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Cloud computing : a hands-on approach

]]> By Bahga, Arshdeep.
Kolkata University press 2014 .
454p. , Table of Content Part I Introduction and Concepts 1 Introduction to Cloud Computing 1.1 Introduction 1.1.1 Definition of Cloud Computing 1.2 Characteristics of Cloud Computing 1.3 Cloud Models 1.3.1 Service Models 1.3.2 Deployment Models 1.4 Cloud Services Examples 1.4.1 IaaS: Amazon EC2, Google Compute Engine, Azure VMs 1.4.2 PaaS: Google App Engine 1.4.3 SaaS: Salesforce 1.5 Cloud-based Services & Applications 1.5.1 Cloud Computing for Healthcare 1.5.2 Cloud Computing for Energy Systems 1.5.3 Cloud Computing for Transportation Systems 1.5.4 Cloud Computing for Manufacturing Industry 1.5.5 Cloud Computing for Government 1.5.6 Cloud Computing for Education 1.5.7 Cloud Computing for Mobile Communication 2 Cloud Concepts & Technologies 2.1 Virtualization 2.2 Load Balancing 2.3 Scalability & Elasticity 2.4 Deployment 2.5 Replication 2.6 Monitoring 2.7 Software Defined Networking 2.8 Network Function Virtualization 2.9 MapReduce 2.10 Identity and Access Management 2.11 Service Level Agreements 2.12 Billing 3 Cloud Services & Platforms 3.1 Compute Services 3.1.1 Amazon Elastic Compute Cloud 3.1.2 Google Compute Engine 3.1.3 Windows Azure Virtual Machines 3.2 Storage Services 3.2.1 Amazon Simple Storage Service 3.2.2 Google Cloud Storage 3.2.3 Windows Azure Storage 3.3 Database Services 3.3.1 Amazon Relational Data Store 3.3.2 Amazon DynamoDB 3.3.3 Google Cloud SQL 3.3.4 Google Cloud Datastore 3.3.5 Windows Azure SQL Database 3.3.6 Windows Azure Table Service 3.4 Application Services 3.4.1 Application Runtimes & Frameworks 3.4.2 Queuing Services 3.4.3 Email Services 3.4.4 Notification Services 3.4.5 Media Services 3.5 Content Delivery Services 3.5.1 Amazon CloudFront 3.5.2 Windows Azure Content Delivery Network 3.6 Analytics Services 3.6.1 Amazon Elastic MapReduce 3.6.2 Google MapReduce Service 3.6.3 Google BigQuery 3.6.4 Windows Azure HDInsight 3.7 Deployment & Management Services 3.7.1 Amazon Elastic Beanstalk 3.7.2 Amazon CloudFormation 3.8 Identity & Access Management Services 3.8.1 Amazon Identity & Access Management 3.8.2 Windows Azure Active Directory 3.9 Open Source Private Cloud Software 3.9.1 CloudStack 3.9.2 Eucalyptus 3.9.3 OpenStack 4 Hadoop & MapReduce 4.1 Apache Hadoop 4.2 Hadoop MapReduce Job Execution 4.2.1 NameNode 4.2.2 Secondary NameNode 4.2.3 JobTracker 4.2.4 TaskTracker 4.2.5 DataNode 4.2.6 MapReduce Job Execution Workflow 4.3 Hadoop Schedulers 4.3.1 FIFO 4.3.2 Fair Scheduler 4.3.3 Capacity Scheduler 4.4 Hadoop Cluster Setup 4.4.1 Install Java 4.4.2 Install Hadoop 4.4.3 Networking 4.4.4 Configure Hadoop 4.4.5 Starting and Stopping Hadoop Cluster Part II Developing for Cloud 5 Cloud Application Design 5.1 Introduction 5.2 Design Considerations for Cloud Applications 5.2.1 Scalability 5.2.2 Reliability & Availability 5.2.3 Security 5.2.4 Maintenance & Upgradation 5.2.5 Performance 5.3 Reference Architectures for Cloud Applications 5.4 Cloud Application Design Methodologies 5.4.1 Service Oriented Architecture 5.4.2 Cloud Component Model 5.4.3 IaaS, PaaS and SaaS Services for Cloud Applications 5.4.4 Model View Controller 5.4.5 RESTful Web Services 5.5 Data Storage Approaches 5.5.1 Relational (SQL) Approach 5.5.2 Non-Relational (No-SQL) Approach 6 Python Basics 6.1 Introduction 6.2 Installing Python 6.3 Python Data Types & Data Structures 6.3.1 Numbers 6.3.2 Strings 6.3.3 Lists 6.3.4 Tuples 6.3.5 Dictionaries 6.3.6 Type Conversions 6.4 Control Flow 6.4.1 if 6.4.2 for 6.4.3 while 6.4.4 range 6.4.5 break/continue 6.4.6 pass 6.5 Functions 6.6 Modules 6.7 Packages 6.8 File Handling 6.9 Date/Time Operations 6.10 Classes 7 Python for Cloud 7.1 Python for Amazon Web Services 7.1.1 Amazon EC2 7.1.2 Amazon AutoScaling 7.1.3 Amazon S3 7.1.4 Amazon RDS 7.1.5 Amazon DynamoDB 7.1.6 Amazon SQS 7.1.7 Amazon EMR 7.2 Python for Google Cloud Platform 7.2.1 Google Compute Engine 7.2.2 Google Cloud Storage 7.2.3 Google Cloud SQL 7.2.4 Google BigQuery 7.2.5 Google Cloud Datastore 7.2.6 Google App Engine 7.3 Python for Windows Azure 7.3.1 Azure Cloud Service 7.3.2 Azure Virtual Machines 7.3.3 Azure Storage 7.4 Python for MapReduce 7.5 Python Packages of Interest 7.5.1 JSON 7.5.2 XML 7.5.3 HTTPLib & URLLib 7.5.4 SMTPLib 7.5.5 NumPy 7.5.6 Scikit-learn 7.6 Python Web Application Framework - Django 7.6.1 Django Architecture 7.6.2 Starting Development with Django 7.6.3 Django Case Study - Blogging App 7.7 Designing a RESTful Web API 8 Cloud Application Development in Python 8.1 Design Approaches 8.1.1 Design Methodology for IaaS Service Model 8.1.2 Design Methodology for PaaS Service Model 8.2 Image Processing App 8.3 Document Storage App 8.4 MapReduce App 8.5 Social Media Analytics App Part III Advanced Topics 9 Big Data Analytics 9.1 Introduction 9.2 Clustering Big Data 9.2.1 k-Means Clustering 9.2.2 DBSCAN Clustering 9.2.3 Parallelizing Clustering Algorithms Using MapReduce 9.3 Classification of Big Data 9.3.1 Naive Bayes 9.3.2 Decision Trees 9.3.3 Random Forest 9.3.4 Support Vector Machine 9.4 Recommendation Systems 10 Multimedia Cloud 10.1 Introduction 10.2 Case Study: Live Video Streaming App 10.3 Streaming Protocols 10.3.1 RTMP Streaming 10.3.2 HTTP Live Streaming 10.3.3 HTTP Dynamic Streaming 10.4 Case Study: Video Transcoding App 11 Cloud Application Benchmarking & Tuning 11.1 Introduction 11.1.1 Trace Collection/Generation 11.1.2 Workload Modeling 11.1.3 Workload Specification 11.1.4 Synthetic Workload Generation 11.1.5 User Emulation vs. Aggregate Workloads 11.2 Workload Characteristics 11.3 Application Performance Metrics 11.4 Design Considerations for a Benchmarking Methodology 11.5 Benchmarking Tools 11.5.1 Types of Tests 11.6 Deployment Prototyping 11.7 Load Testing & Bottleneck Detection Case Study 11.8 Hadoop Benchmarking Case Study 12 Cloud Security 12.1 Introduction 12.2 CSA Cloud Security Architecture 12.3 Authentication 12.3.1 Single Sign-on (SSO) 12.4 Authorization 12.5 Identity & Access Management 12.6 Data Security 12.6.1 Securing Data at Rest 12.6.2 Securing Data in Motion 12.7 Key Management 12.8 Auditing 13 Cloud for Industry, Healthcare & Education 13.1 Cloud Computing for Healthcare 13.2 Cloud Computing for Energy Systems 13.3 Cloud Computing for Transportation Systems 13.4 Cloud Computing for Manufacturing Industry 13.5 Cloud Computing for Education Appendix-A: Setting up Ubuntu VM Appendix-B: Setting up Django Bibliography Index 9788173719233

]]> Place hold on Cloud computing

Internet of things a hands-on approach

]]> By Bahga, Arshdeep.
