Report on industrial attachment with DSO National Laboratories

Abstract

Cloud Computing is rapidly gaining widespread acceptance and has delivered its promised benefits, such as reduced cost, mobility, scalability and agility. Data Farming is an iterative process, which is both computation-intensive and dataintensive. With the incorporation of Cloud Computing, Data Farming can be performed with a lower cost, in a larger scale and a faster time. MapReduce programming model was introduced by Google in 2004 to support distributed computing on large data-sets on clusters of computers. Since then, MapReduce has been popular and is implemented as a software framework in almost all Cloud Computing platforms. In the project, I have implemented a web service and supplemented three Data Farming tools with the ability to use the web service. These tools are able to execute their simulation runs on NTU Hadoop Cluster through their respective user interfaces and were recently being used in International Data Farming Workshop (IDFW) 19.