© The Institution of Engineering and Technology
User's perceived quality of service (QoS) or quality of experience (QoE) is likely to be the major determining factor in the success of new multimedia applications over wireless/mobile networks. The primary aim of this study is to present an adaptation scheme that is QoE-driven for optimising content provisioning and network resource utilisation for video applications over wireless networks. The proposed scheme encompasses the application of a QoE-driven model for optimising content provisioning and network resource utilisation. The content provisioning is optimised by the determination of initial content quality by adapting the video sender bitrate (SBR) according to users' QoE requirement. By finding the impact of the QoS parameters on end-to-end perceptual video quality, the optimum trade-off between SBR and frame rate is found and the benefits to network providers in maximising existing network resources are demonstrated. The QoE is measured in terms of the mean opinion score. The proposed scheme makes it possible for content providers to achieve optimum streaming (with an appropriate SBR) suitable for the network and content type for a requested QoE. The scheme is also beneficial for network providers for network resource provision and planning, and therefore maximising existing network infrastructure by providing service differentiation.
References
-
-
1)
-
Papadimitriou, P., Tsaoussidis, V.: `A rate control scheme for adaptive video streaming over the internet', IEEE ICC, 2007.
-
2)
-
G. Zhai ,
J. Cai ,
W. Lin ,
X. Yang ,
W. Zhang
.
Three-dimensional scalable video adaptation via user-end perceptual quality assessment.
IEEE Trans. Broadcast. (Special Issue on Qual. Issues Multimed. Broadcast.)
,
3 ,
719 -
727
-
3)
-
ITU-T. Rec P.800: ‘Methods for subjective determination of transmission quality’, 1996.
-
4)
-
Q. Huynh-Thu ,
M. Ghanbari
.
Temporal aspect of perceived quality in mobile video broadcasting.
IEEE Trans. Broadcast.
,
3 ,
641 -
651
-
5)
-
A. Alexiou ,
D. Antonellis ,
C. Bouras
.
Adaptive and reliable video transmission over UMTS for enhanced performance.
Int. J. Commun. Syst.
,
65 -
81
-
6)
-
D. Kim ,
K. Jun
.
Dynamic bandwidth allocation scheme for video streaming in wireless cellular networks.
IEICE Trans. Commun.
,
2 ,
350 -
356
-
7)
-
Khan, A., Sun, L., Ifeachor, E.: `Content classification based and QoE-driven video send bitrate adaptation scheme', Fifth Int. Mobimedia Conf., 7–9 September 2009, London, UK.
-
8)
-
NS2, http://www.isi.edu/nsnam/ns/.
-
9)
-
Telchemy application notes: ‘Understanding of video quality metrics’. Telchemy, February 2008. http://www.telchemy.co.uk.
-
10)
-
Agboma, F., Liotta, A.: `QoE-aware QoS management', Sixth Int. Conf. on Advances in Mobile computing and Multimedia, 24–26 November 2008.
-
11)
-
Alexiou, A., Bouras, C., Igglesis, V.: `A decision feedback scheme for multimedia transmission over 3G mobile networks', WOCN, 2005, Dubai, UAE.
-
12)
-
W.J. Krzanowski
.
(1988)
Principles of multivariate analysis.
-
13)
-
Onur, O., Alatan, A.: `Video adaptation based on content characteristics and hardware capabilities', Second Int. Workshop on Semantic Media Adaptation and Personalization, 2007.
-
14)
-
Cranley, N., Murphy, L., Perry, P.: `Content-based adaptation of streamed multimedia', IEEE Int. Conf. on Management of Multimedia Networks and Services, No. 7, 3–6 October 2004, San Diego, CA.
-
15)
-
Y. Wang ,
M. Schaar ,
A. Loui
.
Classification-based multidimensional adaptation prediction for scalable video coding using subjective quality evaluation.
IEEE Trans. Circuits Syst. Video Technol.
,
10 ,
1270 -
1279
-
16)
-
H. Garudadri ,
H. Chung ,
N. Srinivasamurthy ,
P. Sagetong
.
Rate adaptation for video telephony in 3G networks.
Packet Video
,
342 -
348
-
17)
-
Klaue, J., Tathke, B., Wolisz, A.: `Evalvid – a framework for video transmission and quality evaluation', Proc. 13th Int. Conf. on Modelling Techniques and Tools for Computer Performance Evaluation, 2003, Urbana, IL, USA, p. 255–272.
-
18)
-
P. Calyam ,
E. Ekicio ,
C. Lee ,
M. Haffner ,
N. Howes
.
A GAP-model based framework for online VVoIP QoE measurement.
J. Commun. Netw.
,
4 ,
446 -
56
-
19)
-
Manzato, M., Goularter, R.: `Live video adaptation: a context-aware approach', ACM Proc. 11th Brazilian Symp. on Multimedia and the Web, 2005.
-
20)
-
Ffmpeg, http://sourceforge.net/projects/ffmpeg.
-
21)
-
H. Koumaras ,
A. Kourtis ,
C. Lin ,
C. Shieh
.
End-to-end prediction model of video quality and decodable frame rate for MPEG broadcasting services.
Int. J. Adv. Netw. Services
,
1 ,
19 -
29
-
22)
-
F. Angelis ,
I. Habib ,
F. Davide ,
M. Naghshineh
.
Intelligent content aware services in 3G wireless networks.
IEEE J. Sel. Areas Commun.
,
2 ,
221 -
234
-
23)
-
Khan, A., Sun, L., Ifeachor, E.: `Impact of video content on video quality for video over wireless networks', Fifth ICAS, 20–25 April 2009, Valencia, Spain.
-
24)
-
Khan, A., Sun, L., Ifeachor, E.: `Content clustering based video quality prediction model for MPEG4 video streaming over wireless networks', IEEE ICC Conf., 14–18 June 2009, Dresden, Germany.
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