Game Theory for Wireless Sensor Networks: A Survey <s> QoS Control <s> As a new means for Data Acquisition and Fusion, Mobile Ad hoc Sensor Networks has been the focus of many researchers during the previous years. To enhance both the Quality of Service (Q0S) and the networks robustness, the concept of mobility were introduced which gives the designer the capability of using various topologies to perform a certain task. This paper proposes a novel management idea for positioning of the sensor agents based on the concepts of Stackelberg games. It is explained that the new method lowers the cost of internal communication while eases the network description as well. <s> BIB001 </s> Game Theory for Wireless Sensor Networks: A Survey <s> QoS Control <s> Wireless sensor networks (WSN) are planted for sensing the area which people mostly concern and to send data of light, pressure, sound, and so on, back to people to make further analyses. Differ from normal lineal networks, WSN are usually restricted by energy store, plethoric information flow, and short communication distance. So, there are many research hotpots in WSN such as routing, economization of energy, adaptive self-configuration, etc. Among these aspects, the area of quality of service (QoS) remains largely open. This is due to that the optimal alive sensor node number is difficult to determine in a certain focused area which satisfies the requirement of QoS. In the paper, under a circumstance of ITS (Intelligent Transportation Systems) application, a modified Gur Game strategy based on localized information is given to determine the optimal alive node number in a focused area. In the strategy, all nodes use local information to modify their finite state automaton, and the base station receives the QoS feedback and gives the dynamic density domination information. The simulation results about the band shape density domination are given. The results show that the strategy can effectively control the density of nodes and meet the requirement of QoS even with impediment added. <s> BIB002 </s> Game Theory for Wireless Sensor Networks: A Survey <s> QoS Control <s> Wireless sensor networks(WSN) have restrictions due to energy,memory, and communication ability.This paper relates the QoS(quality of service) with the node density and its control strategies given for rectangular,circular,and various elliptical areas and designs for a dynamic adjusting mechanism based on the Gur Game algorithm.Simulations show that the number and locations of the power-up nodes dynamically change when shape control information changes.A dynamic adjusting mechanism dynamically changes the kernel area and the gradient area when the nodes are too dense or too few.More power-up nodes can then be centralized in the kernel area compared with systems without the dynamic adjusting mechanism.The strategy controls the optimal number of nodes to power up in or close to the focused area so as to meet the QoS requirement. <s> BIB003 </s> Game Theory for Wireless Sensor Networks: A Survey <s> QoS Control <s> A queuing analytical model is presented to investigate the performances of different sleep and wakeup strategies in a solar-powered wireless sensor/mesh network where a solar cell is used to charge the battery in a sensor/mesh node. While the solar radiation process (and, hence, the energy generation process in a solar cell) is modeled by a stochastic process (i.e., a Markov chain), a linear battery model with relaxation effect is used to model the battery capacity recovery process. Developed based on a multidimensional discrete-time Markov chain, the presented model is used to analyze the performances of different sleep and wakeup strategies in a sensor/mesh node. The packet dropping and packet blocking probabilities at a node are the major performance metrics. The numerical results obtained from the analytical model are validated by extensive simulations. In addition, using the queuing model, based on a game-theoretic formulation, we demonstrate how to obtain the optimal parameters for a particular sleep and wakeup strategy. In this case, we formulate a bargaining game by exploiting the trade-off between packet blocking and packet dropping probabilities due to the sleep and wakeup dynamics in a sensor/mesh node. The Nash solution is obtained for the equilibrium point of sleep and wakeup probabilities. The presented queuing model, along with the game-theoretic formulation, would be useful for the design and optimization of energy-efficient protocols for solar-powered wireless sensor/mesh networks under quality-of-service (QoS) constraints <s> BIB004 </s> Game Theory for Wireless Sensor Networks: A Survey <s> QoS Control <s> The QoS routing problem of wireless multimedia sensor networks has great challenging. A notion using routing game and ant colony algorithm to solve this problem is proposed in this paper. A mixed strategy routing game model is proposed too, and proves the routing game has Nash equilibrium. In the routing game, we used the probabilities which are calculated on the basis of the pheromone trails left by previous ants to define payoffs of game players, and we change the ant colony algorithm with routing game. In our ant-like routing algorithm, all ant select next hop with the probabilities of mixed strategy Nash