A Framework of Adaptive Video Publishing and sharing in Cloud Network
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Abstract
The video traffic demands are raising over a mobile network through wireless link capacity cannot meet with the demand of video traffic. The increasing traffic demand is considered by video streaming and downloading. As a result, there is a gap between link capacity and traffic demands together with the time varying condition which results in the poor quality of video streaming service over a mobile network such as sending long buffering time and intermittent disruptions due to limited bandwidth and wireless link condition. Cloud computing provides various advanced services, AMES cloud network framework built to provide video services to user, it has two main parts: Efficient social video sharing and Adaptive mobile video streaming which built a private agent, which provides video streaming service for each user in the network efficiently. Thus, it provides efficient storage over cloud network.
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References
Y. Li, Y. Zhang, and R. Yuan, “Measurement and Analysis of a Large Scale Commercial Mobile Internet TV System,†in ACM IMC, pp. 209–224, 2011.
Y. Fu, R. Hu, G. Tian, and Z. Wang, “TCP-Friendly Rate Control for Streaming Service Over 3G network,†in WiCOM, 2006.
M. Wien, R. Cazoulat, A. Graffunder, A. Hutter, and P. Amon, “Real-Time System for Adaptive Video Streaming Based on SVC,†in IEEE Transactions on Circuits and Systems for Video Technology, vol. 17, no. 9, pp. 1227–1237, Sep. 2007.
D. Niu, H. Xu, B. Li, and S. Zhao, “Quality-Assured Cloud Bandwidth Auto-Scaling for Video-on-Demand Applications,†in IEEE INFOCOM, 2012.
S. Chetan, G. Kumar, K. Dinesh, K. Mathew, and M. A. Abhimanyu, “Cloud Computing for Mobile World,†Tech. Rep., 2010.
Q. Zhang, L. Cheng, and R. Boutaba, “Cloud Computing: State-of-the-art and Research Challenges,†in Journal of Internet Services and Applications, vol. 1, no. 1, pp. 7–18, Apr. 2010.
Y. Li, Y. Zhang, and R. Yuan, “Measurement and Analysis of a Large Scale Commercial Mobile Internet TV System,†in ACM IMC, pp. 209–224, 2011.
P. McDonagh, C. Vallati, A. Pande, and P. Mohapatra, “Quality-Oriented Scalable Video Delivery Using H. 264 SVC on An LTE Network,†in WPMC, 2011.
Kamarthi Rekha, R. Vara Prasad and Dr.S.Prem Kumar,†User Adaptive Mobile Video Streaming and Resourceful Video Sharing in Cloud. “International Journal of Computer Engineering in Research Trends., vol.1, no.1, pp. 1-7, 2014.
Gattu Uma Maheswari, E Ramya,†A Structure of Adaptive Mobile Video Streaming and Methodical Social Video Sharing In the Cloud. “International Journal of Computer Engineering in Research Trends., vol.2, no.12, pp. 837-841, 2015.
M.SHIRISHA, M.RADHA,†AMES-Cloud: A Framework of AMOV & ESOV using Clouds. “International Journal of Computer Engineering in Research Trends., vol.2, no.5, pp. 305-309, 2015.