Applying Eco-Threading Framework to Memory-Intensive Hadoop Applications
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Year
: 2014DOI: 10.1109/TENCON.2014.7022323
Keyword(s): Capacity planning,Clustering algorithms,Data mining,Equations,Resource management,Vectors,Virtual machining
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Applying Eco-Threading Framework to Memory-Intensive Hadoop Applications
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| contributor author | Takasaki, H. , Mostafa, S.M. , Kusakabe, S. | |
| date accessioned | 2020-03-12T20:02:00Z | |
| date available | 2020-03-12T20:02:00Z | |
| date issued | 2014 | |
| identifier other | 6847366.pdf | |
| identifier uri | http://libsearch.um.ac.ir:80/fum/handle/fum/999280?locale-attribute=en | |
| format | general | |
| language | English | |
| publisher | IEEE | |
| title | Applying Eco-Threading Framework to Memory-Intensive Hadoop Applications | |
| type | Conference Paper | |
| contenttype | Metadata Only | |
| identifier padid | 8119601 | |
| subject keywords | Capacity planning | |
| subject keywords | Clustering algorithms | |
| subject keywords | Data mining | |
| subject keywords | Equations | |
| subject keywords | Resource management | |
| subject keywords | Vectors | |
| subject keywords | Virtual machining | |
| identifier doi | 10.1109/TENCON.2014.7022323 | |
| journal title | nformation Science and Applications (ICISA), 2014 International Conference on | |
| filesize | 637225 | |
| citations | 0 |