equilibrium of routing game except the first generation ants. Obviously, this algorithm is convergent, and because the node selected by routing game is equilibrium of energy consumes and the overall benefit of network, so the algorithm is energy efficient. In the future work, we will simulate this algorithm and compare with other algorithms. <s> BIB005 </s> Game Theory for Wireless Sensor Networks: A Survey <s> QoS Control <s> The multi-constrained QoS-based routing problem of wireless multimedia sensor networks is an NP hard problem. Genetic algorithms (GAs) have been used to handle these NP hard problems in wireless networks. Because the crossover probability is a key factor of GAs' action and performance, and affects the convergence of GAs, and the selection of crossover probability is very difficult, so we propose a novel method - crossover game instead of probability crossover. The crossover game in routing problems is based of each node has restricted energy, and each node trend to get maximal whole network benefit but pay out minimum cost. The players of crossover game are individual routes. The individual would perform crossover operator if it is Nash equilibrium in crossover game. The Simulation results demonstrate that this method is effective and efficient. <s> BIB006 </s> Game Theory for Wireless Sensor Networks: A Survey <s> QoS Control <s> The distinctive features of wireless multimedia sensor networks (WMSNs) include application-specific quality-of-service (QoS) requirements and limited energy supply, with which each node makes its own decisions selfishly. Therefore this paper presents a power control game theoretic approach for WMSNs by studying the effect of transmission power on QoS and energy efficiency. The game approach determines the transmission strategy using utility optimization according to the fluctuation of channel states. Here, the utility function is defined by effective throughput per unit power while satisfying the user's delay QoS constraints. The existence and uniqueness of Nash equilibrium for the proposed game are proved. Finally, the simulation results show that each user chooses the optimal transmission power to maximize its utility based on other constant parameters and the effects of delay constraints on the user's utility are quantified as well. <s> BIB007 </s> Game Theory for Wireless Sensor Networks: A Survey <s> QoS Control <s> Wireless multimedia sensor networks (WMSNs) models emphasize QoS guarantee. We provide QoS guarantee to measure the qualitative performance of QoS routing model, such as bandwidth, delay and delay jitter. A path that satisfies with the QoS is found by the Directed Diffusion (DD) algorithm in this paper, and an incomplete information game routing model is presented under this condition. We show that the optimal routing architecture is the mixed Bayesian Nash equilibrium of the N-player routing game. Computing the probability to replace the node with low energy, which may maximize benefit of networks and reduce energy consumption, prolongs the network lifetime, and finally the result of the model is presented. <s> BIB008 </s> Game Theory for Wireless Sensor Networks: A Survey <s> QoS Control <s> Body Sensor Networks (BSNs) provide continuous health monitoring and analysis of physiological parameters. A high degree of Quality-of-Service (QoS) for BSN is extremely required. Inter-user interference is introduced by the simultaneous communication of BSNs congregating in the same area. In this paper, a decentralized inter-user interference suppression algorithm for BSN, namely DISG, is proposed. Each BSN measures the interference from other BSNs and then adaptively selects the suitable channel and transmission power. By utilizing non-cooperative game theory and no regret learning algorithm, DISG provides an adaptive inter-user interference suppression strategy. The correctness and effectiveness of DISG is theoretically proved, and the experimental results show that DISG can reduce the effect of inter-user interference effectively. <s> BIB009 </s> Game Theory for Wireless Sensor Networks: A Survey <s> QoS Control <s> Quality of Service (QoS) control is of paramount importance in wireless sensor networks. In this paper we propose a new QoS control algorithm, referred to as Gureen Game, for wireless sensor networks. Gureen Game not only improves the Gur Game for QoS control but also significantly addresses the power consumption weakness of the original Gur Game based QoS control for senor networks. We study the logic behaviors of the proposed Gureen Game, and evaluate its QoS performance compared with the original Gur Game and a recent control algorithm called Shuffle for energy-efficient QoS control. Our simulation results demonstrate the merits of the proposed Gureen Game. <s> BIB010
