JACIII Vol.23 No.1 pp. 72-77
doi: 10.20965/jaciii.2019.p0072


Research on Key Technologies of Massive Videos Management Under the Background of Cloud Platform

Lin Jin and Changhong Yan

School of Economics, Yancheng Institute of Technology
No.20 the Yellow Sea Middle Road, Yancheng City, Jiangsu 224001, China

Corresponding author

March 27, 2018
June 1, 2018
January 20, 2019
massive videos, video management, cloud platform

With the rapid development of mobile internet and smart city, video surveillance is popular in areas such as transportation, schools, homes, and shopping malls. It is important subject to manage the massive videos quickly and accurately. This paper tries to use Hadoop cloud platform for massive video data storage, transcoding and retrieval. The key technologies of cloud computing and Hadoop are introduced firstly in the paper. Then, we analyze the functions of video management platform, such as user management, videos storage, videos transcoding, and videos retrieval. According to the basic functions and cloud computing, each module design process and figure are provided in the paper. The massive videos management system based on cloud platform will be better than the traditional videos management system in the aspects of storage capacity, transcoding performance and retrieval speed.

Cite this article as:
L. Jin and C. Yan, “Research on Key Technologies of Massive Videos Management Under the Background of Cloud Platform,” J. Adv. Comput. Intell. Intell. Inform., Vol.23, No.1, pp. 72-77, 2019.
Data files:
  1. [1] H. Han, D. Qi, and B. Feng, “Video surveillance integrated service platform based on cloud computing tecllnologies,” Computer Engineering and Design, Vol.34, Issue 5, pp. 1657-1662, 2013.
  2. [2] Y. Li, Z. Liu, X. Li, and G. Yu, “Design of massive video conversion platform based on cloud computing,” Experimental Technology and Management, Vol.29, No.3, pp. 98-100, 119, 2012.
  3. [3] Z. Peng, Y. Zhou, and Z. Wen, “Monitoring system of digital video forensics based on cloud computing platform,” Application Research of Computers, Vol.28, No.8, pp. 2974-2977, 2011.
  4. [4] W. Dong, “Cloud Platform Multimedia Video Information Conflict Prevention Scheduling Algorithm Simulation,” Computer Simulation, Vol.32, No.7, pp. 340-343, 2015.
  5. [5] R. Buyya et al., “Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility,” Future Generation computer systems, Vol.25, No.6, pp. 599-616, 2009.
  6. [6] Q. Chen and Q. Deng, “Cloud computing and its key techniques,” J. of Computer Applications, Vol.29, No.9, p. 2565, 2009.
  7. [7] H. T. Dinh et al., “A survey of mobile cloud computing: architecture, applications, and approaches,” Wireless Communications and Mobile Computing, Vol.13, No.18, pp. 1587-1611, 2013.
  8. [8] S. Subashini and V. Kavitha, “A survey on security issues in service delivery models of cloud computing,” J. of Network and Computer Applications, Vol.34, No.1, pp. 1-11, 2011.
  9. [9] M. R. Rahimi et al., “Mobile cloud computing: A survey, state of art and future directions,” Mobile Networks and Applications, Vol.19, No.2, pp. 133-143, 2014.
  10. [10] P. Dašić, J. Dašić, and B. Crvenković, “Service models for cloud computing: Video Surveillance as a Service (VSaaS),” Bulletin of the Transilvania, University of Braşov, Series I: Engineering Sciences, Vol.9, No.1, 2016.
  11. [11] Y. Wang et al., “A New QoE-Driven Video Cache Management Scheme with Wireless Cloud Computing in Cellular Networks,” Mobile Networks and Applications, pp. 1-11, 2016.
  12. [12] Y. Xiong et al., “Design and Implementation of a Prototype Cloud Video Surveillance System,” J. Adv. Comput. Intell. Intell. Inform., Vol.18, No.1, pp. 40-47, 2014.
  13. [13] Y. S. Hu et al., “Accelerating 3B single-molecule super-resolution microscopy with cloud computing,” Nature Methods, Vol.10, No.2, pp. 96-97, 2013.
  14. [14] W. Zhang et al., “A video cloud platform combing online and offline cloud computing technologies,” Personal and Ubiquitous Computing, Vol.19, No.7, pp. 1099-1110, 2015.
  15. [15] D. Hu et al., “Implementation of [J]. port based on completion port model,” Internet of Things Technology, Vol.3, pp. 56-58, 2014.
  16. [16] P. Zhou and C. Huang, “The use and analysis of the completion port model,” Jiangnan Software, Vol.2, pp. 12-15, 2012.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, IE9,10,11, Opera.

Last updated on Feb. 20, 2019