Game Theory for Wireless Sensor Networks: A Survey <s> Applications in WSN <s> Conventional centralised information fusion and control architectures will be challenged by developments in sensor networks that allow sophisticated autonomous sensors, owned by different stakeholders with individual goals, to interact and share information. Given this, we advocate the use of tools and techniques from computational mechanism design (CMD), a field at the intersection of computer science, game theory and economics, to address the challenges posed by these networks. In particular, CMD allows us to engineer networks with desirable system-wide properties, in which sensors act as rational selfish agents, each attempting to fulfill their own individuals goals through the exchange of observations and information. In this paper, we present our work developing such networks. Specifically, we discuss our development of a generic and principled information valuation metric for sensor networks and we report our experiences applying it within a real world information fusion sensor network scenario. <s> BIB001 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Applications in WSN <s> "Cognitive radio" is an emerging technique to improve the utilization of radio frequency spectrum in wireless networks. In this paper, we consider the problem of spectrum sharing among a primary user and multiple secondary users. We formulate this problem as an oligopoly market competition and use a noncooperative game to obtain the spectrum allocation for secondary users. Nash equilibrium is considered as the solution of this game. We first present the formulation of a static game for the case where all secondary users have the current information of the adopted strategies and the payoff of each other. However, this assumption may not be realistic in some cognitive radio systems. Therefore, we consider the case of bounded rationality in which the secondary users gradually and iteratively adjust their strategies based on the observations on their previous strategies. The speed of adjustment of the strategies is controlled by the learning rate. The stability condition of the dynamic behavior for this spectrum sharing scheme is investigated. The numerical results reveal the dynamics of distributed dynamic adaptation of spectrum sharing strategies. <s> BIB002 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Applications in WSN <s> In infrastructure-less sensor networks, efficient usage of energy is very critical because of the limited energy available to the sensor nodes. Among various phenomena that consume energy, radio communication is by far the most demanding one. One of the effective ways to limit unnecessary energy loss is to control the power at which the nodes transmit signals. In this paper, we apply game theory to solve the power control problem in a CDMA-based distributed sensor network. We formulate a noncooperative game under incomplete information and study the existence of Nash equilibrium. With the help of this equilibrium, we devise a distributed algorithm for optimal power control and prove that the system is power stable only if the nodes comply with certain transmit power thresholds. We show that even in a noncooperative scenario, it is in the best interest of the nodes to comply with these thresholds. The power level at which a node should transmit, to maximize its utility, is evaluated. Moreover, we compare the utilities when the nodes are allowed to transmit with discrete and continuous power levels; the performance with discrete levels is upper bounded by the continuous case. We define a distortion metric that gives a quantitative measure of the goodness of having finite power levels and also find those levels that minimize the distortion. Numerical results demonstrate that the proposed algorithm achieves the best possible payoff/utility for the sensor nodes even by consuming less power. <s> BIB003 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Applications in WSN <s> We propose the energy efficient MAC algorithm in this paper. In the proposed algorithm, each node sets the contention window size with respect to the residual energy, the harvesting energy and the transmit power. This algorithm makes the sensor nodes consume their energy efficiently. To achieve this goal, we use the game theory and the cross-layer optimization. Introducing the non-cooperative game, we can formulate the utility function easily. In this paper, we can allocate the optimal power by the cross-layer optimization on the PHY and the MAC. <s> BIB004
Conventional centralized information fusion and control architectures will be challenged by developments in sensor networks that allow sophisticated autonomous sensors, owned by different stakeholders with individual goals, to interact and share information. Rogers et al. BIB001 advocate the use of tools and techniques from computational mechanism design (CMD), a field at the intersection of computer science and non-cooperative game theory, to address the challenges posed by these networks. Shamik et al. BIB003 formulated a non-cooperative game under incomplete information for the distributed sensor nodes. The benefit and the cost were defined the existence of NE was investigated. A metric called distortion factor was formulated to assess the performance of such system and compare it with systems that would allow any continuous power levels. "Cognitive radio" is an emerging technique to improve the utilization of radio frequency spectrum in wireless networks. In BIB002 , Niyato and Hossain considered the problem of spectrum sharing among a primary user and multiple secondary users. They formulated this problem as an oligopoly market competition and used a non-cooperative game to obtain the spectrum allocation for secondary users. Haksub et al. BIB004 proposed a non-cooperative game based energy efficient MAC algorithm which makes the sensor nodes consume their energy efficiently.