An Incentive Mechanism Using Game Theory for Wireless Mesh Networks

2013 ◽  
Vol 284-287 ◽  
pp. 2694-2698
Author(s):  
Wei Kuang Lai ◽  
Mu Lung Weng ◽  
Yuh Chung Lin ◽  
Chin Shiuh Shieh

Wireless mesh networks (WMNs) have attracted much attention in recent years. The main problems in WMNs are the unfairness in bandwidth sharing and potential selfish behavior. In this paper, an incentive-based pricing model is designed which follows the concepts of mechanism design in game theory to encourage nodes to relay packets for other nodes and therefore achieve fairness. In the pricing model, we consider the packet transmitting amounts, idle conditions and the special need of border nodes in the margin area. The incentive is the main feature of the model. We also discuss the model using mathematical analysis from various perspectives. The analysis shows that this model is highly effective in eliminating unfairness in the multi-hop transmission topology. This is achieved by allowing border mesh routers to receive a fair profit. This flexible pricing model is capable of encouraging packet forwarding. With the issue of unfairness resolved, WMNs can be expected to have a broader range of applications.

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
S. Q. Huang ◽  
G. C. Wang ◽  
H. H. Zhen ◽  
Z. Zhang

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.


IEEE Network ◽  
2008 ◽  
Vol 22 (1) ◽  
pp. 39-44 ◽  
Author(s):  
Liqiang Zhao ◽  
Jie Zhang ◽  
Hailin Zhang

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