S. Thamarai Selvi

Cloud Computing Architecture

The term cloud computing is a wide umbrella encompassing many different things. Lately it has become a buzzword that is easily misused to revamp existing technologies and ideas for the public. What makes cloud computing so interesting to IT stakeholders and research practitioners? How does it introduce innovation into the field of distributed computing? This chapter addresses all these questions and characterizes the phenomenon. It provides a reference model that serves as a basis for discussion of cloud computing technologies.

Principles of Parallel and Distributed Computing

This chapter presents the fundamental principles of parallel and distributed computing and discusses models and conceptual frameworks that serve as foundations for building cloud computing systems and applications.

Data-Intensive Computing: MapReduce Programming

This chapter characterizes the nature of data-intensive computing and presents an overview of the challenges introduced by production of large volumes of data and how they are handled by storage systems and computing models. It describes MapReduce, which is a popular programming model for creating data-intensive applications and their deployment on clouds. Practical examples of MapReduce applications for data-intensive computing are demonstrated using the Aneka MapReduce Programming Model.This chapter characterizes the nature of data-intensive computing and presents an overview of the challenges introduced by production of large volumes of data and how they are handled by storage systems and computing models. It describes MapReduce, which is a popular programming model for creating data-intensive applications and their deployment on clouds. Practical examples of MapReduce applications for data-intensive computing are demonstrated using the Aneka MapReduce Programming Model.

Aneka: Cloud Application Platform

This chapter provides a complete overview of the cloud application framework by first describing the architecture of the system. It introduces Aneka’s components and the fundamental services that make up the Aneka Cloud and discusses some common deployment scenarios.

Cloud Platforms in Industry

This chapter presents some of the representative cloud computing solutions offered as Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) services in the market. It provides some insights into and practical issues surrounding the architecture of the major cloud computing technologies and their service offerings.

Concurrent Computing: Thread Programming

This chapter presents multithreading and describes how it supports the development of high-throughput computing applications. It discusses how multithreaded programming, originally conceived to be contained within the boundaries of a single machine, can be extended to a distributed context and which limitations apply. The Aneka Thread Programming Model is taken as a reference model to review a practical implementation of a multithreaded model for computing clouds.

Advanced Topics in Cloud Computing

This chapter presents an overview of various open issues in cloud computing that need long-term investigation. It discusses issues involved in energy-efficient cloud computing and presents a “green” cloud computing architecture. It discusses market models needed for realizing an open market for cloud computing systems from the perspective of federations of clouds and agreements between clouds. A general overview of some of the existing standards that enable interoperation between clouds and a brief look at third-party cloud services are presented.

High-Throughput Computing: Task Programming

This chapter characterizes the abstraction of a task and provides a brief overview of the distributed application models that are based on the task abstraction. The Aneka Task Programming Model is taken as a reference implementation to illustrate the execution of bag-of-tasks (BoT) applications on a distributed infrastructure.