Game Theory for Wireless Sensor Networks: A Survey <s> Resource Management-Spectrum Allocation and Bandwidth Allocation <s> Impulse radio-ultra wideband (IR-UWB) communication is a strong candidate for short-range biomedical wireless sensor networks (BWSN). In this paper, we propose a multiband/multiuser IR-UWB scheme, which is robust against unknown narrowband interference (NBI), by deploying multiband signaling with forward error correction (FEC) coding and subband scheduling. We define our problem with an n-transmitter Jamming game and find a Nash equilibrium (NE) for such a game. By the NE result we say that a uniform access to all the subband resources from all the sensors can form a fair situation for the system. In addition, we propose a fair subband scheduling that is required to provide each sensor with uniform opportunity of avoiding the unknown NBI. We cast the problem of finding the fair subband schedule into a multi-objective integer programming, and plan to solve it using Nash bargaining solutions (NBS). <s> BIB001 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Resource Management-Spectrum Allocation and Bandwidth Allocation <s> Impulse radio ultra-wideband (IR-UWB) communication is a strong candidate for short range wireless sensor networks (BWSN). One of the biggest challenges in IR-UWB is to suppress the performance degradation due to concurrent narrowband interferences (NBIs). There are two main possible ways of NBI suppression, namely, cancellation and avoidance. The former is difficult to be implemented since it makes receivers largely complicate (e.g., high speed sampling and Rake receivers), and the latter requires accurate detection of NBI center frequency. In this paper we consider a multiuser multiband IR-UWB where no NBI detection mechanism is available due to complexity constraints of implanted biomedical sensors. In this situation, we are interested in finding a transmission scheduling policy that provides a stable state where no single sensor deviates from the scheduling. To this end, we model multiuser multiband IR-UWB as n-transmitter jammer game, and computes its Nash equilibrium that corresponds to the definition of the stable state. We observe that the steady state based on the Nash equilibrium provides a scheduling with the policy of letting all sensors access to all available subbands uniformly. We evaluate the scheduling scheme based on the steady state by comparing it with non-uniform random access scheduling. <s> BIB002 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Resource Management-Spectrum Allocation and Bandwidth Allocation <s> The dragonfly adult has been extensively studied as a model insect for the design of robots and more recently MAV (Micro-Aerial Vehicle). In particular, its flight and vision-guided navigation mechanisms have been widely adopted in the design of MAV and robots. The wings of dragonfly have been investigated to develop new generation of nanocomposite MEMS materials. In this article, we are interested in some other behaviors of dragonfly, which can be inspirational for flight and communication control of a fleet (population) of UAV/MAVs. Specifically, the territory behaviors and mating systems of dragonflies are able to automatically control the accesses to limited number of female dragonflies by male dragonflies. We suggest that this kind of mechanisms used by dragonflies may be used for engineering applications such as optimal deployment of UAV/MAV or robots in unpredictable or hostile environments. Similarly, they may be inspirational for solving problems such as the optimal coverage of wireless sensor networks (WSN) or channel time-sharing in wireless communications. Due to the population nature (a population of dragonflies vs. a fleet of UAV/MAV) of the dragonfly-behavior-inspired applications, mathematical modeling tools such as Evolutionary Game theory and Rendezvous Search Game theory are suggested to transfer biological inspirations to engineering designs. <s> BIB003 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Resource Management-Spectrum Allocation and Bandwidth Allocation <s> We propose a virtualization framework to separate the network operator (NO) who focuses on wireless resource management and service providers (SP) who target distinct objectives with different constraints. Within the proposed framework, we model the interactions among SPs and NO as a stochastic game, each stage of which is played by SPs (on behalf of the end users) and is regulated by the NO through the Vickrey-Clarke-Groves (VCG) mechanism. Due to the strong coupling between the future decisions of SPs and lack of global information at each SP, the stochastic game is notoriously hard. Instead, we introduce conjectural prices to represent the future congestion levels the end users potentially will experience, via which the future interactions between SPs are decoupled. Then, the policy to play the dynamic rate allocation game becomes selecting the conjectural prices and announcing a strategic value function (i.e., the preference on the rate) at each time. We prove that there exists one Nash equilibrium in the conjectural prices and, given the conjectural prices, the SPs have to truthfully reveal their own value function. We further prove that this Nash equilibrium results in efficient rate allocation in our virtualized wireless network. In other words, there are enough incentives