Game Theory for Wireless Sensor Networks: A Survey <s> Others <s> Sensor networks are large scale networks of low-power devices that collaborate in order to perform a given task. The sensors are limited in battery energy, capacity and computational power. In recent years, researchers have proposed several protocols for such sensor networks assuming that all sensors belong to the same authority. In this paper, we introduce the concept of multidomain sensor networks that was, to the best of our knowledge, never considered before. We propose a game-theoretic model to investigate the impact of cooperation and show the conditions for which cooperation is the best strategy. <s> BIB001 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Others <s> This work is motivated by the need for an ad hoc sensor network to autonomously optimise its performance for given task objectives and constraints. Arguing that communication is the main bottleneck for distributed computation in a sensor network we formulate two approaches for optimisation of computing rates. The first is a team problem for maximising the minimum communication throughput of sensors and the second is a game problem in which cost for each sensor is a measure of its communication time with its neighbours. We investigate adaptive algorithms using which sensors can tune to the optimal channel attempt rates in a distributed fashion. For the team problem, the adaptive scheme is a stochastic gradient algorithm derived from the augmented Lagrangian formulation of the optimisation problem. The game formulation not only leads to an explicit characterisation of the Nash equilibrium but also to a simple iterative scheme by which sensors can learn the equilibrium attempt probabilities using only the estimates of transmission and reception times from their local measurements. Our approach is promising and should be seen as a step towards developing optimally self-organising architectures for sensor networks. <s> BIB002 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Others <s> Deployment of wireless sensors to efficiently forward information through a large array is considered from a game-theoretic perspective. Sensors with limited awareness learn to make local decisions (sleep/wake) in order to forward data in a slowly varying environment through a "Regret Matching" algorithm. With appropriately small smoothing and perturbation, we are able to apply results from stochastic approximation to establish global convergence of this algorithm and for an adaptive variant. The adaptive version allows sensor network connections to be reconfigured as game conditions change. We illustrate this reconfigurability with respect to channel fading, changing network demands, and sensor failure. Instead of the Blackwell approachability method used in previous papers, we give an ordinary differential equation formulation with a Liapunov function to prove convergence to a correlated equilibrium. Numerical studies show that the algorithms can satisfactorily track correlated equilibria in systems of several thousand sensors, resulting in near competitive optimality at each sensor. <s> BIB003 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Others <s> We provide a game theoretic formulation for a sensor activation problem in a multi-attribute environment. Activated sensors randomly select one of M environmental attributes, and transmit data on that attribute to an end user. The goal is to maximize the number of attributes reported while minimizing redundant reports and packet collisions, which both increase with the number of active sensors. Sensor participation is optimized according to an adaptive scheme, in which sensors activate only when their expected utility, given by the number of unique attributes reported minus an energy cost, is positive. We formulate a Nash equilibrium policy that maximizes the expected performance from the perspective of each sensor when transmission is according to a one-shot frequency hopping scheme, and compare this to the global optimum. <s> BIB004 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Others <s> In the prevailing development of applying wireless sensor networks to human body monitoring, it should be carefully addressed on the possible adverse effects caused by radio frequency radiation to the body, especially for long term, intensive and close inspection. This paper first investigates the bioeffects caused by radiofrequency transmission of sensor node, including thermal effects and athermal effects. The bioeffects model is studied in both near-field and far-field, in relation to Specific Absorption Rate (SAR). A bioeffects metric is then proposed to evaluate the adverse biological effects. After identifying the factors that can reduce the adverse health effects in the communication system we propose a game theoretic model of distributed power control to analysis bioeffects for the system. The bioeffects cost function is introduced to the network utility as a metric to evaluate the performance of wireless body sensor networks in terms of health effect consideration. The two main contributions of this work are that a normalized bioeffects metric, equivalent Coefficient-of-Absorption-and-Bioeffects (CAB), is introduced to evaluate and design the communication protocols, and a novel game theoretic power control model is employed to balance the bioeffects for CDMA-Based wireless body sensor networks. <s> BIB005 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Others <s> Wireless Biosensor Networks will enhance the medical performances due