CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
Reseach Article

A Framework for Cloud Assisted Adaptive Video Streaming to Enhance User QoE

by G. Rajasekaran, K. Keerthiga
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 180 - Number 21
Year of Publication: 2018
Authors: G. Rajasekaran, K. Keerthiga
10.5120/ijca2018916501

G. Rajasekaran, K. Keerthiga . A Framework for Cloud Assisted Adaptive Video Streaming to Enhance User QoE. International Journal of Computer Applications. 180, 21 ( Feb 2018), 37-43. DOI=10.5120/ijca2018916501

@article{ 10.5120/ijca2018916501,
author = { G. Rajasekaran, K. Keerthiga },
title = { A Framework for Cloud Assisted Adaptive Video Streaming to Enhance User QoE },
journal = { International Journal of Computer Applications },
issue_date = { Feb 2018 },
volume = { 180 },
number = { 21 },
month = { Feb },
year = { 2018 },
issn = { 0975-8887 },
pages = { 37-43 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume180/number21/29059-2018916501/ },
doi = { 10.5120/ijca2018916501 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:01:21.962765+05:30
%A G. Rajasekaran
%A K. Keerthiga
%T A Framework for Cloud Assisted Adaptive Video Streaming to Enhance User QoE
%J International Journal of Computer Applications
%@ 0975-8887
%V 180
%N 21
%P 37-43
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The drastic increase in the usage of handheld devices like smartphones, tablets, etc., produce huge traffic on the Internet which are mainly due the video streaming services applications. Due to the limitations of resources (Power, Memory, Processing, etc.), numerous design patterns of the mobile devices and heterogeneous users' expectations, it is difficult to handle those video streaming services requests. In order to provide an expected experience to the end user and to reduce the burden of the service providers, cloud computing provides the most easy and viable solution. A novel framework in cloud environment has been proposed in this paper to provide a good trade-off between the service handling as well as the user experience. The framework covers various aspects related to streaming services such as user experience, content distribution and retrieval, power usage, network analysis, video storage, device analysis on static and runtime conditions, parallel service provision and the experience perceived by user.

