Browse > Article
http://dx.doi.org/10.12672/ksis.2014.22.5.001

An Open Source Mobile Cloud Service: Geo-spatial Image Filtering Tools Using R  

Kang, Sanggoo (Dept. of Information Systems Engineering, Hansung University)
Lee, Kiwon (Dept. of Information Systems Engineering, Hansung University)
Publication Information
Spatial Information Research / v.22, no.5, 2014 , pp. 1-8 More about this Journal
Abstract
Globally, mobile, cloud computing or big data are the recent marketable key terms. These trend technologies or paradigm in the ICT (Information Communication Technology) fields exert large influence on the most application fields including geo-spatial applications. Among them, cloud computing, though the early stage in Korea now, plays a important role as a platform for other trend technologies uses. Especially, mobile cloud, an integrated platform with mobile device and cloud computing can be considered as a good solution to overcome well known limitations of mobile applications and to provide more information processing functionalities to mobile users. This work is a case study to design and implement the mobile application system for geo-spatial image filtering processing operated on mobile cloud platform built using OpenStack and various open sources. Filtering processing is carried out using R environment, recently being recognized as one of big data analysis technologies. This approach is expected to be an element linking geo-spatial information for new service model development and the geo-spatial analysis service development using R.
Keywords
Mobile Cloud; Cloud Computing; Image Filtering; R;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
연도 인용수 순위
1 CRAN R, Accessed July 16. http://cran.r-project.org/
2 Almeer, M. H. 2012, Cloud Hadoop Map Reduce For Remote Sensing Image Analysis, Journal of Emerging Trends in Computing and Information Sciences, 3(4):637-644.
3 Bordese, M; Alini, W. 2013, Package 'biOps' Reference Manual, Accessed July 16. http://cran.rproject.org/web/packages/biOps/biOps.pdf
4 CRAN Contributed Packages, Accessed July 16. http://cran.r-project.org/web/packages/
5 Evangelidis, K; Ntouros, K; Makridis, S; Papatheodorou, C. 2014, Geospatial services in the Cloud, Computers and Geosciences, 63:116-122.   DOI
6 Hung, S-H; Shih, C-S; Shieh, J-P; Lee, C-P; Huang, Y-H. 2012, Executing Mobile Applications on the Cloud: Framework and Issues, Computers and Mathematics with Applications, 63(2):573-587.   DOI
7 Fernando, N; Loke, S. W; Rahayu, W. 2013, Mobile Cloud Computing: A Survey, Future Generation Computer Systems, 29(1):84-106.   DOI   ScienceOn
8 Gartner. 2013, Gartner Identifies the Top 10 Strategic Technology Trends for 2014, Accessed July 16. http://www.gartner.com/newsroom/id/2603623
9 Hong, S. T; Shin, Y. S; Chang, J. W. 2011, Optimization and Performance Analysis of Cloud Computing Platform for Distributed Processing of Big Data, Journal of Korea Spatial Information Society, 19(4): 55-71.   과학기술학회마을
10 Hwang, J. R; Kim, T. H; Choi, H. S. 2012, A Study on the Strategies for Promoting Spatial Information Service for Mobile Environment, Journal of Korea Spatial Information Society, 20(4): 57-67.   과학기술학회마을   DOI   ScienceOn
11 Kang, S; Lee, K; Kim, Y. 2012, Preliminary Performance Testing of Geo-spatial Image Parallel Processing in the Mobile Cloud Computing Service, Korean Journal of Remote Sensing, 28(4):467-475.   과학기술학회마을   DOI   ScienceOn
12 Khan, A. R; Othman, M; Madani, S. A; Khan, S. U. 2014, A Survey of Mobile Cloud Computing Application Models, IEEE Communications Surveys & Tutorials, 16(1):393-413.   DOI
13 Kang, S; Lee, K. 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.   과학기술학회마을   DOI
14 Kang, S; Lee, K. 2013, Mobile App Approach by Open Source Stack for Satellite Images Utilization, Remote Sensing Letters, 4(7):648-656.   DOI
15 Kang, S; Kim, K; Lee, K. 2013, Tablet Application for Satellite Image Processing on Cloud Computing Platform, Paper presented at the International Geoscience and Remote Sensing Symposium, Melbourne, Australia, July 21-26.
16 Kang, S; Kim, K; Lee, K. 2014, Mobile Application for Geo-spatial Image Processing using R on Cloud Computing, Paper presented at the Conference on Geo-Spatial Information 2014 Spring, May 23.
17 Kang, S; Lee, K. 2014, Mobile Application Service of Satellite Image Fusion on OpenStack Cloud Platform, Paper presented at the International Conference on Earth Observations and Societal Impacts 2014, June 22-24.
18 Kim, K; Kang S; Lee, K. 2013, Geo-based Image Blending in a Mobile Cloud Environment, Remote Sensing Letters, 4(11):1117-1126.   DOI   ScienceOn
19 Kouyoumjian, V. 2011, Demystifying the Cloud, Geoconnexion International Magazine, March 2011:46-48.
20 Lance, A. 2012, Comparing Open Source Private Cloud (IaaS) Platforms, open source convention, http://cdn.oreillystatic.com/en/assets/1/event/80/Comparing Open Source Private Cloud PlatformsPresentation.pdf.
21 Lee, D. W; Liang, S. H. L. 2011, Geopot: A Cloudbased Geolocation Data Service for Mobile Applications, International Journal of Geographical Information Science, 25(8):1283-1301.   DOI
22 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(3):337-346.   과학기술학회마을   DOI
23 Yue, P; Zhou, H; Gong, J; Hu, L. 2013, Geoprocessing in Cloud Computing Platforms-A Comparative Analysis, International Journal of Digital Earth, 6(4):404-425.   DOI
24 Lee, K.; Kang, S. 2013, Mobile Cloud Service of Geo-based Image Processing Functions: A Test iPad Implementation, Remote Sensing Letters, 4(9): 910-919.   DOI   ScienceOn
25 Ma, X; Cui, Y; Stojmenovic, I. 2012, Energy Efficiency on Location Based Applications in Mobile Cloud Computing: A Survey, Procedia Computer Science, 10:577-584.   DOI
26 Mell, P; Grance, T. 2011, The NIST Definition of Cloud Computing, NIST Special Publication 800-145, Accessed July 16. http://csrc.nist.gov/publications/nistpubs/800-145/SP800-145.pdf
27 NIPA. 2013, ICT Spot Issue, August, 9-16.
28 Van Rees, E. 2010, Challenges and Possibilities: ESRI and Cloud computing, GEO Informatics, Sept. 2010:24-26.
29 Wang, L; Kunze, M; Tao, J; von Laszewski, G. 2011, Towards Building a Cloud for Scientific Applications, Advances in Engineering Software, 42(9):714-722.   DOI
30 Wang, P; Wang, J; Chen, Y; Ni, G. 2013, Rapid Processing of Remote Sensing Images based on Cloud Computing, Future Generation Computer Systems, 29(8):1963-1968.   DOI