Mastering Cloud Computing

Name: Mastering Cloud Computing
Price: 99.95 USD
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ISBN: 9780443404351

Foundations and Applications Programming

by Rajkumar Buyya, Christian Vecchiola, S. Thamarai Selvi, Shivananda Poojara, Satish Narayana Srirama

2nd Edition

Publisher: Morgan Kaufmann

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Book Details

Print ISBN	9780443404351
eText ISBN	9780443404368
Publisher	Morgan Kaufmann
Publishing Year	2026
Edition	2nd Edition
Language	English
Pages	490

Mastering Cloud Computing, 2nd Edition, is a textbook designed for students and aspiring cloud application developers. The text examines fundamental distributed architectures, detailing core theoretical concepts alongside operational execution models. Primary areas of emphasis include foundational principles governing parallel systems, distributed computing, virtualization methods, thread programming, task programming, and MapReduce techniques.

To illustrate operational development models, the textbook presents an in-depth examination of the Aneka platform. The text positions Aneka as a dedicated cloud application platform, detailing how software engineers construct applications using its supported programming paradigms. Specifically, the material addresses how Aneka integrates thread, task, and MapReduce programming models to structure execution across distributed hardware.

The book reinforces theoretical concepts by analyzing real-world case studies across multiple operational contexts. These practical studies incorporate scientific research requirements, enterprise business demands, and energy-efficiency considerations. This structure helps students evaluate system behavior under varied resource constraints and computational goals.