to its many advantages such as long term monitoring, fast network establishment, untethered connectivity and ambulatory diagnosis. The network protocol plays a paramount role in performing the medical tasks. Due to many unique challenges imposed on the network design in wireless biosensor networks, especially when it is related to healthcare, there are a lot of network optimization problems to be solved in the network design such as congestion control, medium access control, power control and bioeffects control etc. These issues involve several layers of the network protocol stack so that it is not practical to consider every single optimization problem independently. It is better to consider the whole network stack as adaptive cross layer optimization problem in a holistic view. The main contribution of this paper is the employment of cross layer optimization methods to combat the unique challenges posed to the WBSN. Two preliminary optimization schemes are proposed: one is for joint congestion control and medium access control, and the other for joint power and bioeffects control. In the later scheme, we introduce the biological effects into the utility model for two purposes, one is to evaluate and control the bioeffects caused by higher power radiofrequency, and the other is to use it as the cost of non-cooperative game for each node. This position paper also briefly outlines the current methodologies exploited for wireless network cross layer design and investigates the theoretical problems. <s> BIB006 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Others <s> This paper first investigates the bioeffects caused by radiofrequency transmission of sensor node, including thermal effects and athermal effects. The bioeffects model is studied in both near-field and far-field, in relation to specific absorption rate (SAR). A bioeffects metric is then proposed to evaluate the adverse biological effects. After identifying the factors that can reduce the adverse health effects in the communication system we propose a game theoretic model of distributed power control to analysis bioeffects for the system. The bioeffects cost function is introduced to the network utility as a metric to evaluate the performance of wireless body sensor networks in terms of health effect consideration. The two main contributions of this work are that a normalized bioeffects metric, equivalent coefficient-of-absorption-and-bioeffects (CAB), is derived to evaluate and design the communication protocols, and a novel game theoretic power control model is employed to balance the bioeffects for CDMA-based wireless body sensor networks. <s> BIB007 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Others <s> We describe a class of decentralized, game theoretic adaptive algorithms which can be deployed to manage sensor activities with low coordination overhead. This class includes traditional game theoretic algorithms such as fictitious play as well as new dynamically adaptive regret matching algorithms, which allow sensors to track a competitively optimal (correlated equilibrium) set of behaviour as it evolves in time. Two applications are given, to a ZigBee-enabled unattended ground sensor network for intruder monitoring, and to a dynamic spectrum allocation scheme for wireless sensor communication. <s> BIB008 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Others <s> We describe a decentralized learning-based activation algorithm for a ZigBee-enabled unattended ground sensor network. Sensor nodes learn to monitor their environment in a low-power "sleep" mode, until an intruder is detected, then enter a full-power mode only if the benefit for doing so outweighs an energy cost. Our formulation accounts for the energy required to transmit and the probability of successful transmission in a crowded ZigBee network. Since these depend on the activity of other nodes, we propose a decentralized adaptive algorithm for sensor activation based on game theoretic principles. We show that the algorithm tracks the time-varying set of correlated equilibria of the problem, and illustrate performance through simulation. The algorithm is described as a stochastic approximation, with attendant differential inclusion analysis. <s> BIB009 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Others <s> Wireless Sensor Networks (WSNs) deployed in hostile environments are susceptible to various attacks directed at their data. In this work we focus on an emerging and largely unexplored issue arising from the presence of actuator (or actor) nodes in the form of Wireless Sensor Actuator Networks (WSANs). Specifically, we consider the case where hostile WSAN nodes belonging to a foreign network directly perturb the readings of WSN nodes during sensing. The attack is modeled as affecting the decision that a WSN node reports about the presence or absence of a phenomenon to its cluster head. To assess the potential loss of sensing fidelity due to the opposing network, we employ a game theoretic analysis. We focus on determining the probability that the WSN cluster head becomes alerted to such an attack given some statistical information about the phenomenon. Our results show that an actuation attack may go unnoticed even if such an attack is not coordinated among the hostile WSAN nodes. Importantly, the number of WSN nodes in a cluster affects the probability of WSAN attack success. For clusters consisting of only a few nodes, the hostile WSAN may achieve a stealthy attack with a wider range of attack parameters. We also determine that natural phenomena with certain