Game Theory for Wireless Sensor Networks: A Survey <s> Dynamic Communication Assignment <s> The proliferation of wireless networks on unlicensed communication bands leads to coexisting networks, creating interference problems. In this paper, interference problems for spectrum-agile networks are addressed by allowing the networks to dynamically change channel. For insight into dynamic channel-change strategies, we model the networks as autonomous players in a multistage non-cooperative game-theoretic model. Here the networks are assumed to be highly interfering, i.e., when two or more networks exist on a single channel they cannot successfully carry traffic. Each network seeks to minimize its time to find a clear channel. The game-theoretic analysis reflects the motivations and choices of independent, rational, selfish decision makers that do not trust one another. We analyze the game-theoretic solutions appropriate for an untrusted environment, and compare the results with socially optimal decisions that would maximize the expected benefit of all coexisting networks in a trusted environment. <s> BIB001 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Dynamic Communication Assignment <s> In this paper we consider the problem of distributed convergence to a Nash equilibrium based on minimal information about the underlying noncooperative game. We assume that the players/agents generate their actions based only on measurements of local cost functions, which are corrupted with additive noise. Structural parameters of their own and other players' costs, as well as the actions of the other players are unknown. Furthermore, we assume that the agents may have dynamics: their actions can not be changed instantaneously. We propose a method based on a stochastic extremum seeking algorithm with sinusoidal perturbations and we prove its convergence, with probability one, to a Nash equilibrium. We discuss how the proposed algorithm can be adopted for solving coordination problems in mobile sensor networks, taking into account specific motion dynamics of the sensors. The local cost functions can be designed such that some specific overall goal is achieved. We give an example in which each agent/sensor needs to fulfill a locally defined goal, while maintaining connectivity with neighboring agents. The proposed algorithms are illustrated through simulations. <s> BIB002 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Dynamic Communication Assignment <s> Scheduling tasks in wireless sensor networks is one of the most challenging problems. Sensing tasks should be allocated and processed among sensors in minimum times, so that users can draw prompt and effective conclusions through analyzing sensed data. Furthermore, finishing sensing task faster will benefit energy saving, which is critical in system design of wireless sensor networks. But sensors may refuse to take pains to carry out the tasks due to the limited energy. To solve the potentially selfish problem of the sensors, a non-cooperative game algorithm (NGTSA) for task scheduling in wireless sensor networks is proposed. In the proposed algorithm, according to the divisible load theory, the tasks are distributed reasonably to every node from SINK based on the processing capability and communication capability. By removing the performance degradation caused by communications interference and idle, the reduced task completion time and the improved network resource utilization are achieved. Strategyproof mechanism which provide incentives to the sensors to obey the prescribed algorithms, and to truthfully report their parameters, leading to an effient task scheduling and execution. A utility function related with the total task completion time and tasks allocating scheme is designed. The Nash equilibrium of the game algorithm is proved. The simulation results show that with the mechanism in the algorithm, selfish nodes can be forced to report their true processing capability and endeavor to participate in the measurement, thereby the total time for accomplishing the task is minimized and the energy-consuming of the nodes is balanced. <s> BIB003
Stankovicacute et al. BIB002 considered the problem of distributed convergence to a NE based on minimal information about the underlying non-cooperative game. Interference problems for spectrum-agile networks were addressed by allowing the networks to dynamically change channel in literature BIB001 . For insight into dynamic channel-change strategies, authors modeled the networks as autonomous players in a multistage non-cooperative game-theoretic model. Here the networks are assumed to be highly interfering, i.e., when two or more networks exist on a single channel they cannot successfully carry traffic. Each network seeks to minimize its time to find a clear channel. The game-theoretic analysis reflects the motivations and choices of independent, rational, selfish decision makers that do not trust one another. They analyzed appropriate game-theoretic solutions in an un-trusted environment, and compare results with socially optimal decisions that would maximize the expected benefit of all coexisting networks in a trusted environment. Sensor energy is limited, and the sensor is selfish but rational in WSN. If a node cannot get some profits, it will not perform the task. Of course, there will be some nodes that may exaggerate their real capacities to get some more tasks for profits. These dishonest or selfish behaviors will seriously affect the efficiency of WSN. Therefore, incentives should be provided to force nodes to obey the prescribed algorithms and report truthfully their capacity. Mechanism design in GT can resolve this problem BIB003 .