- Volume 28 Issue 4
DOI QR Code
Preliminary Performance Testing of Geo-spatial Image Parallel Processing in the Mobile Cloud Computing Service
모바일 클라우드 컴퓨팅 서비스를 위한 위성영상 병렬 정보처리 성능 예비실험
- Kang, Sang-Goo (Dept. of Information Systems Engineering, Hansung University) ;
- Lee, Ki-Won (Dept. of Information Systems Engineering, Hansung University) ;
- Kim, Yong-Seung (Satellite Information Research Center, Korea Aerospace Research Institute)
- Received : 2012.07.18
- Accepted : 2012.08.23
- Published : 2012.08.31
Cloud computing services are known that they have many advantages from the point of view in economic saving, scalability, security, sharing and accessibility. So their applications are extending from simple office systems to the expert system for scientific computing. However, research or computing technology development in the geo-spatial fields including remote sensing applications are the beginning stage. In this work, the previously implemented smartphone app for image processing was first migrated to mobile cloud computing linked to Amazon web services. As well, parallel programming was applied for improving operation performance. Industrial needs and technology development cases in terms of mobile cloud computing services are being increased. Thus, a performance testing on a satellite image processing module was carried out as the main purpose of this study. Types of implementation or services for mobile cloud varies. As the result of this testing study in a given condition, the performance of cloud computing server was higher than that of the single server without cloud service. This work is a preliminary case study for the further linkage approach for mobile cloud and satellite image processing.
Supported by : 한국항공우주연구원
- 강상구, 이기원, 2010. 위성영상정보 분석을 위한 안드로이드 스마트폰 앱 개발, 대한원격탐사학회지, 26: 561-570.
- 강상구, 이기원, 2011. 위성영상정보 기반 코너 포인트 객체 추출 안드로이드 스마트폰 앱 개발, 대한원격탐사학회지, 27: 33-41.
- 강상구, 이기원, 2012. 공간영상정보 클라우드 서비스를 위한 스마트폰 앱 개발 전략, 한국지리정보학회 2012 춘계학술대회.
- 김광섭, 이기원, 2012. 클라우드 컴퓨팅 연계 모바일 3차원 공간객체 처리 기술 분석, 한국지리정보학회 2012 춘계학술대회.
- 유선실, 2012. 개인용 클라우드 (Personal Cloud) 서비스 동향, 방송통신정책, 24: 43-48.
- 한국전자통신연구원, 2011. 공개 SW기반 클라우드 기술 현황, 전자통신동향분석, 26: 43-54.
- 한국정보화진흥원, 2011. 2012년 IT 트렌드 전망 및 정책방향, IT 정책연구시리즈, 21p.
- Alonso-Calvo, R., J. Crespo, M. Garcia-Remesal, A. Anguita, and V. Maojo, 2010. On distributing load in cloud computing: A real application for very-large image datasets, Procedia Computer Science, 1: 2669-2677. https://doi.org/10.1016/j.procs.2010.04.300
- Armbrust, M., A. Fox, R. Griffith., A.D. Joseph, R. Katz, A. Konwinski, G. Lee, D. Patterson, A. Rabkin, I. Stoica, and M. Zaharia, 2009. Above the Coluds: A Berkeley View of Cloud Computing, University of California Berkeley Technical Report, UCB/EECS-2009-28.
- Barnatt, C., 2010. A Brief Guide to Cloud Computing. Constable & Robinson Ltd., 289p.
- Dean, J. and S. Ghemawat, 2004. MapReduce: Simplified Data Processing on Large Clusters, Proceedings of the 6th Symposium on Operating Systems Design and Implementation, pp. 137-150.
- Endo, P.T., G.E. Goncalves, J. Kelner, and D. Sadok, 2010. A Survey on Open-source Cloud Computing Solutions, Brazilian Symposium on Computer Networks and Distributed Systems.
- Fernando, N., S. W. Loke, and W. Rahayu, 2013. Mobile cloud computing: A survey, Future Generation Computer Systems, 29: 84-106. https://doi.org/10.1016/j.future.2012.05.023
- Iosup, A., S. Ostermann, N. Yigitbasi, R. Prodan, T. Fahringer, and D. Epema, 2011. Performance analysis of cloud computing services for many-tasks scientific computing, IEEE Trans. Parallel Distrib. Syst., 22: 931-945. https://doi.org/10.1109/TPDS.2011.66
- Lee, K., 2012. Open Source Cloud Computing: An Experience Case of Geo-based Image Handling in Amazon Web Services, Korean Journal of Remote Sensing, 28: 337-346. https://doi.org/10.7780/kjrs.2012.28.3.337
- Ostermann, S., A. Iosup, N. Yigitbasi, R. Prodan, T. Fahringer, and D. Epema, 2010. A Performance Analysis of EC2 Cloud Computing Services for Scientific Computing, Cloudcomp: 115-131.
- OTB Development Team, 2010. The ORFEO Tool Box Software Guide, Updated for OTB-3.8, 670p.
- Sempolinski, P. and D. Thain, 2010. A Comparison and Critique of Eucalyptus, OpenNebula and Nimbus, IEEE International Conference on Cloud Computing Technology and Science, pp. 417-426.
- Sriram, I. and K.-H. Ali, 2010. Research Agenda in Cloud Technologies, 1st ACM Symposium on Cloud Computing, http://arxiv.org/ftp/arxiv/papers/1001/ 1001.3259.pdf.
- Xiong, K. and H. Perros, 2009. Service Performance and Analysis in Cloud Computing, Proceedings of the 2009 Congress on Services I.: 693-700.
- Zhang, S., H. Yan, and X. Chen, 2012. Research on Key Technologies of Cloud Computing, Physics Procedia, 33: 1791-1797. https://doi.org/10.1016/j.phpro.2012.05.286
- Mobile cloud service of geo-based image processing functions: a test iPad implementation vol.4, pp.9, 2013, https://doi.org/10.1080/2150704X.2013.810821
- A Performance Test of Mobile Cloud Service for Bayesian Image Fusion vol.30, pp.4, 2014, https://doi.org/10.7780/kjrs.2014.30.4.3
- Evaluation of Geo-based Image Fusion on Mobile Cloud Environment using Histogram Similarity Analysis vol.31, pp.1, 2015, https://doi.org/10.7780/kjrs.2015.31.1.1
- WPS-based Satellite Image Processing onWeb Framework and Cloud Computing Environment vol.31, pp.6, 2015, https://doi.org/10.7780/kjrs.2015.31.6.6