As the demand for high-throughput communications in wireless LANs (WLAN) increases, the need for expanding channel bandwidth also increases. However, the use of wider band channels results in a decrease in the number of available channels because the total available bandwidth for WLAN is limited. Therefore, if multiple access points (APs) are in proximity and the cells overlap, it is difficult for each AP to use an orthogonal channel and competition increases between APs using the same channel. Coordination of APs is one promising approach; however, it is impractical to control all APs in WLAN systems. To cope with this problem, we proposed to analyze throughput performances of a multibandwidth channel selection by the coordinating APs at Nash equilibria, which can be considered as operating points for independent channel selection by APs. To clarify the effect of coordinating APs, we assume a simple scenario where the cells of three or more APs overlap, and each AP can select multibandwidth channels to maximize their own throughput. Through game-theoretic analysis, we find that the coordinated APs are able to select channels more effectively than if each AP independently selects channels. Consequently, the total throughput of the coordinated APs at Nash equilibria is significantly improved.

Evolutionary stability has been discussed as a fundamental issue in single-criterion games. We extend evolutionarily and neutrally stable strategies to multicriteria games. Keeping in mind the fact that a payoff is given by a vector in multicriteria games, we provide several concepts which are coincident in single-criterion games based on partial vector orders of payoff vectors. We also investigate the hierarchical structure of our proposed evolutionarily and neutrally stable strategies. Shapley had introduced concepts such as strong and weak equilibria. We discuss the relationship between these equilibria and our proposed evolutionary stability.

Recent studies have shown that the traffic load is often distributed unevenly among the access points. Such load imbalance results in an ineffective bandwidth utilization. The load imbalance and the consequent ineffective bandwidth utilization could be alleviated via intelligently selecting user-AP associations. In this paper, the diversity in users' utilities is sufficiently taken into account, and a Stackelberg leader-follower game is formulated to obtain the optimal user-AP association. The effectiveness of the proposed algorithm on improving the degree of load balance is evaluated via simulations. Simulation results show that the performance of the proposed algorithm is superior to or at least comparable with the best existing algorithms.

The dynamic competition between two bounded rational mobile virtual network operators (MVNOs) in a duopoly spectrum market is investigated. A two stage game is employed to model the interaction of the MVNOs and the quality of service of the secondary users is taken into account. The evolutionary game theory is introduced to model the dynamic strategy selections of MVNOs. Using replicated dynamics, the proposed evolutionary game algorithm can converge to a unique evolutionary stable strategy. Simulation results verify that the proposed algorithm can make the MVNOs adaptively adjust the strategies to approximate optimal solution.

In this paper, a hybrid overlay/underlay cognitive radio system is modeled as an M/M/1 queue where the rate of arrival and the service capacity are subject to Poisson alternations. Each packet as a customer arriving at the queue makes a decision to join the queue or not. Upon arrival, the individual decision of each packet is optimized based on his observation about the queue length and the state of system. It is shown that the individually optimal strategy for joining the queue is characterized by a threshold of queue length. Thus, the individual optimal threshold of queue length is analyzed in detail in this work.

One important issue in cognitive transmission is for multiple secondary users to dynamically acquire spare spectrum from the single primary user. The existing spectrum sharing scheme adopts a deterministic Cournot game to formulate this problem, of which the solution is the Nash equilibrium. This formulation is based on two implicit assumptions. First, each secondary user is willing to fully exchange transmission parameters with all others and hence knows their complete information. Second, the unused spectrum of the primary user for spectrum sharing is always larger than the total frequency demand of all secondary users at the Nash equilibrium. However, both assumptions may not be true in general. To remedy this, the present paper considers a more realistic assumption of incomplete information, i.e., each secondary user may choose to conceal their private information for achieving higher transmission benefit. Following this assumption and given that the unused bandwidth of the primary user is large enough, we adopt a probabilistic Cournot game to formulate an opportunistic spectrum sharing scheme for maximizing the total benefit of all secondary users. Bayesian equilibrium is considered as the solution of this game. Moreover, we prove that a secondary user can improve their expected benefit by actively hiding its transmission parameters and increasing their variance. On the other hand, when the unused spectrum of the primary user is smaller than the maximal total frequency demand of all secondary users at the Bayesian equilibrium, we formulate a constrained optimization problem for the primary user to maximize its profit in spectrum sharing and revise the proposed spectrum sharing scheme to solve this problem heuristically. This provides a unified approach to overcome the aforementioned two limitations of the existing spectrum sharing scheme.

With the proliferation of IEEE 802.11 wireless local area networks, large numbers of wireless access points have been deployed, and it is often the case that a user can detect several access points simultaneously in dense metropolitan areas. Most owners, however, encrypt their networks to prevent the public from accessing them due to the increased traffic and security risk. In this work, we use pricing as an incentive mechanism to motivate the owners to share their networks with the public, while at the same time satisfying users' service demand. Specifically, we propose a “federated network” concept, in which radio resources of various wireless local area networks are managed together. Our algorithm identifies two candidate access points with the lowest price being offered (if available) to each user. We then model the price announcements of access points as a game, and characterize the Nash Equilibrium of the system. The efficiency of the Nash Equilibrium solution is evaluated via simulation studies as well.