characteristics are more susceptible to the attack and require further sensing-verification mechanisms. <s> BIB010 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Others <s> Wireless sensor networks are distributed ad-hoc networks that consist of small sensor devices collecting and transmitting data. In such devices, optimizing power consumption due to sensing and routing data is an open area for researchers. In earlier works, approaches based on the Gur game, ant algorithms and evolutionary algorithms were introduced. These approaches have been employed to control the number of active sensors in wireless networks required to guarantee high performance parameters while taking energy conservation into consideration. These studies though ignored the coverage redundancy, which is a key issue in sensor networks. In this paper, we use the mathematical paradigm of the Gur Game in order to achieve the optimal assignment of active sensors while maximizing the number of regions covered by sensor nodes. We use a dynamic clustering algorithm that employs the concept of connected dominating sets. The proposed algorithm addresses this problem by playing Gur Game among the cluster nodes. We also further develop the earlier developed ants algorithm and genetic algorithm to take into consideration node addition and deletion. A simulation study was used to test the proposed algorithms under different network scenarios. <s> BIB011 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Others <s> We present decentralized adaptive filtering algorithms for sensor activation control in an unattended ground sensor network (UGSN) comprised of ZigBee-enabled nodes. Nodes monitor their environment in a low-power ldquosleeprdquo mode, until an intruder is detected, then must decide whether to enter a full-power monitoring and transmission mode if their estimated average performance for activation outweighs their energy cost. The tradeoff is formulated in terms of the energy required to transmit data using the ZigBee protocol, probability of successful transmission, and the expected marginal increase in global utility resulting from a report, all of which depend on the activity of nearby sensor nodes. Since activation control is decentralized, and utilities are codependent, the adaptive filtering/stochastic approximation algorithms that we propose for sensor activation are based on game theoretic principles. We show that if each sensor operates according to this algorithm, the entire network is capable of actively tracking the correlated equilibrium set of the underlying game, which varies with target motion, node failures, or intentional parameter adjustments. We analyze the convergence and tracking properties of the adaptive filtering algorithms using differential inclusions. <s> BIB012 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Others <s> Traditional networks are built on the assumption that network entities cooperate based on a mandatory network communication semantic to achieve desirable qualities such as efficiency and scalability. Over the years, this assumption has been eroded by the emergence of users that alter network behavior in a way to benefit themselves at the expense of others. At one extreme, a malicious user/node may eavesdrop on sensitive data or deliberately inject packets into the network to disrupt network operations. The solution to this generally lies in encryption and authentication. In contrast, a rational node acts only to achieve an outcome that he desires most. In such a case, cooperation is still achievable if the outcome is to the best interest of the node. The node misbehaviour problem would be more pronounced in multihop wireless networks like mobile ad hoc and sensor networks, which are typically made up of wireless battery-powered devices that must cooperate to forward packets for one another. But, cooperation may be hard to maintain as it consumes scarce resources such as bandwidth, computational power and battery power. This paper applies game theory to achieve collusive networking behavior in such network environments. In this work, pricing, promiscuous listening and mass punishments are avoided altogether. Our model builds on recent work in the field of Economics on the theory of imperfect private monitoring for the dynamic Bertrand oligopoly, and adapts it to the wireless multihop network. The model derives conditions for collusive packet forwarding, truthful routing broadcasts and packet acknowledgments under a lossy, wireless, multi-hop environment, thus capturing many important characteristics of the network layer and link layer in one integrated analysis that has not been achieved previously. Finally, we provide a proof of the viability of the model under a theoretical wireless environment. <s> BIB013 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Others <s> Support for intelligent, autonomous, adaptive and distributed resource management is a key to the success of scalable and dynamic wireless sensor network applications. Distributed independent reinforcement learning (DIRL) is a micro-learning framework that enables distributed, adaptive resource management using only local information at individual sensor nodes. In this paper we propose COllective INtelligence (COIN) a macro-learning paradigm that aims to specifically address the problem of designing utility functions for individual agents in order to achieve higher system wide utility. We extend DIRL, by combining it with COIN based macro-learning paradigm to steer the system towards global optimization, improving performance