References
- Consortium of Cloud Computing Research. 2017. Cloud computing technologies stack v.3 (한국클라우드컴퓨팅연구조합, 2017, 클라우드 컴퓨팅 기술 스택).
- Geospatial World. 2014. Cloud for GIS systems. Available at: https://www.geospa tialworld.net/article/cloud-for-gissystems/(Accessed September 07, 2017).
- IDG(International Data Group, Inc). 2015. 2015 Cloud computing issues and prospect. http://www.itworld.co.kr/techlibrary/96754 (2015 클라우드 컴퓨팅 과제와 전망)(Accessed September 07, 2017).
- IDG(International Data Group, Inc) Market. 2016. Korea PaaS Market, when and where will it launch ?. Available at: http: //www.itworld.co.kr/techlibrary/100718 (국내 PaaS 시장, 언제 어디서부터 열릴까?) (Accessed September 07, 2017).
- IDG(International Data Group, Inc), 2016. Security instead of fads, practical use rather than concept, prerequisite for Korean private cloud. Available at: http://www.itworld.co.kr/techlibrary/100769 ("유행 대신 보안, 컨셉 아닌 실용"한국형 프 라이빗 클라우드의 요건) (Accessed September 07, 2017).
- IDG(International Data Group, Inc), 2017. Cloud for enterprise survival, getting ready. Available at: http://www.itworld.co. kr/techlibrary/105377 (기업 생존을 위한 클라우드, 제대로 준비하고 계십니까) (Accessed September 07, 2017).
- Kang, S.G and K.W Lee. 2013. Testing implementation of remote sensing image analysis processing service on OpenStack of open source cloud platform. Journal of the Korean Association of Geographic Information Studies 16(4):141-152 (강상구, 이기원, 2012. 오픈소스 클라우드 플랫폼 OpenStack 기반 위성영상분석처리 서비스 시험구현, 한국지리정보학회지 16(4):141-152). https://doi.org/10.11108/kagis.2013.16.4.141
- Kang, S.G and K.W Lee. 2014. An open source mobile cloud service: geo-spatial image filtering tools using R. Journal of Korea Spatial Information Society 22(5): 1-8 (강상구, 이기원, 2015. 오픈소스 모바일 클라우드 서비스: R 기반 공간영상정보 필터링 사례, 한국공간정보학회지 22(5):1-8).
- Kouyoumjian, V. 2011. GIS in the cloud-the new age of cloud computing and geographic information systems. ESRI, p.31.
- Kim, D.H. 2016. An open source GIS based planning support system for abandoned, vacant, and underutilized land. Journal of the Korean Association of Geographic Information Studies 19(4): 1-16 (김동한. 2016. 유휴공간 분석을 위한 오픈소스 GIS 기반의 계획지원체계. 한국지리정보학회지 19(4):1-16). https://doi.org/10.11108/KAGIS.2016.19.4.001
- Kim, J., T.J. Kim, Y.I. Kim, S.N. Park, and S,G. Bae. 2017. GIS cloud service plan in the proceedings of the 9th KSIS Conference p.200. (김진, 김택진, 김영일, 박상남, 배상근. 2017. 공간정보시스템 클라우드 서비스 방안. 제9회 한국공간정보학회 신년학술대회 발표자료 모음집 200쪽).
- Jeong, U.J., D.J. Kim, and S.I. Jung. 2011. Trend of open source SW-based cloud computing technology. Electronics and Telecommunications Trends. 26(5):43-54 (정의정, 김동재, 정성인. 2011. 공개 SW기반 클라우드 컴퓨팅 기술 현황. 전자통신동향 분석 26(5):43-54).
- Lee, I.S., Y. Huh, J.K. Lee, and J.W. Lee. 2016. Cloud technology for geospatial information -focus on data as a service-. Journal of the Korean Cadastre Information Association 18(2):3-16 (이인수, 허용, 이재강, 이재원, 2016. 클라우드의 공간 정보분야 연계 방안 연구 -DaaS (Data as a Service) 중심으로-. 한국지적정보학회지 18(2):3-16).
- Lee, K.W. 2012. Open source cloud computing: an experience case of geobased image handling in Amazon web services. Korean Journal of Remote Sensing 2(3):337-346.
