期刊
REMOTE SENSING
卷 8, 期 8, 页码 -出版社
MDPI AG
DOI: 10.3390/rs8080662
关键词
auto-scaling; cloud computing; OpenStack; satellite image processing
类别
资金
- National Land Space Information Research Program from Ministry of Land, Infrastructure and Transport, Korea [14NSIP-B080144-01]
- Korea Agency for Infrastructure Technology Advancement (KAIA) [80793] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
Cloud computing is a base platform for the distribution of large volumes of data and high-performance image processing on the Web. Despite wide applications in Web-based services and their many benefits, geo-spatial applications based on cloud computing technology are still developing. Auto-scaling realizes automatic scalability, i.e., the scale-out and scale-in processing of virtual servers in a cloud computing environment. This study investigates the applicability of auto-scaling to geo-based image processing algorithms by comparing the performance of a single virtual server and multiple auto-scaled virtual servers under identical experimental conditions. In this study, the cloud computing environment is built with OpenStack, and four algorithms from the Orfeo toolbox are used for practical geo-based image processing experiments. The auto-scaling results from all experimental performance tests demonstrate applicable significance with respect to cloud utilization concerning response time. Auto-scaling contributes to the development of web-based satellite image application services using cloud-based technologies.
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