Report on industrial attachment with DSO National Laboratories
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 F...
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sg-ntu-dr.10356-465232023-03-03T21:03:24Z Report on industrial attachment with DSO National Laboratories Yong, Yong Cheng. Low Yoke Hean, Malcolm School of Computer Engineering DSO National Laboratories DRNTU::Engineering::Computer science and engineering 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. 2011-12-13T06:43:54Z 2011-12-13T06:43:54Z 2011 2011 Industrial Attachment (IA) http://hdl.handle.net/10356/46523 en Nanyang Technological University 63 p. application/pdf |
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DRNTU::Engineering::Computer science and engineering Yong, Yong Cheng. Report on industrial attachment with DSO National Laboratories |
description |
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. |
author2 |
Low Yoke Hean, Malcolm |
author_facet |
Low Yoke Hean, Malcolm Yong, Yong Cheng. |
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Industrial Attachment (IA) |
author |
Yong, Yong Cheng. |
author_sort |
Yong, Yong Cheng. |
title |
Report on industrial attachment with DSO National Laboratories |
title_short |
Report on industrial attachment with DSO National Laboratories |
title_full |
Report on industrial attachment with DSO National Laboratories |
title_fullStr |
Report on industrial attachment with DSO National Laboratories |
title_full_unstemmed |
Report on industrial attachment with DSO National Laboratories |
title_sort |
report on industrial attachment with dso national laboratories |
publishDate |
2011 |
url |
http://hdl.handle.net/10356/46523 |
_version_ |
1759854817633632256 |