Evaluation of channel dependent bandwidth allocation in wireless access networks: centralized and distributed approach

The problem of bandwidth allocation in wireless access networks is studied in this paper, investigating the performance of two approaches. Firstly, we use centralized algorithms, such as bankruptcy division rules and Nash bargaining. Secondly, a distributed algorithm is proposed in order to find the optimal solution of the bandwidth allocation problem. In both approaches, the allocation rules are properly modified to incorporate the influence of the channel state resulting in a more efficient and fair bandwidth allocation. The channel dependent centralized and distributed schemes are compared in terms of efficiency and fairness with a view to highlighting the advantages and disadvantages of every approach.

[1]  R. Aumann,et al.  Game theoretic analysis of a bankruptcy problem from the Talmud , 1985 .

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

[3]  Aurel A. Lazar,et al.  Design and Analysis of the Progressive Second Price Auction for Network Bandwidth Sharing , 1999 .

[4]  W. Thomson,et al.  Constrained Egalitarianism: A New Solution for Claims Problems , 1998 .

[5]  Philip Constantinou,et al.  Bandwidth allocation in wireless access networks: Bankruptcy game vs cooperative game , 2009, 2009 International Conference on Ultra Modern Telecommunications & Workshops.

[6]  J. Nash THE BARGAINING PROBLEM , 1950, Classics in Game Theory.

[7]  Byeong Gi Lee,et al.  Wireless Communications Resource Management , 2008 .

[8]  Scott Shenker,et al.  Fundamental Design Issues for the Future Internet (Invited Paper) , 1995, IEEE J. Sel. Areas Commun..

[9]  Fernando Perez Fontan,et al.  Modelling the Wireless Propagation Channel: A simulation approach with MATLAB , 2008 .

[10]  Cem U. Saraydar,et al.  Efficient power control via pricing in wireless data networks , 2002, IEEE Trans. Commun..

[11]  Raj Jain,et al.  A Quantitative Measure Of Fairness And Discrimination For Resource Allocation In Shared Computer Systems , 1998, ArXiv.

[12]  Zhu Han,et al.  Dynamics of Multiple-Seller and Multiple-Buyer Spectrum Trading in Cognitive Radio Networks: A Game-Theoretic Modeling Approach , 2009, IEEE Transactions on Mobile Computing.

[13]  Patrick Maillé,et al.  Multibid auctions for bandwidth allocation in communication networks , 2004, IEEE INFOCOM 2004.

[14]  Dusit Niyato,et al.  A Queuing-Theoretic and Optimization-Based Model for Radio Resource Management in IEEE 802.16 Broadband Wireless Networks , 2006, IEEE Transactions on Computers.

[15]  Bruce E. Hajek,et al.  VCG-Kelly Mechanisms for Allocation of Divisible Goods: Adapting VCG Mechanisms to One-Dimensional Signals , 2006, 2006 40th Annual Conference on Information Sciences and Systems.

[16]  Dusit Niyato,et al.  Queue-aware uplink bandwidth allocation and rate control for polling service in IEEE 802.16 broadband wireless networks , 2006, IEEE Transactions on Mobile Computing.

[17]  William Thomson,et al.  Axiomatic and game-theoretic analysis of bankruptcy and taxation problems: An update , 2015, Math. Soc. Sci..

[18]  John N. Tsitsiklis,et al.  Efficiency loss in a network resource allocation game: the case of elastic supply , 2004, IEEE Transactions on Automatic Control.

[19]  Ellen W. Zegura,et al.  Utility max-min: an application-oriented bandwidth allocation scheme , 1999, IEEE INFOCOM '99. Conference on Computer Communications. Proceedings. Eighteenth Annual Joint Conference of the IEEE Computer and Communications Societies. The Future is Now (Cat. No.99CH36320).

[20]  Dusit Niyato,et al.  QoS-aware bandwidth allocation and admission control in IEEE 802.16 broadband wireless access networks: A non-cooperative game theoretic approach , 2007, Comput. Networks.

[21]  N. Dagan,et al.  A Noncooperative View of Consistent Bankruptcy Rules , 1994 .

[22]  Dusit Niyato,et al.  A Cooperative Game Framework for Bandwidth Allocation in 4G Heterogeneous Wireless Networks , 2006, 2006 IEEE International Conference on Communications.