Chapter 1: Introduction
- • 1.1 Cloud computing at a glance
- • 1.1.1 The vision of cloud computing
- • 1.1.2 Defining a cloud
- • 1.1.3 A closer look
- • 1.1.4 Cloud computing reference model
- • 1.1.5 Characteristics and benefits
- • 1.1.6 Challenges ahead
- • 1.2 Historical developments
- • 1.2.1 Distributed systems
- • 1.2.2 Virtualization
- • 1.2.3 Web 2.0
- • 1.2.4 Service-oriented computing
- • 1.2.5 Utility-oriented computing
- • 1.2.6 Post 2010 advances in cloud computing context
- • 1.3 Building cloud computing environments
- • 1.3.1 Application development
- • 1.3.2 Infrastructure and system development
- • 1.4 Computing platforms and technologies
- • 1.4.1 Amazon web services (AWS)
- • 1.4.2 Google AppEngine
- • 1.4.3 Microsoft azure
- • 1.4.4 Hadoop
- • 1.4.5 Force.com and Salesforce.com
- • 1.4.6 Manjrasoft aneka
- • Summary
- • Review questions
Chapter 2: Principles of Parallel and Distributed Computing
- • 2.1 Eras of computing
- • 2.2 Parallel versus distributed computing
- • 2.3 Elements of parallel computing
- • 2.3.1 What is parallel processing?
- • 2.3.2 Hardware architectures for parallel processing
- • 2.3.3 Approaches to parallel programming
- • 2.3.4 Levels of parallelism
- • 2.3.5 Laws of caution
- • 2.4 Elements of distributed computing
- • 2.4.1 General concepts and definitions
- • 2.4.2 Components of a distributed system
- • 2.4.3 Architectural styles for distributed computing
- • 2.4.4 Models for interprocess communication
- • 2.5 Technologies for distributed computing
- • 2.5.1 Remote procedure call
- • 2.5.2 Distributed object frameworks
- • 2.5.3 Service-oriented computing
- • Summary
- • Review questions
Chapter 3: Virtualization
- • 3.1 Introduction
- • 3.2 Characteristics of virtualized environments
- • 3.2.1 Increased security
- • 3.2.2 Managed execution
- • 3.2.3 Portability
- • 3.3 Taxonomy of virtualization techniques
- • 3.3.1 Execution virtualization
- • 3.3.2 Other types of virtualization
- • 3.4 Virtualization and cloud computing
- • 3.5 Pros and cons of virtualization
- • 3.5.1 Advantages of virtualization
- • 3.5.2 The other side of the coin: disadvantages
- • 3.6 Technology examples
- • 3.6.1 Xen: paravirtualization
- • 3.6.2 VMware: full virtualization
- • 3.6.3 Microsoft Hyper-V
- • Summary
- • Review questions
Chapter 4: Cloud Computing Architecture
- • 4.1 Introduction
- • 4.2 The cloud reference model
- • 4.2.1 Architecture
- • 4.2.2 Infrastructure- and Hardware-as-a-Service
- • 4.2.3 Platform-as-a-Service
- • 4.2.4 Software-as-a-Service
- • 4.3 Types of clouds
- • 4.3.1 Public clouds
- • 4.3.2 Private clouds
- • 4.3.3 Hybrid clouds
- • 4.3.4 Community clouds
- • 4.4 Economics of the cloud
- • 4.5 Open challenges
- • 4.5.1 Cloud definition
- • 4.5.2 Cloud interoperability and standards
- • 4.5.3 Scalability and fault tolerance
- • 4.5.4 Security, trust, and privacy
- • 4.5.5 Organizational aspects
- • Summary
- • Review questions
Chapter 5: Aneka: Cloud application platform
- • 5.1 Framework overview
- • 5.2 Anatomy of the Aneka container
- • 5.2.1 From the ground up: the platform abstraction layer
- • 5.2.2 Fabric services
- • 5.2.3 Foundation services
- • 5.2.4 Application services
- • 5.3 Building Aneka clouds
- • 5.3.1 Infrastructure organization
- • 5.3.2 Logical organization
- • 5.3.3 Private cloud deployment mode
- • 5.3.4 Public cloud deployment mode
- • 5.3.5 Hybrid cloud deployment mode
- • 5.4 Cloud programming and management
- • 5.4.1 Aneka SDK
- • 5.4.2 Management tools
- • Summary
- • Review questions
Chapter 6: Concurrent Computing
- • 6.1 Introducing parallelism for single-machine computation
- • 6.2 Programming applications with threads
- • 6.2.1 What is a thread?
- • 6.2.2 Thread APIs
- • 6.2.3 Techniques for parallel computation with threads
- • 6.3 Multithreading with Aneka
- • 6.3.1 Introducing the thread programming model
- • 6.3.2 Aneka thread versus common threads
- • 6.4 Programming applications with Aneka threads
- • 6.4.1 Aneka threads application model
- • 6.4.2 Domain decomposition: matrix multiplication
- • 6.4.3 Functional decomposition: Sine, Cosine, and Tangent
- • Summary
- • Review questions
Chapter 7: High-Throughput Computing
- • 7.1 Task computing
- • 7.1.1 Characterizing a task
- • 7.1.2 Computing categories
- • 7.1.3 Frameworks for task computing
- • 7.2 Task-based application models
- • 7.2.1 Embarrassingly parallel applications
- • 7.2.2 Parameter sweep applications
- • 7.2.3 MPI applications
- • 7.2.4 Workflow applications with task dependencies
- • 7.3 Aneka task-based programming
- • 7.3.1 Task programming model
- • 7.3.2 Developing applications with the task model
- • 7.3.3 Developing a parameter sweep application
- • 7.3.4 Managing workflows
- • Summary
- • Review questions
Chapter 8: Data-Intensive Computing
- • 8.1 What is data-intensive computing?