Kolkata University press 2025 .
520p. , I INTRODUCTION & CONCEPTS 1 Introduction to Internet of Things 1.1 Introduction 1.1.1 Definition & Characteristics of IoT 1.2 Physical Design of IoT 1.2.1 Things in IoT 1.2.2 IoT Protocols 1.3 Logical Design of IoT 1.3.1 IoT Functional Blocks 1.3.2 IoT Communication Models 1.3.3 IoT Communication APIs 1.4 IoT Enabling Technologies 1.4.1 Wireless Sensor Networks 1.4.2 Cloud Computing 1.4.3 Big Data Analytics 1.4.4 Communication Protocols 1.4.5 Embedded Systems 1.5 IoT Levels & Deployment Templates 1.5.1 IoT Level-1 1.5.2 IoT Level-2 1.5.3 IoT Level-3 1.5.4 IoT Level-4 1.5.5 IoT Level-5 1.5.6 IoT Level-6 2 Domain Specific IoTs 2.1 Introduction 2.2 Home Automation 2.2.1 Smart Lighting 2.2.2 Smart Appliances 2.2.3 Intrusion Detection 2.2.4 Smoke/Gas Detectors 2.3 Cities 2.3.1 Smart Parking 2.3.2 Smart Lighting 2.3.3 Smart Roads 2.3.4 Structural Health Monitoring 2.3.5 Surveillance 2.3.6 Emergency Response 2.4 Environment 2.4.1 Weather Monitoring 2.4.2 Air Pollution Monitoring 2.4.3 Noise Pollution Monitoring 2.4.4 Forest Fire Detection 2.4.5 River Floods Detection 2.5 Energy 2.5.1 Smart Grids 2.5.2 Renewable Energy Systems 2.5.3 Prognostics 2.6 Retail 2.6.1 Inventory Management 2.6.2 Smart Payments 2.6.3 Smart Vending Machines 2.7 Logistics 2.7.1 Route Generation & Scheduling 2.7.2 Fleet Tracking 2.7.3 Shipment Monitoring 2.7.4 Remote Vehicle Diagnostics 2.8 Agriculture 2.8.1 Smart Irrigation 2.8.2 Green House Control 2.9 Industry 2.9.1 Machine Diagnosis & Prognosis 2.9.2 Indoor Air Quality Monitoring 2.10 Health & Lifestyle 2.10.1 Health & Fitness Monitoring 2.10.2 Wearable Electronics 3 IoT and M2M 3.1 Introduction 3.2 M2M 3.3 Difference between IoT and M2M 3.4 SDN and NFV for IoT 3.4.1 Software Defined Networking 3.4.2 Network Function Virtualization 4 IoT System Management with NETCONF-YANG 4.1 Need for IoT Systems Management 4.2 Simple Network Management Protocol (SNMP) 4.2.1 Limitations of SNMP 4.3 Network Operator Requirements 4.4 NETCONF 4.5 YANG 4.6 IoT Systems Management with NETCONF-YANG 4.6.1 NETOPEER II DEVELOPING INTERNET OF THINGS 5 IoT Platforms Design Methodology 5.1 Introduction 5.2 IoT Design Methodology 5.2.1 Step 1: Purpose & Requirements Specification 5.2.2 Step 2: Process Specification 5.2.3 Step 3: Domain Model Specification 5.2.4 Step 4: Information Model Specification 5.2.5 Step 5: Service Specifications 5.2.6 Step 6: IoT Level Specification 5.2.7 Step 7: Functional View Specification 5.2.8 Step 8: Operational View Specification 5.2.9 Step 9: Device & Component Integration 5.2.10 Step 10: Application Development 5.3 Case Study on IoT System for Weather Monitoring 5.4 Motivation for Using Python 6 IoT Systems - Logical Design using Python 6.1 Introduction 6.2 Installing Python 6.3 Python Data Types & Data Structures 6.3.1 Numbers 6.3.2 Strings 6.3.3 Lists 6.3.4 Tuples 6.3.5 Dictionaries 6.3.6 Type Conversions 6.4 Control Flow 6.4.1 if 6.4.2 