SELF-LEARNING OF PARAMETER WEIGHTS FOR TASK SCHEDULING IN GRID COMPUTING ENVIRONMENT
The Grid computing environment is very important for solving scientific problems. To get the best performance from Grid, it is important to know where to send tasks. This paper is about one of the suggested methods for a Grid resource broker to find the best resources for the task. This method requi...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | Lithuanian |
| Published: |
Kauno Kolegija (Kaunas University of Applied Sciences)
2021-12-01
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| Series: | Mokslo Taikomieji Tyrimai Lietuvos Kolegijose |
| Subjects: | |
| Online Access: | http://ojs.kaunokolegija.lt/index.php/mttlk/article/view/503 |
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| Summary: | The Grid computing environment is very important for solving scientific problems. To get the best performance from Grid, it is important to know where to send tasks. This paper is about one of the suggested methods for a Grid resource broker to find the best resources for the task. This method requires defining the parameters of the resources and knowing the importance of the weights of parameters. This paper also presents the self-learning method of parameter weights. |
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| ISSN: | 1822-1068 2335-8904 |