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http://dx.doi.org/10.5532/KJAFM.2019.21.4.347

Comparative Analysis on Cloud and On-Premises Environments for High-Resolution Agricultural Climate Data Processing  

Park, Joo Hyeon (R&D Center, EPINET Co., Ltd.)
Ahn, Mun Il (R&D Center, EPINET Co., Ltd.)
Kang, Wee Soo (National Institute of Agricultural Sciences, Rural Development Administration)
Shim, Kyo-Moon (National Institute of Agricultural Sciences, Rural Development Administration)
Park, Eun Woo (Department of Agricultural Biotechnology, Seoul National University)
Publication Information
Korean Journal of Agricultural and Forest Meteorology / v.21, no.4, 2019 , pp. 347-357 More about this Journal
Abstract
The usefulness of processing and analysis systems of GIS-based agricultural climate data is affected by the reliability and availability of computing infrastructures such as cloud, on-premises, and hybrid. Cloud technology has grown in popularity. However, various reference cases accumulated over the years of operational experiences point out important features that make on-premises technology compatible with cloud technology. Both cloud and on-premises technologies have their advantages and disadvantages in terms of operational time and cost, reliability, and security depending on cases of applications. In this study, we have described characteristics of four general computing platforms including cloud, on-premises with hardware-level virtualization, on-premises with operating system-level virtualization and hybrid environments, and compared them in terms of advantages and disadvantages when a huge amount of GIS-based agricultural climate data were stored and processed to provide public services of agro-meteorological and climate information at high spatial and temporal resolutions. It was found that migrating high-resolution agricultural climate data to public cloud would not be reasonable due to high cost for storing a large amount data that may be of no use in the future. Therefore, we recommended hybrid systems that the on-premises and the cloud environments are combined for data storage and backup systems that incur a major cost, and data analysis, processing and presentation that need operational flexibility, respectively.
Keywords
Agricultural climate data; Cloud; On-premises; Hybrid; Gluster file system;
Citations & Related Records
Times Cited By KSCI : 7  (Citation Analysis)
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