- • 8.1.1 Characterizing data-intensive computations
- • 8.1.2 Challenges ahead
- • 8.1.3 Historical perspective
- • 8.2 Technologies for data-intensive computing
- • 8.2.1 Storage systems
- • 8.2.2 Programming platforms
- • 8.3 Aneka MapReduce programming
- • 8.3.1 Introducing the MapReduce programming model
- • 8.3.2 Example application
- • Summary
- • Review questions
Chapter 9: Cloud Platforms in Industry
- • 9.1 Amazon web services
- • 9.1.1 Compute services
- • 9.1.2 Storage services
- • 9.1.3 Communication services
- • 9.1.4 Additional services
- • 9.1.5 Summary
- • 9.2 Google AppEngine
- • 9.2.1 Architecture and core concepts
- • 9.2.2 Application life cycle
- • 9.2.3 Cost model
- • 9.2.4 Observations
- • 9.2.5 Other services in the Google cloud platform
- • 9.3 Microsoft Azure
- • 9.3.1 Azure core concepts
- • 9.3.2 SQL Azure
- • 9.3.3 Windows Azure platform appliance
- • 9.3.4 Observations
- • Summary
- • Review questions
Chapter 10: Cloud applications
- • 10.1 Scientific applications
- • 10.1.1 Healthcare: ECG analysis in the cloud
- • 10.1.2 Biology: protein structure prediction
- • 10.1.3 Biology: gene expression data analysis for cancer diagnosis
- • 10.1.4 Geoscience: satellite image processing
- • 10.2 Business and consumer applications
- • 10.2.1 CRM and ERP
- • 10.2.2 Productivity
- • 10.2.3 Social networking
- • 10.2.4 Media applications
- • 10.2.5 Multiplayer online gaming
- • Summary
- • Review questions
Chapter 11: Internet of Things, edge, and fog Computing
- • 11.1 Introduction
- • 11.1.1 What is a thing?
- • 11.1.2 Why is Internet of Things (IoT) so important?
- • 11.2 Internet of Things applications
- • 11.2.1 Smart home
- • 11.2.2 Smart city
- • 11.2.3 Smart healthcare
- • 11.2.4 Smart factory and Industrial Internet of Things
- • 11.2.5 Smart agriculture
- • 11.2.6 Environmental protection
- • 11.2.7 Smartphone-based applications
- • 11.3 Cloud-centric Internet of Things
- • 11.3.1 Layers of cloud-centric Internet of Things
- • 11.3.2 Sensing and smart devices layer
- • 11.3.3 Gateway/connectivity layer
- • 11.3.4 Cloud layer
- • 11.4 Internet of Things platforms
- • 11.4.1 Features of Internet of Things platforms
- • 11.4.2 Example Internet of Things platforms
- • 11.4.3 IoT data processing using Aneka: deep learning–based object detection
- • 11.5 Edge and fog computing
- • 11.5.1 Hierarchical fog computing architecture
- • 11.5.2 Aneka-based edge and fog computing
- • Summary
- • Review questions
Chapter 12: Cloud computing security
- • 12.1 Introduction
- • 12.2 Fundamentals of computer security
- • 12.2.1 Categories of computer security
- • 12.2.2 Vulnerabilities, threats, and risks
- • 12.2.3 Computer security risk plan and mitigations
- • 12.2.4 Concepts of computer security
- • 12.3 Cloud security
- • 12.3.1 Importance of cloud security
- • 12.3.2 Cloud security risks, threats, and challenges
- • 12.3.3 Benefits of secured cloud systems
- • 12.3.4 Cloud security architecture
- • 12.4 Cloud shared responsibility model
- • 12.4.1 Shared responsibility across cloud service models
- • 12.4.2 Microsoft Azure Shared Responsibility Model
- • 12.4.3 AWS Shared Responsibility Model
- • 12.4.4 Google Cloud shared responsibility model
- • 12.5 Cloud security frameworks
- • 12.5.1 Industry standard cloud security frameworks
- • 12.5.2 Overview of NIST Cybersecurity Framework
- • 12.5.3 Case study on AWS Cloud services
- • 12.5.4 Six steps towards more secure cloud computing
- • 12.6 Security in cloud deployment models
- • 12.6.1 Private clouds
- • 12.6.2 Public clouds
- • 12.6.3 Hybrid cloud
- • 12.7 Practical examples of cloud security
- • 12.7.1 Security aspects in Amazon Elastic Compute Cloud
- • 12.7.2 Securing the Platform as a Service: Aneka clouds
- • 12.8 Advanced topics in cloud security
- • 12.8.1 Zero trust security
- • 12.8.2 Blockchain based cloud security
- • 12.8.3 Artificial intelligence in cloud security
- • Summary
- • Review questions
Chapter 13: Containers and serverless computing
- • 13.1 Introduction
- • 13.2 Containers
- • 13.2.1 Differences between virtual machines and containers
- • 13.2.2 Fundamental building blocks of containers
- • 13.2.3 Open source container platforms
- • 13.2.4 Key benefits of containers
- • 13.3 Container orchestration
- • 13.3.1 Docker Swarm
- • 13.3.2 Kubernetes
- • 13.3.3 Service mesh
- • 13.3.4 Public cloud container platforms
- • 13.4 Serverless computing/ Function as a Service
- • 13.4.1 Serverless computing architecture
- • 13.4.2 Public cloud serverless platforms
- • 13.4.3 Open source serverless platforms
- • Summary
- • Review questions
Chapter 14: Distributed machine learning
- • 14.1 Introduction
- • 14.2 Introduction to artificial intelligence / machine learning
- • 14.3 Programming languages
- • 14.3.1 Python
- • 14.3.2 C++
- • 14.3.3 Julia
- • 14.3.4 C#.NET
- • 14.3.5 R
- • 14.3.6 Java