Video Quality Adjustment Model Supporting Mobility for Seamless Multimedia Service Delivery

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Advanced multimedia computing technology is capable of providing user-oriented services for the user and the environment through context-awareness. This study seeks to provide seamless video delivery service with the focus on the user’s mobility patterns during a multimedia streaming service session. Mobility supporting technology which ensures the provision of seamless services can be classified into host mobility and user mobility. The former corresponds to host-level handoff while the latter refers to user-level handoff. In host-level handoff, the factors that directly affect the quality of video consumption are total distance between hosts, the distance for streaming resuming while user is in mobility mode as well as the screen size of the end host. The relationship among these parameters is analyzed by carrying out a user subjective assessment and an appropriate video quality model was developed, accordingly. The proposed quality model supporting seamless-mobility has a high correlation to the assessed quality and enables an adequate seamless mobility for multimedia service delivery.

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3482-3486

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January 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] Y. Cui. K. Nahrstedt, D. Xu, Seamless User-Level Handoff in Ubiquitous Multimedia Service Delivery , Multimedia Tools and Applications, v. 22 n. 2, pp.137-170 (2004).

DOI: 10.1023/b:mtap.0000011932.28891.a0

Google Scholar

[2] P. Bellavista, A. Corradi, L. FoschiniW Context-aware handoff middleware for transparent service continuity in wireless networks, Pervasive and Mobile Computing, 3(4), (2007).

DOI: 10.1016/j.pmcj.2007.04.006

Google Scholar

[3] A. C. Snoeren, H. Balakrishnan, An end-to-end approach to host mobility, Proceedings of the 6th International Conf. on Mobile Computing and Networking, pp.155-166, August (2000).

DOI: 10.1145/345910.345938

Google Scholar

[4] Y. Ma, C. Lai, C. Hu, M. Chen, and Y. Huang, RFID based seamless multimedia services for smart homes, Int. J. Internet Protocol Technol., vol. 4, no. 4, p.232–239 (2009).

DOI: 10.1504/ijipt.2009.029272

Google Scholar

[5] N. Samaan, A. Karmouch, A mobility prediction architecture based on contextual knowledge and spatial conceptual maps, IEEE Trans. Mobile Computing, 4 (6) p.537–551 (2005).

DOI: 10.1109/tmc.2005.74

Google Scholar

[6] S. Michaelis, C. Wietfeld, Evaluation and comparison of prediction stability for user movement pattern detection algorithms, European Wireless, Athens (2006).

Google Scholar

[7] N. Banerjee, A. Acharya, and S. Das, Seamless SIPBased Mobility for Multimedia Applications, IEEE Network, (2006).

Google Scholar

[8] K. Sakamoto, S. Aoyama, S. Asahara, K. Yamashita, A. Okada, Relationship between Viewing Distance and Visual Fatigue in Relation to Feeling of Involvement, Proceedings of the 8th Asia-Pacific conference on Computer-Human Interaction (2008).

DOI: 10.1007/978-3-540-70585-7_26

Google Scholar

[9] DS. Lee, Preferred viewing distance of liquid crystal high-definition television, Applied Ergonomics 43, 151-156 (2012).

DOI: 10.1016/j.apergo.2011.04.007

Google Scholar

[10] Xiph. org video sequence test media, [Online]. Available: http: /media. xiph. org/video/derf.

Google Scholar

[11] ITU-R, Methodology for the subjective assessment of the quality of television pictures, Tech. Rep. BT. 500-11, ITU-R, (2002).

Google Scholar

[12] N. Priyantha, A. Chakraborty, and H. Balakrishnan, The Cricket location-support system, ACM MOBICOM, pp.32-43, (2000).

Google Scholar

[13] R. Feghali, D. Wang, F. Speranza and A. Vincent, Quality metric for video sequences with temporal scalability, Proceedings of the International Conf. on Image Processing, pp.137-140 (2005).

DOI: 10.1109/icip.2005.1530347

Google Scholar