with minimal communication overheads. We present results of simulation to compare our approach with other existing approaches such as team game and DIRL in an example object tracking application. Simulation results demonstrate that a combination of micro- and macro-learners is two times more energy-efficient than micro-learners (DIRL) alone and four times more energy-efficient than macro-learners (TEAM game) alone. <s> BIB014 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Others <s> In this work we consider an event-driven wireless visual sensor network (WVSN) comprised of untethered camera nodes and scalar sensors deployed in a hostile environment. In the event-driven paradigm, each camera node transmits a surveillance frame to the cluster-head only if an event of interest was captured in the frame, for energy and bandwidth conservation. We thus examine a simple image processing algorithm at the camera nodes based on difference frames and the chi-squared detector. We show that the test statistic of the chi-squared detector is equivalent to that of a robust (non-parametric) detector and that this simple algorithm performs well on indoor surveillance sequences and some, but not all, outdoor sequences. In outdoor sequences containing significant changes in background and lighting, this simple detector may produce a high probability of error and benefits from the inclusion of scalar sensor decisions. The scalar sensor decisions are, however, prone to attack and may exhibit errors that are arbitrarily frequent, pervasive throughout the network and difficult to predict. To achieve attack prediction and mitigation given an attacker whose actions are not known a priori, we employ game-theoretic analysis. We show that the scalar sensor error can be controlled through cluster-head checking and appropriate selection of cluster size n. Given this attack mitigation, we employ real-life sequences to determine the total probability of error when individual and combined decisions are utilized and we discuss the ensuing ramifications and performance issues. <s> BIB015 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Others <s> There is a critical need to provide privacy assurances for distributed vision-based sensor networking in applications such as building surveillance and healthcare monitoring. To effectively address protection and reliability issues, secure networking and processing must be considered from system inception. This paper presents attacks that affect the data privacy in visual sensor networks and proposes privacy-promoting security solutions based on opponent detection via game-theoretic analysis and keyless encryption. <s> BIB016 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Others <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> BIB017 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Others <s> Traditional distributed source coding rarely considers the possible link between separate encoders. However, the broadcast nature of wireless communication in sensor networks provides a free gossip mechanism which can be used to simplify encoding/decoding and reduce transmission power. Using this broadcast advantage, we present a new two-encoder scheme which imitates the ping-pong game and has a successive approximation structure. For the quadratic Gaussian case, we prove that this scheme is successively refinable on the {sum-rate, distortion pair} surface, which is characterized by the rate-distortion region of the distributed two-encoder source coding. A potential energy saving over conventional distributed coding is also illustrated. This ping-pong distributed coding idea can be extended to the multiple encoder case and provides the theoretical foundation for a new class of distributed image coding method in wireless scenarios. <s> BIB018 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Others <s> Current advances in wireless sensor networks have contributed to the development of multi-hop wireless body sensor networks (WBSNs). These networks, which are primarily comprised of low-power sensor nodes, provide long term health and physiological monitoring of patients without obstructing their normal activities. However, the time-varying nature of network resources poses a significant challenge to the high reliability of operations required of a body sensor network. In this paper, we address the problem of reliability optimization in multi-hop WBSNs, where the nodes co-operate with each other in maximizing system performance. We model our problem as a co-operative game which inherently induces a distributed mechanism that optimizes the reliability of network operations in a multi-hop WBSN supporting concurrent applications. By the term ‘reliability’, we imply the system utility generated when each sensor node (user) services its specific application. We denote the system utility as an instance of the vector of utilities of individual users, where each user's utility is a function of its allocated bandwidth. Our mechanism jointly accounts for the dynamistic nature of the wireless medium, application quality of service, user fairness in achieving the resources to service applications, and results in an optimal operating point (utility vector) at which the WBSN should operate. We arrive at the result that the Nash bargaining solution of the co-operative game gives us the optimal system operating point, i.e., the Nash bargaining solution optimizes the overall system reliability. <s> BIB019 </s> Game Theory for Wireless Sensor Networks: A Survey <s> Others <s> In this paper, we deal with a scheduling algorithm to fulfil a qualified end-to-end video service in terms of fairness and energy efficiency over multi-hop wireless sensor networks. For this goal, we explore to optimize the routing and power allocation via cross-layer optimization by utilizing a game-theoretic approach. In order to reduce computational complexity, we also propose a distributed optimization algorithm. In the simulation results, we demonstrate an improved performance of the proposed distributed algorithm. <s> BIB020