- Leung, K. 2011. GIS on cloud computing. ESRI. p.38. Available at: http://www.lsgi.polyu.edu.hk/staff/Bo.Wu/event/ASSIST 2011/pdf/ASSIST_11_KLeung.pdf (Accessed September 07, 2017).
- Myserson, J. 2014. Five open source PaaS options you should know. Available at: http://www.techrepublic.com/article/fiveopen-source-paas-options-you-should-know/ (Accessed September 07, 2017).
- Navercast. 2016. IaaS, PaaS, SaaS. Available at: http://terms.naver.com/entry.nhn?docId=3580686&cid=59088&categoryId=59096(Accessed September 07, 2017).
- Seo, B.K. 2017. DevOps based on cloud platform and practical architecture of micro service. Proceedings of Open Technet Summit 2017 (서보국. 2017. 클라우드 플랫폼 기반 데브옵스 및 마이크로 서비스 아키텍처 실무. 오픈 테크넷 서밋 2017. Accessed June 21, 2017).
- SPACEN(Spatial Information Industry Promotion Institute). 2016. Execution direction of R&D roadmap in 2016 geo-based Information Research Enterprise Open Forum (공간정보산업진흥원. 2016. 공간정보 분야 융복합 산업 창출을 위한 R&D 로드맵 추진방향. 2016년 국토공간정보연구사업오픈포럼).
- Troutman, A. 2017. Solutions review 2017 cloud platforms buyers guide. Available at: https://solutionsreview.com/ (Accessed August 19, 2017).
- Yang, C., Y. Xu, and D. Nebert. 2013. Redefining the possibility of digital earth and geosciences with spatial cloud computing. Journal International Journal of Digital Earth 6(4):297-312. https://doi.org/10.1080/17538947.2013.769783
- Yoo, H.Y., K.W. Lee, K.J. Lee, and Y.S. Kim. 2013. Questionnaire analysis of geo-spatial open source application. Journal of the Korean Association of Geographic Information Studies 16(4): 106-119 (유희영, 이기원, 이광재, 김용승. 2013. 공간정보 오픈소스 활용 설문조사에 따른 현황 분석. 한국지리정보학회지 16(4): 106-119). https://doi.org/10.11108/kagis.2013.16.4.106
- Yoon, G.S. and K.W. Lee. 2015. WPSbased satellite image processing on web framework and cloud computing environment. Korean Journal of Remote Sensing 31(6):561-570 (윤구선, 이기원. 2015. 클라우드 컴퓨팅과 웹 프레임워크 환경에서 WPS 기반 위성영상 정보처리. 대한원격탐사학회지 31(6):561-570). https://doi.org/10.7780/kjrs.2015.31.6.6
- Yoon, G.S., K.S Kim, and K.W. Lee. 2016. Performance testing of satellite image processing based on OGC WPS 2.0 in the OpenStack cloud environment. Korean Journal of Remote Sensing 32(6):617-627 (윤구선, 김광섭, 이기원, 2016. 오픈스택 클라우드 환경 OGC WPS 2.0 기반 위성영상처리 성능측정 시험. 대한원격탐사학회지. 32(6):617-627). https://doi.org/10.7780/kjrs.2016.32.6.6
- Yoon, G.S., K.S. Kim, and K.W. Lee. 2017. Linkage of OGC WPS 2.0 to the e-government standard framework in Korea: an implementation case for geo-spatial image processing. ISPRS International Journal of Geo-Information 6(1):25. https://doi.org/10.3390/ijgi6010025
- Youn, J.H., C.Y. Kim, and H.S. Moon. 2017. The establishment for technology development plan for national spatial information infrastructure cloud service. Journal of the Korea Academia-Industrial Cooperation Society 18(3):469-477 (윤준희, 김창윤, 문현석. 2017. 국가 공간정보인프라의 클라우드 서비스 기술개발 방안 수립. 한국산학기술학회논문지 18(3):469-477). https://doi.org/10.5762/KAIS.2017.18.3.469
- Yuan, M. 2011. A Java developer's guide to PaaS. Available at: https://www.infoq.com/articles/paas_comparison (Accessed May 19, 2017).
Cited by
- A Performance Evaluation of a Geo-Spatial Image Processing Service Based on Open Source PaaS Cloud Computing Using Cloud Foundry on OpenStack vol.10, pp.8, 2018, https://doi.org/10.3390/rs10081274