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Markov Game Theory Based Routing Countering Eavesdropping
针对窃听问题的马尔可夫博弈路由模型的研究

Keywords: WSN,MGBR,Probability
无线传感器网络,马尔可夫博弈路由模型,概率

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Abstract:

To reduce the probability of eavesdropping in wireless sensor networks, this paper proposed a Markov game theory based routing(MGBR) to counter tapping problems under stochastic routing. The sender and the eavesdropper are considered as the two players of the game. Data is transmitted by senders with probability, determining the data transmission to effective tap is hence difficult for the eavesdroppers. With the tool of PRISM, simulation results demonstrate that there is a Nash Ectuilibrium point in MGBR, where the probability to be eavesdropped can be minimized. Furthermore,we presented the probability variation tendency of information to be eavesdropped on the Nash Equilibrium point. Compared with protocol based on minimal-hop algorithm, MGI3R can reduce the probability of information to be eavesdropped effectively.

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