Rate allocation games in multiuser multimedia communications

In this study, the authors study a game-theoretic framework for the problem of multiuser rate allocation in multimedia communications. The authors consider the multimedia users to be autonomous, that is, they are selfish and behave strategically. The authors propose a rate allocation framework based on a pricing mechanism to prevent the selfish users from manipulating the network bandwidth by untruthfully representing their demands. The pricing mechanism is used for message exchange between the users and the network controller. The messages represent network-aware rate demands and corresponding prices. The authors show that a Nash equilibrium can be obtained, according to which the controller generates allocations that are efficient, budget balanced and satisfy voluntary participation. Simulation results demonstrate the validity of the proposed framework.

[1]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[2]  Frank Kelly,et al.  Rate control for communication networks: shadow prices, proportional fairness and stability , 1998, J. Oper. Res. Soc..

[3]  Oscar C. Au,et al.  Simultaneous RD-optimized rate control and video de-noising , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

[4]  Wei Ding,et al.  Rate control of MPEG video coding and recording by rate-quantization modeling , 1996, IEEE Trans. Circuits Syst. Video Technol..

[5]  Zhu Han,et al.  Fair multiuser channel allocation for OFDMA networks using Nash bargaining solutions and coalitions , 2005, IEEE Transactions on Communications.

[6]  Bernd Girod,et al.  Analysis of video transmission over lossy channels , 2000, IEEE Journal on Selected Areas in Communications.

[7]  Hsueh-Ming Hang,et al.  Source model for transform video coder and its application. I. Fundamental theory , 1997, IEEE Trans. Circuits Syst. Video Technol..

[8]  K. Ramchandran,et al.  From Rate-distortion Theory To Commercial Image and Video Compression Technology , 1998, IEEE Signal Processing Magazine.

[9]  Antonio Ortega,et al.  Rate-distortion methods for image and video compression , 1998, IEEE Signal Process. Mag..

[10]  Mihaela van der Schaar,et al.  Bargaining Strategies for Networked Multimedia Resource Management , 2007, IEEE Transactions on Signal Processing.

[11]  Stephan Olariu,et al.  A Fair Resource Allocation Protocol for Multimedia Wireless Networks , 2003, IEEE Trans. Parallel Distributed Syst..

[12]  Zhengguo Li,et al.  A Novel Rate Control Scheme for Low Delay Video Communication of H.264/AVC Standard , 2007, IEEE Transactions on Circuits and Systems for Video Technology.

[13]  Wen Gao,et al.  Adaptive rate control for H.264 , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

[14]  Susanto Rahardja,et al.  Adaptive rate control for H.264 , 2004, ICIP.

[15]  R. W. Lucky,et al.  Tragedy of the commons [Reflections] , 2006 .

[16]  K. J. Ray Liu,et al.  Multiuser rate allocation games for multimedia communications , 2009, IEEE Transactions on Multimedia.

[17]  Mihaela van der Schaar,et al.  A Pricing Mechanism for Resource Allocation in Wireless Multimedia Applications , 2007, IEEE Journal of Selected Topics in Signal Processing.

[18]  Mihaela van der Schaar,et al.  Optimized scalable video streaming over IEEE 802.11 a/e HCCA wireless networks under delay constraints , 2006, IEEE Transactions on Mobile Computing.

[19]  G. Hardin,et al.  The Tragedy of the Commons , 1968, Green Planet Blues.

[20]  Tihao Chiang,et al.  A new rate control scheme using quadratic rate distortion model , 1997, IEEE Trans. Circuits Syst. Video Technol..

[21]  Frank Kelly,et al.  Charging and rate control for elastic traffic , 1997, Eur. Trans. Telecommun..

[22]  Jordi Ribas-Corbera,et al.  Rate control in DCT video coding for low-delay communications , 1999, IEEE Trans. Circuits Syst. Video Technol..