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