Journal of Korea Multimedia Society (한국멀티미디어학회논문지)

Korea Multimedia Society (한국멀티미디어학회)
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The Collaborative Image Editing Tool based On the Cloud Computing

클라우드 컴퓨팅 기반의 협업 이미지 제작 도구

  • Lim, Yang Mi (Dept. of Digital Media, Duksung Women's University)
  • Received : 2017.07.17
  • Accepted : 2017.08.01
  • Published : 2017.08.31
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Abstract

In recent times, IaaS (Infrastructure as a Services) have been rapidly evolving to allow developers to easily and efficiently access work in the server and network areas for development of a web of App based on cloud computing. In this study, we developed the collaborative image editing tool App based on Cloud-computing, by adopting AWS of representative company that develops IaaS. First, it is crucial to understand various situation conditions for representative infrastructure services: AWS, Azure and Google (GCP). This may have the effect of reducing manpower and development time, but as each company has different policy and technical support, we need a new study every time the environment changes of infrastructure services. We tried to develop a hybrid-App so that users with various devices can collaborate work each other by utilizing the infrastructure service AWS through the process of developing the image editing authoring tool based on the cloud computing. The future studies should continue about compatibility issues and support issues in order to minimize the problems of overseas infrastructure services, but we think that domestic cloud computing policies and developments should be urgently considered.

Keywords

References

  1. S.H. Park, H.J. Lee, S.H. Lee, K.R. Kwon, Y.K. Park, and K.D. Moon, "Collaboration Contents Fractal Service and Intrusion Detection Framework Based on Cloud," Journal of Korea Multimedia Society Vol. 20, No. 1, pp. 58-65, 2017. https://doi.org/10.9717/kmms.2017.20.1.058
  2. H.J. Lee, K.R. Kwon, S.H. Lee, Y.K. Park, and K.D. Moon, “Design of Open Scenario Structure for Content Creation Service Based on User Defined Story,” Journal of Korea Multimedia Society, Vol. 19, No. 2, pp. 170-179, 2016. https://doi.org/10.9717/kmms.2016.19.2.170
  3. KERIS, Feasibility Study on Strategic Planning to Build a Cloud Computing Environment for Smart Education, KERIS Issue Report Research Data RM 2011-19, 2011.
  4. D.W. Nurmi, R. Grzegorczyk, and C. Obertelli, "The Eucalyptus Open-Source Cloud-Computing System," Proceeding of 9th IEEE/ACM International Symposium, Cluster Computing and the Grid, pp. 124-131, 2009.
  5. B.Y. Lee, J. Park, and J.S Yoo, "Software Architecture of the Grid for Implementing the Cloud Computing of the High Availability," Journal of the Korea Contents Association, Vol. 12, No. 2, pp. 19-29, 2012. https://doi.org/10.5392/JKCA.2012.12.02.019
  6. B.D. Lee and S.U. Shin, "Design of Secure Log System in Cloud Computing Environment," Journal of Korea Multimedia Society, Vol. 19, No. 2, pp. 300-307, 2016. https://doi.org/10.9717/kmms.2016.19.2.300
  7. Cloud Academy Blog of Motasem Aldiab, https://cloudacademy.com/blog/public-cloud-war-aws-vs-azure-vs-google (accessed July, 16, 2017).
  8. IDG Network, http://www.ciokorea.com/news/ (accessed July, 16, 2017).
  9. Adobe Systems Inc, http://www.phonegap.com (accessed July, 16, 2017).
  10. Axway, http://www.appcelerator.com/ (accessed July, 16, 2017).
  11. $SmartPhoneMart^{TM}$, https://www.smartphonemart.net/ (accessed July, 16, 2017).
  12. S.M. Han, Y.S. Son, and Y.S. Lee, "Design and Implementation of the Smart Virtual Machine for Smart Cross Platform," Journal of Korea Multimedia Society, Vol. 16, No. 2, pp. 190-197, 2013. https://doi.org/10.9717/kmms.2013.16.2.190
  13. Amazon Elastic Compute Cloud (EC2), http://aws.amazon.com/ec2 (accessed July, 16, 2017).
  14. J.M. Kim, I.B. Park, and Y.M. Lim, "Real-Time Collaborative Tool Based on Cloud Computing," Proceeding of Korea Multimedia Society Autumn Conference, Vol. 19, No. 2, pp. 819-820, 2016.

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