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The Scientific World Journal
Volume 2013 (2013), Article ID 936536, 9 pages
http://dx.doi.org/10.1155/2013/936536
Research Article

An MPS-BNS Mixed Strategy Based on Game Theory for Wireless Mesh Networks

1Network and Education Technology Center, Jinan University, Guangzhou, Guangdong 510632, China
2School of Computer and Electrical Information, Guangxi University, Nanning, Guangxi 530004, China
3College of Information Science and Technology, Jinan University, Guangzhou, Guangdong 510632, China

Received 31 October 2012; Accepted 17 December 2012

Academic Editors: G. Bordogna and P. Melin

Copyright © 2013 S. Q. Huang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

To achieve a valid effect of wireless mesh networks against selfish nodes and selfish behaviors in the packets forwarding, an approach named mixed MPS-BNS strategy is proposed in this paper. The proposed strategy is based on the Maximum Payoff Strategy (MPS) and the Best Neighbor Strategy (BNS). In this strategy, every node plays a packet forwarding game with its neighbors and records the total payoff of the game. After one round of play, each player chooses the MPS or BNS strategy for certain probabilities and updates the strategy accordingly. In MPS strategy, each node chooses a strategy that will get the maximum payoff according to its neighbor’s strategy. In BNS strategy, each node follows the strategy of its neighbor with the maximum total payoff and then enters the next round of play. The simulation analysis has shown that MPS-BNS strategy is able to evolve to the maximum expected level of average payoff with faster speed than the pure BNS strategy, especially in the packets forwarding beginning with a low cooperation level. It is concluded that MPS-BNS strategy is effective in fighting against selfishness in different levels and can achieve a preferable performance.