AMES-Cloud: A Framework of AMOV & ESOV using Clouds
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Abstract
The demand on video traffic concerning mobile networks have been increase rapidly above the usual level, the wireless link capacity cannot keep up with the traffic needed. The poor service quality of video flooding on mobile networks such as long buffering time and disturbance in continuity, are caused due to the separation between the traffic need and the capacity of link, along with time-varying link conditions. The advantage of Cloud Computing is that we propose a new mobile video streaming framework, named AMES-Cloud, which has two main parts: Adaptive Mobile Video streaming (AMOV) and Efficient Social Video sharing (ESOV), these construct a private agent to provide streaming services for each mobile user. For a given user, depending on feedback of quality of the link, AMOV makes her private agent to adjust the streaming flow with video coding technique. Similarly, ESOV detects the social network interactions among the users of mobile, and their private agents try to prefetch the video content. To clearly show the performance, we implement prototype of AMES-Cloud framework. Based on social network analysis, the private agents in clouds can impressively provide the adaptive streaming and perform video sharing.
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References
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.
H. Schwarz and M. Wien, “The Scalable Video Coding Extension of The H. 264/AVC Standard,” in IEEE Signal Processing Magazine, vol. 25, no. 2, pp.135–141, 2008.
Srinivas P.M , Venkata Ravana Nayak ,“Efficient social video sharing in Mobile traffic on WWW using clouds,” in IJREAT International Journal of Research in Engineering & Advanced Technology, Volume 2, Issue 2, Apr-May, 2014.
Shobha. D Jalikoppa, “AMES-Cloud: A Framework of Adaptive Mobile Video Streaming and Efficient Social Video Sharing in the Clouds” in International Journal of Scientific Engineering and Researc h (IJSER) Volume 2 Issue6, June 2014.
Y. Chen, L. Qiu, W. Chen, L. Nguyen, and R. Katz, “Clustering Web Content for Efficient Replication,” in IEEE ICNP, 2002.
M. Cha, H. Kwak, P. Rodriguez, Y. Y. Ahn, and S. Moon, “I Tube, You Tube, Everybody Tubes: Analyzing the World’s Largest User Generated Content Video System,” in ACM IMC, 2007.
K. Bhavani,V Veena,“ A Framework For Video Streaming In Mobile Devices (AMoV and ESoV),” in International Conference on Computer & Communication Technologies 2K14 March 28-29, 2014.
XiaofeiWang, MinChen, Ted“Taekyoung”Kwon, LaurenceT.Yang, VictorC.M.Leung, “AMES-Cloud: A Framework of Adaptive Mobile Video Streaming and Efficient Social Video Sharing in the Clouds,” in IEEE TRANSACTIONS ON CLOUD COMPUTING VOL: 15 NO: 4 YEAR 2014.