A big data placement method using NSGA-III in meteorological cloud platform
| Autor: | Shengjun Xue, Feng Ruan, Renhao Gu, Tao Huang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Computer Networks and Communications
Computer science Real-time computing Big data Weather forecasting NSGA-III lcsh:TK7800-8360 Cloud computing 02 engineering and technology Data placement computer.software_genre 01 natural sciences lcsh:Telecommunication Resource (project management) lcsh:TK5101-6720 0202 electrical engineering electronic engineering information engineering Information system business.industry 010401 analytical chemistry lcsh:Electronics 020206 networking & telecommunications Energy consumption 0104 chemical sciences Computer Science Applications Data access Signal Processing business computer Meteorological cloud platform |
| Zdroj: | EURASIP Journal on Wireless Communications and Networking, Vol 2019, Iss 1, Pp 1-13 (2019) |
| ISSN: | 1687-1499 |
| DOI: | 10.1186/s13638-019-1456-7 |
| Popis: | Meteorological cloud platforms (MCP) are gradually replacing the traditional meteorological information systems to provide information analysis services such as weather forecasting, disaster warning, and scientific research. However, the explosive growth of meteorological data resources has brought new challenges to the placement and management of big data in MCP. On the one hand, managers of MCP need to save energy to achieve cost savings. On the other hand, users need shorter data access time to improve user’s experience. Hence, a big data placement method in MCP is proposed in this paper to deal with challenges above. First, the resource utilization, the data access time, and the energy consumption in MCP with the fat-tree topology are analyzed. Then, a corresponding data placement method, using the improved non-dominated sorting genetic algorithm III (NSGA-III), is designed to optimize the resource usage, energy saving, and efficient data access. Finally, extensive experimental evaluations validate the efficiency and effectiveness of our proposed method. |
| Databáze: | OpenAIRE |
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