Cloud computing : application on data farming

• Main Author: Yong, Yong Cheng.
• Other Authors: Low Yoke Hean, Malcolm
• Format: Final Year Project
• Language: English
• Published: 2010
• Subjects: DRNTU::Engineering::Computer science and engineering::Data; DRNTU::Engineering::Computer science and engineering::Computer systems organization::Computer-communication networks
• Online Access: http://hdl.handle.net/10356/42453
• Institution: Nanyang Technological University

Objective-Based Data Farming requires massive amount of computing power to run thousands/millions of simulations. To acquire this massive amount of computing power, one has to own the infrastructure: a cluster/grid of many cheap computers or an expensive supercomputer. Both actions amount to an exorbitant sum of money over time to satisfy this increasing need. With the introduction of Amazon Elastic Compute Cloud (Amazon EC2) and MapReduce programming model, the story of one having to own the infrastructure to gain access to this massive amount of computing power is in the past. The term “Cloud Computing” has been introduced and is more popular with each passing day. Cloud Computing allows massive amount of computing power to be available as a utility and at a cheap cost. It also offers other benefits such as scalability in real-time and with great ease, high availability and fault tolerant. This project implements a robust private Cloud to address the security concerns when using military applications. It also implements a public Cloud to exhibit the feasibility of using a public infrastructure. In this project, a Web Service and 6 MapReduce applications, which are used in distributing workloads within a Cloud, are designed and implemented. They allow conventional Objective-Based Data Farming frameworks to take full advantage of Cloud Computing.