Quality of Service (QoS) seems an overused term with various meanings and perspectives, but anyway QoS control is of paramount importance in WSN. The network is required to provide the QoS services while maximizing network resource utilization. To achieve this, the network needs to analyze the application requirements and deploy various network QoS mechanisms. Ayers and Yao BIB010 proposed a QoS control algorithm which is referred to as Gureen Game. Gureen Game not only improves the Gur Game for QoS control but also significantly addresses the power consumption weakness of the original Gur Game based QoS control for senor networks. Zhou and Mu BIB003 related the QoS with the node density and its control strategies were given for rectangular, circular, and various elliptical areas and designs for a dynamic adjusting mechanism based on the Gur Game algorithm. Cui et al. BIB007 presented a power control game theoretic approach for wireless multimedia sensor networks (WMSNs) by studying the effect of transmission power on QoS and energy efficiency. Danak et al. BIB001 proposed a novel management idea for positioning of sensor agents based on the concepts of Stackelberg games to enhance both the QoS and the network's robustness. Under a circumstance of intelligent transportation systems, a modified Gur game strategy based on localized information was given to determine the optimal alive node number in a focused area BIB002 . In the strategy, all nodes use local information to modify their finite state automaton, and the base station receives the QoS feedback and gives the dynamic density domination information. To provide a set of measurable service attributes to the end users, Ke et al. BIB008 guarantee to measure the qualitative performance of QoS routing model, such as bandwidth, delay and delay jitter. A path that satisfies with the QoS was found by the Directed Diffusion (DD) algorithm, and an incomplete information game routing model was presented under this condition. A notion using routing game and ant colony algorithm to solve the QoS routing problem of wireless multimedia sensor networks was proposed in BIB005 . A mixed strategy routing game model was also proposed, and proves that the routing game has NE. A queuing analytical model was presented to investigate the performances of different sleep and wakeup strategies in a solar-powered wireless sensor/mesh network where a solar cell is used to charge the battery in a sensor/mesh node in literature BIB004 . The presented queuing model, along with the game-theoretic formulation, would be useful for the design and optimization of energy-efficient protocols for solar-powered wireless sensor/mesh networks under QoS constraints. The multi-constrained QoS-based routing problem of wireless multimedia sensor networks is an NP hard problem. Genetic algorithms (GAs) have been used to handle these NP hard problems in wireless networks. Because the crossover probability is a key factor of GAs' action and performance, and affects the convergence of GAs, and the selection of crossover probability is very difficult, Zongwu et al. BIB006 proposed a novel method -crossover game instead of probability crossover. The crossover game in routing problems is based the principle that each node has restricted energy, and each node trend to get maximal whole network benefit but pay out minimum cost. The players of crossover game are individual routes. The individual would perform crossover operator if it is NE in the crossover game. Body Sensor Networks (BSNs) provide continuous health monitoring and analysis of physiological parameters. A high degree of QoS for BSN is desperately required. Inter-user interference is introduced by the simultaneous communication of BSNs congregating in the same area. Wu et al. BIB009 proposed a decentralized inter-user interference suppression algorithm for BSN, called the Decentralized inter-user Interference Suppression in body sensor networks with non-cooperative Game (DISG). While a lot of contributions have been available on some important aspects of WSNs, supporting QoS in WSNs is still a largely unexplored issue. In mechanism design, each participating entity is often called an agent. In a mechanism, the participants can obtain the maximum benefit by reporting their parameters subject to a given algorithm. The mechanism of this kind is called a Strategyproof mechanism and also known as credible mechanism. In other words, in strategyproof mechanism, truth telling is a dominant strategy. A rational participant in order to maximize its interests will tell the truth. Strategyproof can well coordinate resource sharing among autonomous entities and collaboration to achieve the system's self-support and healthy development. Mechanism design is the most important application of the non-cooperative game theory. Although the system can achieve NE by mechanism design, but often only a sub-optimal result is obtained. Pareto Optimality can be derived from cooperative game theory. The theory will help protect the overall performance of WSN. However, the cooperative game theory only considers the ideal computing model. This simplification not only ignores the corresponding QoS constraints, but also ignores the diversity of operations, resources, heterogeneous and dynamic environments. Therefore, it is necessary to consider QoS with reference to constrained cooperative game theory and focus on the following questions: (1) QoS constrained algorithmic mechanism design. (2) QoS constrained and group strategyproof distributed algorithmic mechanism design. (3) QoS constrained cooperative game theory. Based on the ideal computing model for the specific application, one should study the mechanism designs of different characteristics by considering QoS constrained and in combination with the cooperative game theory.