Abstract
Due to the fast growth of wireless multimedia applications, mobile media cloud network is getting more and more popular. In the architecture of mobile media cloud network, the wireless access points are placed on edge of the cloud to provide media services for the mobile users. The video bandwidth allocation managed by a centralized media cloud directly affect the user’s experiences. In this paper, the problem of the video bandwidth allocation in the mobile media cloud access network is explored. Firstly, this paper formulates the problems in bandwidth allocation in the form of quadratic programming in order to maximize the system revenue on the basis of video bitrates capacity between the user and the Mobile Access Edge Point (MAEP). The optimization model could more vividly explicate the trade-off between the expected bitrates capacity and the allocation fairness of User Equipment (UE). Then this paper subdivides the problem into major and minor ones and proposes an algorithm based on Benders’ Decomposition to deal with it. The optimality of the solution is proved by both theoretical and experimental investigations. The error tolerance is analyzed as the algorithm disavows the trade-off between the convergence time and the system performance. The experiments show that the average computing time and confidence interval of the proposed algorithm are lower than Simplex algorithm by 68% and 94% and Barrier algorithm by 46% and 75% respectively at most. Finally, some conclusions are derived from evaluations on the system performance against various network topologies and different values for parameters of the proposed algorithms.
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References
Aazam M, Huh E-N (2014) Resource management in media cloud of things. In: Proceeding of 2014 43nd international conference on parallel processing workshops, Minneapolis, MN, USA, ICCPW’14, 361–367. doi:10.1109/ICPPW.2014.54
Ahmed I, Ikhlef A, Schober R, Mallik R (2013) Joint power allocation and relay selection in energy harvesting AF relay systems. IEEE Wireless Commun Lett 2:239–242. doi:10.1109/wcl.2013.012513.130007
Benders J (1962) Partitioning procedures for solving mixed-variables programming problems. Numer Math 4(1):238–252. doi:10.1007/s10287-004-0020-y
Boyd S, Vandenberghe L (2004) Con vex optimization. Cambridge University Press, Cambridge. doi:10.1017/cbo9780511804441
Chih-Lin I, Rowell G, Han S et al (2014) Toward green and soft: a 5G perspective. IEEE Commun Mag 52(2):66–73. doi:10.1109/mcom.2014.6736745
Chuah S, Tan Y, Chen Z (2015) Rate and power allocation for joint coding and transmission in wireless video chat applications. IEEE Trans Multimedia 17(5):687–699. doi:10.1109/tmm.2015.2413354
Dey S (2012) Cloud mobile media: opportunities, challenges, and directions. In: Proceedings of international conference on computing, networking and communications, Maui, Hawaii, USA, ICNC’12, pp 929–933. doi:10.1109/iccnc.2012.6167561
Dong Y, Zhou L, Chen J, Zheng B et al. (2015) Energy efficient virtual machine consolidation in mobile media cloud. In: Proceeding of 31st picture coding symposium, Cairns, Australia, PCS’15, pp 248–252. doi:10.1109/pcs.2015.7170084
Kosta S, Aucinas A, Hui P, Mortier R, Zhang X (2012) ThinkAir: dynamic resource allocation and parallel execution in the cloud for mobile code offloading. In: Proceeding of. IEEE international conference on computer communications, Houston, TX, USA, 2012, INFOCOM’12, pp 945–953. doi:10.1109/infcom.2012.6195845
McDaniel D (1977) A modified benders’ partitioning algorithm for mixed integer programming. Manag Sci 24(3):312–319. doi:10.1287/mnsc.24.3.312
Miao D, Zhu W, Luo C, Chen C (2011) Resource allocation for cloud-based free viewpoint video rendering for mobile phones. In: Proceeding of the 19th ACM international conference multimedia, New York, NY, USA, MM ’11, pp 1237–1240. doi:10.1145/2072298.2071983
Nan X, He Y, Guan L (2011) Optimal resource allocation for multi-media cloud based on queuing model. In: Proceeding of IEEE international workshop on multimedia signal processing, Hangzhou, China, MMSP’11, pp 1–6. doi:10.1109/mmsp.2011.6093813
Pan Z, Zhang Y, Kwong S (2015) Efficient motion and disparity estimation optimization for low complexity multiview video coding. IEEE Trans Broadcast. doi:10.1109/tbc.2015.2419824
Qian L, Zhang Y, Wu Y, Chen J (2013) Joint base station association and power control via Benders’ Decomposition. IEEE Trans Wirel Commun 12:1651–1665. doi:10.1109/glocom.2009.5425218
Sardis F, Mapp G, Loo J, Aiash M et al (2013) On the investigation of cloud-based mobile media environments with service-populating and QoS-aware mechanisms. IEEE Trans Multimedia 15(4):769–777. doi:10.1109/tmm.2013.2240286
Wang C, Haider F, Gao X et al (2014) Cellular architecture and key technologies for 5G wireless communication networks. IEEE Commun Mag 52(2):122–130. doi:10.1109/mcom.2014.6736752
Wen Y, Zhu X, Rodrigues J, Chen C (2014) Cloud mobile media reflections and outlook. IEEE Trans Multimedia 16(4):885–902. doi:10.1109/tmm.2014.2315596
Xu Y, Mao S (2013) A survey of mobile cloud computing for rich media applications. IEEE Wirel Commun 20(3):46–53. doi:10.1109/mwc.2013.6549282
Zhang X, Kunjithapatham A, Jeong S, Gibbs S (2011) Towards an elastic application model for augmenting the computing capabilities of mobile devices with cloud computing. Mob Netw Appl 16(2):270–284. doi:10.1007/s11036-011-0305-7
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This paper is supported by the 863 Program (2015AA01A705) and NSFC (61271187).
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Feng, L., Zhou, F., Yu, P. et al. Benders Decomposition-based video bandwidth allocation in mobile media cloud network. Multimed Tools Appl 77, 877–895 (2018). https://doi.org/10.1007/s11042-016-4299-9
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DOI: https://doi.org/10.1007/s11042-016-4299-9