Felegyhazi et al. BIB001 introduced the concept of multi-domain sensor networks to a WSN, it contains a game-theoretic model to investigate the impact of cooperation, and shows conditions for which cooperation is the best strategy. Nayer and Ali BIB011 used Gur Game in order to achieve the optimal assignment of active sensors while maximizing the number of regions covered by sensor nodes. They used a dynamic clustering algorithm that employs the concept of connected dominating sets. The proposed algorithm addresses this problem by playing the Gur Game among the cluster nodes. They also further developed the earlier ants algorithm and genetic algorithm to take into consideration node addition and deletion. Karnik et al. BIB002 formulated two approaches for optimization of computing rates. The first is a team problem for maximizing the minimum communication throughput of sensors, and the second is a game problem in which cost for each sensor is a measure of its communication time with its neighbors. The game formulation not only leads to an explicit characterization of the NE but also to a simple iterative scheme by which sensors can learn the equilibrium attempt probabilities using only the estimates of transmission and reception times from their local measurements. Krishnamurthy et al. BIB012 presented decentralized adaptive filtering algorithms for sensor activation control in an unattended ground sensor network (UGSN) comprised of ZigBee-enabled nodes. Krishnamurthy and Hanh  considered finite-size slotted ALOHA sensor networks with multiple packet reception capability and selfish sensors. The problem is formulated as a finite player finite action, non-cooperative stochastic game where each sensor is a selfish but rational player. Instead of the Blackwell approachability method used in previous works, Krishnamurthy et al. BIB003 gave an ordinary differential equation formulation with a Lyapunov function to prove convergence to a correlated equilibrium. Kwanghyun et al. BIB020 dealt with a scheduling algorithm to fulfill a qualified end-to-end video service in terms of fairness and energy efficiency over multi-hop wireless sensor networks. In  , on the basis of comprehensive consideration of game theory and the IEEE 802.11 Distributed Coordination Function (DCF), for the characteristics of the WSN, the authors put the channel competitive process between nodes molded into an incompletely information dynamic game. Then improve DCF by the NE game strategy. The simulation results show that the proposed model and strategy can obtain higher efficiency than the 802.11 DCF and improve many performances of the WSN. Maskery and Krishnamurthy BIB004 BIB008 BIB009 described a decentralized game theoretic adaptive algorithm and learning-based activation algorithm for a ZigBee-enabled unattended ground sensor network. See-Kee and Seah BIB013 applied GT to achieve collusive networking behavior in WSNs. Shah and Kumar BIB014 proposed, COllective INtelligence (COIN), a macro-learning paradigm that aims to specifically address the problem of designing utility functions for individual agents in order to achieve higher system wide utility. They extended the method of distributed independent reinforcement learning, by combining it with COIN based macro-learning paradigm to steer the system towards global optimization, and improve performance with minimal communication overheads. Zichong et al. BIB018 presented a two-encoder scheme which imitates the ping-pong game and has a successive approximation structure. This ping-pong distributed coding idea can be extended to the multiple encoder case and provides the theoretical foundation for a new class of distributed image coding method in wireless scenarios. Czarlinska et al. BIB015 BIB010 BIB016 employed the game-theoretic analysis in wireless visual sensor network (WVSN) and wireless sensor actuator networks (WSANs) which are concerned about security. Current advances in wireless sensor networks have contributed to the development of multi-hop wireless body sensor networks (WBSNs). Pal et al. BIB019 model the problem of reliability optimization in multi-hop WBSNs as a cooperative game which inherently induces a distributed mechanism that optimizes the reliability of network operations in multi-hop WBSN supporting concurrent applications. The NBS optimizes the overall system reliability. WSANs combine sensors and actuators interconnected by wireless networks in order to perform distributed sensing and action tasks. The model and simulation method as well as the framework which was proposed in  are illustrated on a Pursuit Evasion Game. Ren et al. BIB005 BIB006 BIB007 proposed a bio-effects metric to evaluate the adverse biological effects using game theory. Ma et al. BIB017 solved the problems such as the optimal coverage of WSN or channel time-sharing in wireless communications inspired by the dragonfly-behavior, using mathematical modeling tools such as evolutionary game theory and rendezvous search game theory are suggested to transfer biological inspirations to engineering designs.