for NO to advertise such a conjectural price and SPs to follow this advice. <s> BIB004 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Resource Management-Spectrum Allocation and Bandwidth Allocation <s> This paper considers a Markovian dynamical game theoretic setting for distributed transmission control in a wireless sensor network. The available spectrum bandwidth is modeled as a Markov chain. A distributed algorithm named correlated Q-learning algorithm is proposed to obtain the correlated equilibrium policies of the system. This algorithm has the decentralized feature and is easily implementable in a real system. Numerical example is also provided to verify the performances of the proposed algorithms. <s> BIB005 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Resource Management-Spectrum Allocation and Bandwidth Allocation <s> In this paper, the problem of sequential estimation in a wireless sensor network (WSN) is formulated in a cooperative game theoretic framework. This framework allows addressing the issue of fair resource allocation for sequential estimation task at the Fusion center (FC) in a WSN as a solution of a cooperative game. We propose a simple game theoretic solution to the problem of power allocation for sensor nodes that are subjected to power constraints. Simulation results show that the proposed solution has the same performance trend (in terms of the estimator quality at the FC) as when all nodes transmit at their maximum powers, while our proposed solution leads to an overall improvement of the network lifetime. <s> BIB006 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Resource Management-Spectrum Allocation and Bandwidth Allocation <s> In this paper, the problem of sequential estimation and lifetime maximization of a wireless sensor network (WSN) is formulated in a cooperative game theoretic framework. This framework allows addressing problems of fair resource allocation for sequential estimation at the Fusion center (FC) of a wireless sensor network as a solution of a cooperative game. We propose a simple game theoretic solution to power allocation problem for sensor nodes such that the obtained solution leads to increased lifetime of the WSN. Simulation results show that the proposed solution achieves target estimation quality at the FC, and at the same time lifetime of the overall sensor network is increased. <s> BIB007
It is a salient and desirable feature that wireless sensors are deployed in a large number and with a high degree of redundancy. The sensors are therefore mostly manufactured with small size, light weight. Hence the resources, such as power, computation and communication capabilities, that can be embedded onboard the sensor are always limited. Resource management is thus an important consideration while designing a WSN. Impulse Radio-Ultra WideBand (IR-UWB) communication is a strong candidate for short-range biomedical wireless sensor networks (BWSN). Moussavinik et al. BIB001 BIB002 proposed a multiband/ multiuser IR-UWB scheme, which is robust against unknown NarrowBand Interference, by deploying multiband signaling with Forward Error Correction coding and subband scheduling. They defined the problem with an n-transmitter Jamming game and find a NE for such a game. Furthermore, they cast the problem of finding the fair sub-band schedule into a multi-objective integer programming problem, and planed to solve it using NBS. Ma et al. BIB003 solved problems such as the optimal coverage of WSN or channel time-sharing in wireless communications inspired by the territory behaviors and mating systems of dragonflies. Fu and Kozat BIB004 developed a virtualization framework to separate the network operator (NO) who focuses on wireless resource management and service providers (SP) who targets distinct objectives with different constraints. Within the proposed framework, the authors modeled the interactions among SPs and NO as a stochastic game, each stage of which is played by SPs and is regulated by the NO through the Vickrey-Clarke-Groves (VCG) mechanism. Due to the strong coupling between the future decisions of SPs and lack of global information at each SP, the stochastic game is notoriously hard. They introduced conjectural prices to represent the future congestion levels the end users potentially will experience, via which the future interactions between SPs are decoupled. Then, the policy to play the dynamic rate allocation game becomes selecting the conjectural prices and announcing a strategic value function at each time. They proved that there exists one NE in the conjectural prices and, given the conjectural prices, the SPs have to truthfully reveal their own value function. They further proved that this NE results in efficient rate allocation in virtualized wireless network. Huang et al. BIB005 considered a Markovian dynamical game theoretic setting for distributed transmission control in a WSN. The available spectrum bandwidth is modeled as a Markov chain. A distributed algorithm named correlated Q-learning algorithm was proposed to obtain the correlated equilibrium policies of the system. The problem of sequential estimation and lifetime maximization in a WSN was formulated in a cooperative game theoretic framework in BIB006 BIB007 , which allow the issue of fair resource allocation for sequential estimation task at the "fusion center" in a WSN as a solution of a cooperative game.