References
  1. “Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2011–2016,” CISCO, 2012.
  2. M. Armbrust, A. Fox, R. Griffith, A. D. Joseph,R.Katz, A. Konwinski,G. Lee, D. Patterson, A. Rabkin, I. Stoica, and M. Zaharia, “A view of cloud computing,” Commun. ACM, vol. 53, pp. 50-58, Apr. 2010.
  3. Viktor Mauch, Marcel Kunze, Marius Hillenbrand, ”High Performance cloud computing, ”, Future Generation Computer System.Elsevier,vol.29,No.6,pp.1408-1416, Aug.2013.
  4. Y. K. Lai, Y. F. Lai, and P. Y. Chen, “Content-based LCD backlight power reduction with image contrast enhancement using histogram analysis,” J. Display Technol., vol. 7, no. 10, pp. 550–555, 2011.
  5. J. M. Kang, S. S. Seo, and J. W. Hong, “Personalized battery lifetime prediction for mobile devices based on usage patterns,” J. Computing Sci. Eng., vol. 5, no. 4, pp. 338–345, 2011.
  6. Fangming Liu, Peng Shu, Hai Jin,Linjie Ding, Jie Yu,Di Niu, and Bo Li,” Gearing resource-poor mobile devices with powerful clouds: architectures, challenges, and applications,”Wireless Communication.IEEE,vol.20,No.3,pp.14-22,June.2013.
  7. N. Davies, “The case for VM-Based Cloudlets in mobile computing,” IEEE Pervasive Computing, vol. 8, no. 4, pp. 14–23, Oct.-Dec. 2009.
  8. S. Kosta, A. Aucinas, P. Hui, R. Mortier, and X. Zhang, “Thinkair: Dynamic resource allocation and parallel execution in the cloud for mobile code offloading,” in Proc. IEEE INFOCOM, 2012.
  9. B. Aggarwal, N. Spring, and A. Schulman, “Stratus: Energy-efficient mobile communication using cloud support,” in Proc. ACM SIGCOMM, 2010, pp. 477–478.
  10. Seungjun Yang, Donghyun Kwon, Hayoon Yi, Yeongpil Cho,Yongin Kwon, Yunheung Paek,” Techniques to Minimize State Transfer Costs for Dynamic Execution Offloading in Mobile Cloud Computing,” Mobile Computing.IEEE Transactions,vol.13,No.11,pp.2648-2660,Nov.2014.
  11. X. Zhang, A. Kunjithapatham, S. Jeong, and S. Gibbs, “Towards an elastic application model for augmenting the computing capabilities of mobile devices with cloud computing,” Mobile Netw. Applicat., pp.1–15, Apr. 2011.
  12. Dijiang Huang, Tianyi Xing, and Huijun Wu, ”Mobile Cloud Computing Service Models: A User-Centric Approach,” IEEE Network, vol.27, pp. 6-11, Sep-Oct.2013.
  13. Yi Xu and Shiwen Mao, “A survey of mobile cloud computing for rich media applications,” Wireless Communications, IEEE,vol.20,No.3,pp.46-53, June-2013.
  14. Shaoxuan Wang and Sujit Dey,” Adaptive Mobile Cloud Computing to Enable Rich Mobile Multimedia Applications”, Multimedia.IEEETransactions,vol.15,No.4,pp.870-883,June.2013.
  15. Y. G. Wen, W. W. Zhang, K. Guan, D. Kilper, and H. Y. Luo, “Energy- optimal execution policy for a Cloud-assisted mobile application platform,” Sep. 2011.
  16. Antero Taivalsaari and Kari Systa,” Cloudberry: An HTML5 Cloud Phone Platform for Mobile Devices,”Software.IEEE,vol.29,No.4,pp.40-45,July-Aug.2012.
  17. W. Zhu, C. Luo, J. F. Wang, and S. P. Li, “Multimedia cloud computing,” IEEE Signal Process. Mag., vol. 28, no. 3, pp. 59–69,May. 2011.
  18. Heiko Schwarz,Detlev Marpe and Thomas Wiegand,” Overview of the Scalable Video Coding Extension of the H.264/AVC Standard,” Circuits and Systems for video Technology.IEEE Transactions, vol.17,No.9,pp. 1103 – 1120,Sep.2007.
  19. A. Garcia and H. Kalva, “Cloud transcoding for mobile video content delivery,” in Proc. 2011 IEEE Int. Conf. Consumer Electronics (ICCE), pp. 379–380, 2011.
  20. Z. Huang, C. Mei, L. E. Li, and T. Woo, “CloudStream: Delivering high-quality streaming videos through a cloud-based SVC proxy,” in Proc. IEEE INFOCOM Mini-conf., 2011, pp. 201–205.
  21. Weiwen Zhang, Yonggang Wen ; Jianfei Cai ; Wu, D.O.,” Toward Transcoding as a Service in a Multimedia Cloud: Energy-Efficient Job-Dispatching Algorithm,” Vehicular Technology, IEEE Transactions,vol.63,No.5,pp.2002-2012,Jun.2014.
  22. Muhamad Felemban,Saleh Basalamah, and Arif Ghafoor,” A distributed cloud architecture for mobile multimedia services,” Network, IEEE,vol.27,No.5,pp.20-27, Sep-Oct 2013.
  23. Yao Liu, Fei Li ; Lei Guo ; Bo Shen ; Songqing Chen ; Yingjie Lan,” Measurement and Analysis of an Internet Streaming Service to Mobile Devices,” Parallel and Distributed Systems.IEEE Transactions,vol.24,No.11,pp.2240-2250,Nov.2013.
  24. Yu Wu, Zhizhong Zhang, Chuan Wu, Zongpeng Li and Francis C.M.Lau,” CloudMoV: Cloud-Based Mobile Social TV”, Multimedia.IEEETranscations,vol.15,No.4,pp.821-832,June.2013.
  25. Mathias Wien,Renaud Cazoulat,Andreas Graffunder,Andreas Hutter,and Peter Amon,”Real-Time System for Adaptive Video Streaming Based on SVC,”Circuits and Systems for video Technology.IEEE Transactions, vol.17,No.9,pp. 1227 - 1237 ,Sep.2007.
  26. Xiaofei Wang, MinChen, Ted Taekyoung Kwon, LaurenceT. Yang, , and Victor C. M. Leung,” AMES-Cloud: A Framework of Adaptive Mobile Video Streaming and Efficient Social Video Sharing in the Clouds,”Multimedia.IEEE Transactions,vol.15,No.4,pp.811-820,June.2013.
  27. Xiaofei Wang and Min Chen,” PreFeed: Cloud-Based Content Prefetching of Feed Subscriptions for Mobile Users”, Systems Journal, IEEE,vol.8,No.1,pp.202-207,March-2014.
  28. X. Jin and Y. K. Kwok, “Cloud assisted p2p media streaming for bandwidth constrained mobile subscribers,” in Proc. IEEE Int. Conf. Parallel and Distributed Syst., 2010, pp. 800–805.
  29. Ke Xua, Ming Zhangb, , Jiangchuan Liuc, Zhijing Qind and Mingjiang Yea, ” Proxy caching for peer-to-peer live streaming, ”Computer Networks.Elsevier,vol.54,No.7,pp.1229-1241,May.2010.
  30. Kalpana Seshadrinathan,Rajiv Soundararajan,Alen Conrad Bovik, and Lawrence K.Cormack,” Study of Subjective and Objective Quality Assessment of Video,” Image Processing.IEEE Transactions,vol.19,No.6,pp.1427-1441,June.2010.
  31. Chikkerur, S., Sundaram, V.,Reisslein, M., and Karam, L.J.,” Objective Video Quality Assessment Methods: A Classification, Review, and Performance Comparison,” Broadcasting. IEEE Transactions,vol.57,No.2,pp.165-182,June-2011.
  32. Weiwen Zhang, Yonggang Wen, Zhenzhong Chen, and Ashish Khisti,” QoE-Driven Cache Management for HTTP Adaptive Bit Rate Streaming Over Wireless Networks,”Multimedia.IEEE Transactions,vol.15,No.6,pp.1431-1445,Oct.2013
  33. Wu-Hsiao Hsu and Chi-Hsiang Lo,” QoS/QoE Mapping and Adjustment Model in the Cloud-based Multimedia Infrastructure,”IEEE Systems Journal,vol.8,No.1,pp.247-255,March.2014.
  34. Vuclip.[Online].Available: http://www.vuclip.com/index.html
Index Terms

Computer Science
Information Sciences

Keywords

Cloud Computing Video Streaming Quality of Experience (QoE) Transcoding Cloudlet.