Abstract
Video service has been a killer application over wireless networks. Many cross-layer optimization techniques have been proposed to improve the quality of video services in wireless networks. However, most of them did not consider video content type information in resource allocation, which greatly affects the quality of users’ watching experience. In this paper, we take video type information into consideration for resource allocation at base stations. Accordingly, for given transmission power at base station, we build an optimal model to achieve maximal achievable total Mean Opinion Score (MOS) by allocating appropriate powers and video rates for different users watching different types of videos. Numerical results show that our model can achieve much higher MOS compared with existing scheme that does not consider such video type information.
Keywords
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Cisco Visual Networking Index. Global Mobile Data Traffic Forecast Update 2015–2020, White Paper. http://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/mobile-white-paper-c11-520862.html. Accessed 1 Feb 2016
Gross, J., Klau, J., Karl, H., Wolisz, A.: Cross-layer optimization of OFDM transmission systems for MPEG-4 video streaming. Comput. Commun. 27, 1044–1055 (2004)
Li, P., Chang, Y., Feng, N., Yang, F.: A cross-layer algorithm of packet scheduling and resource allocation for multi-user wireless video transmission. IEEE Trans. Consum. Electron. 57(3), 1128–1134 (2011)
Chuah, S.P., Chen, Z., Tan, Y.P.: Energy-efficient resource allocation and scheduling for multicast of scalable video over wireless networks. IEEE Trans. Multimedia 14(4), 1324–1336 (2012)
Danish, E., Silva, V., Fernando, A., Alwis, C., Kondoz, A.: Content-aware resource allocation in OFDM systems for energy-efficient video transmission. In: Proceedings of IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NV, pp. 456–457 (2014)
Khan, A., Sun, L., Ifeachor, E.: Content-based video quality prediction for MPEG4 video streaming over wireless networks. J. Multimedia 4(4), 1–5 (2009)
Khan, S., Peng, Y., Steinbach, E.: Application-driven cross-layer optimization for video streaming over wireless networks. IEEE Commun. Mag. 44(1), 122–130 (2006)
Lee, S., Koo, J., Chung, K.: Content-aware rate control scheme to improve the energy efficiency for mobile IPTV. In: Proceedings of IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NV, pp. 445–446 (2010)
Danish, E., Fernando, A., Abdul-Hameed, O., Alshamrani, M., Kondoz, A.: Perceptual QoE based resource allocation for mobile 3D video communications. In: Proceedings of IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NV, pp. 454–455 (2014)
Wang, L., Zhao, Y., Li, C., Guo, Y.: Enabling content aware QoE network bandwidth allocation. In: Proceedings of International Conference on Wireless Communications and Signal Processing (WCSP), Nanjing, China, pp. 1–5 (2017)
Wireless Communication Systems. Lecture Notes. http://www.ece.utah.edu/~npatwari/pubs/lectureAll_ece5325_6325_f11.pdf. Accessed 18 Apr 2018
Winstein, K., Sivaraman, A., Balakrishnan, H.: Stochastic forecasts achieve high throughput and low delay over cellular networks. In: Proceedings of 10th USENIX NSDI 2013, Lombard, IL, pp. 459–471 (2013)
Acknowledgement
This work was supported in part by National Natural Science Foundation of China under Grants 61572071, u1534201, 61531006, and 61471339.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Zhao, Y., Song, Y., Li, C. (2019). Content Aware Resource Allocation for Video Service Provisioning in Wireless Networks. In: Zheng, J., Xiang, W., Lorenz, P., Mao, S., Yan, F. (eds) Ad Hoc Networks. ADHOCNETS 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 258. Springer, Cham. https://doi.org/10.1007/978-3-030-05888-3_5
Download citation
DOI: https://doi.org/10.1007/978-3-030-05888-3_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-05887-6
Online ISBN: 978-3-030-05888-3
eBook Packages: Computer ScienceComputer Science (R0)