Taiwan is surrounded by ocean, thus the ocean transportation has become the necessary support of Taiwan's economy. Due to this fact, this research provides a system based on cloud computing and distributed storage which is applied to compute large amount of data provided by many sensors on the sea in order to diagnose the existence of possible magnetized invaders.
We use Hadoop platform from Apache Foundation to proceed distributable K-means clustering computation to process the data collected f
rom many sensor nodes containing DGPS and magnetic sensors. With these data, it is possible to diagnose the existence and the moving direction of the possible invader. And the result can be return to remote monitoring terminal. Not only K-means can detect the irregularity of any axis of the magnetic field well, but also this system obtain good reliability and performance by Hadoop platform.
The goal system can detect the irregularity of any axis of the magnetic field well enough by deploying K-Means clustering and obtain good reliability and performance by Hadoop platform.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-1121112-102954 |
| Date | 21 November 2012 |
| Creators | Sun, Rui-Ting |
| Contributors | Tsung-Chuan Huang, Shie-Jue Lee, Chun-Liang Hou, Chen-Sen Ouyang |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1121112-102954 |
| Rights | user_define, Copyright information available at source archive |
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