for 6.4.3 while 6.4.4 range 6.4.5 break/continue 6.4.6 pass 6.5 Functions 6.6 Modules 6.7 Packages 6.8 File Handling 6.9 Date/Time Operations 6.10 Classes 6.11 Python Packages of Interest for IoT 6.11.1 JSON 6.11.2 XML 6.11.3 HTTPLib & URLLib 6.11.4 SMTPLib 7 IoT Physical Devices & Endpoints 7.1 What is an IoT Device 7.1.1 Basic building blocks of an IoT Device 7.2 Exemplary Device: Raspberry Pi 7.3 About the Board 7.4 Linux on Raspberry Pi 7.5 Raspberry Pi Interfaces 7.5.1 Serial 7.5.2 SPI 7.5.3 I2C 7.6 Programming Raspberry Pi with Python 7.6.1 Controlling LED with Raspberry Pi 7.6.2 Interfacing an LED and Switch with Raspberry Pi 7.6.3 Interfacing a Light Sensor (LDR) with Raspberry Pi 7.7 Other IoT Devices 7.7.1 pcDuino 7.7.2 BeagleBone Black 7.7.3 Cubieboard 8 IoT Physical Servers & Cloud Offerings 8.1 Introduction to Cloud Storage Models & Communication APIs 8.2 WAMP - AutoBahn for IoT 8.3 Xively Cloud for IoT 8.4 Python Web Application Framework - Django 8.4.1 Django Architecture 8.4.2 Starting Development with Django . 8.5 Designing a RESTful Web API 8.6 Amazon Web Services for IoT 8.6.1 Amazon EC2 8.6.2 Amazon AutoScaling 8.6.3 Amazon S3 8.6.4 Amazon RDS 8.6.5 Amazon DynamoDB . 8.6.6 Amazon Kinesis 8.6.7 Amazon SQS 8.6.8 Amazon EMR 8.7 SkyNet IoT Messaging Platform 9 Case Studies Illustrating IoT Design 9.1 Introduction 9.2 Home Automation 9.2.1 Smart Lighting 9.2.2 Home Intrusion Detection 9.3 Cities 9.3.1 Smart Parking 9.4 Environment 9.4.1 Weather Monitoring System 9.4.2 Weather Reporting Bot 9.4.3 Air Pollution Monitoring 9.4.4 Forest Fire Detection 9.5 Agriculture 9.5.1 Smart Irrigation 9.6 Productivity Applications 9.6.1 IoT Printer III ADVANCED TOPICS 10 Data Analytics for IoT 10.1 Introduction 10.2 Apache Hadoop 10.2.1 MapReduce Programming Model 10.2.2 Hadoop MapReduce Job Execution 10.2.3 MapReduce Job Execution Workflow 10.2.4 Hadoop Cluster Setup 10.3 Using Hadoop MapReduce for Batch Data Analysis 10.3.1 Hadoop YARN 10.4 Apache Oozie 10.4.1 Setting up Oozie 10.4.2 Oozie Workflows for IoT Data Analysis 10.5 Apache Spark 10.6 Apache Storm 10.6.1 Setting up a Storm Cluster 10.7 Using Apache Storm for Real-time Data Analysis 10.7.1 REST-based approach 10.7.2 WebSocket-based approach 10.8 Structural Health Monitoring Case Study 11 Tools for IoT 11.1 Introduction 11.2 Chef 11.2.1 Setting up Chef 11.3 Chef Case Studies 11.3.1 Multi-tier Application Deployment 11.3.2 Hadoop Cluster 11.3.3 Storm Cluster 11.4 Puppet 11.5 Puppet Case Study - Multi-tier Deployment 11.6 NETCONF-YANG Case Studies 11.6.1 Steps for IoT device Management with NETCONF-YANG 11.6.2 Managing Smart Irrigation IoT System with NETCONF-YANG 11.6.3 Managing Home Intrusion Detection IoT System with NETCONF-YANG 11.7 IoT Code Generator Appendix-A - Setting up Raspberry Pi Appendix-B - Setting up Ubuntu VM Appendix-C - Setting up Django Bibliography Index 9788173719547

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