In this paper, a decentralized concurrent transmission strategy in shared channel in Ad Hoc networks is proposed based on game theory. Firstly, a static concurrent transmissions game is used to determine the candidates for transmitting by channel quality threshold and to maximize the overall throughput with consideration of channel quality variation. To achieve NES (Nash Equilibrium Solution), the selfish behaviors of node to attempt to improve the channel gain unilaterally are evaluated. Therefore, this game allows each node to be distributed and to decide whether to transmit concurrently with others or not depending on NES. Secondly, as there are always some nodes with lower channel gain than NES, which are defined as hunger nodes in this paper, a hunger suppression scheme is proposed by adjusting the price function with interferences reservation and forward relay, to fairly give hunger nodes transmission opportunities. Finally, inspired by stock trading, a dynamic concurrent transmission threshold determination scheme is implemented to make the static game practical. Numerical results show that the proposed scheme is feasible to increase concurrent transmission opportunities for active nodes, and at the same time, the number of hunger nodes is greatly reduced with the least increase of threshold by interferences reservation. Also, the good performance on network goodput of the proposed model can be seen from the results.

In existing systems of mobile routers, the frequency band is shared in uplinks from wireless terminals to mobile routers, and carrier sense multiple access with collision avoidance (CSMA/CA) is generally used as the medium access control protocol. To use the frequency band effectively, adaptive control is one promising approach. In this paper, a decentralized access control protocol in which mobile routers adaptively select the minimum contention window size is proposed. However, because of their mobility, which is one of the main difference between mobile routers and fixed access points, individual local area networks (LANs) consisting of the mobile routers and wireless terminals randomly interact with each other, and such random interactions can cause instability. To analyze the stability of the proposed control, evolutionary game theory is introduced because a system with random interactions between numerous decision-making entities can be analyzed by using evolutionary game theory. Using evolutionary game theory, the condition for existence of a convergence point is obtained. In addition, to implement the decentralized access control, a learning rule is proposed. In the proposed learning rule, each mobile router selects a strategy based on the result of past trials. From the simulation result, it is confirmed that the decentralized access control converges to a point closed to the stable state derived through evolutionary game theory.

The Voronoi game is a two-person perfect information game modeling a competitive facility location. The original version of the game is played on a continuous domain. Only two special cases (1-dimensional case and 1-round case) have been extensively investigated. Recently, the discrete Voronoi game of which the game arena is given as a graph was introduced. In this note, we give a complete analysis of the discrete Voronoi game on a path. There are drawing strategies for both the first and the second players, except for some trivial cases.

In this letter, an AGV based relay selection mechanism is developed to ensure relays reporting true information in wireless relay networks. The source selects relays based on the channel state information (CSI) of relay-destination links. Selfish relays may report fake CSI in order to obtain a better chance of being selected, whereas the source is not able to tell the reported in real or in false. In the proposed scheme, a relay node receives some payoffs from the destination with respect to the achievable data rate and also some compensations from the others in terms of the reported CSI of all relays. This mechanism not only enforces truth-telling upon relay nodes with maximum payoff but also ensures fairness among them. The equilibrium of payoff is attained when relay nodes report their true CSI. Simulation results demonstrate the theoretical solutions.

It has been shown that power control is an efficient approach to achieve the quality of service (QoS) requirement in wireless networks. In this letter, we present a utility function that denotes the QoS and energy efficiency of each wireless terminal. We propose a framework of power control based on the game theory for the QoS of wireless mesh networks (WMNs). In this framework, all players do their best to maximize their own utility. Furthermore, we present a Nash Equilibrium (NE) point of the power control game. We prove that the equilibrium is inefficient, and we propose a distributed power control algorithm that improves the total utility with respect to the NE point. Finally, the proposed framework is evaluated by a numerical experiment, the results of which show the rationality of our system model and the efficiency of our power control algorithm.

In a spectrum sharing system, lower-priority users are allowed to spatially reuse the spectrum allocated to higher-priority users as long as they do not disrupt communications of the latter. Therefore, to improve spectrum utilization, an important requirement for the former users is to manage the interference and ensure that the latter users can maintain reliable communications. In the present paper, a game theoretic framework of joint channel selection and power allocation for spectrum sharing in distributed cognitive radio networks is proposed. First, a utility function that captures the cooperative behavior to manage the interference and the satisfaction level to improve the throughput of the lower-priority users is defined. Next, based on the defined utility function, the proposed framework can be formulated as a potential game; thus, it is guaranteed to converge to a Nash equilibrium when the best response dynamic is performed. Simulation results show the convergence of the proposed potential game and reveal that performance improvements in terms of network throughput of the lower-priority users and outage probability of the higher-priority users can be achieved by the introduction of an adaptive coefficient adjustment scheme in the proposed utility function at the expense of the convergence to the Nash equilibrium.

Recent studies investigating the Internet topology reported that inter Autonomous System (AS) topology exhibits a power-law degree distribution which is known as the scale-free property. Although there are many models to generate scale-free topologies, no game theoretic approaches have been proposed yet. In this paper, we propose the new dynamic game theoretic model for the AS level Internet topology formation. Through numerical simulations, we show our process tends to give emergence of the topologies which have the scale-free property especially in the case of large decay parameters and large random link costs. The significance of our study is summarized as following three topics. Firstly, we show that scale-free topologies can also emerge from the game theoretic model. Secondly, we propose the new dynamic process of the network formation game for modeling a process of AS topology formation, and show that our model is appropriate in the micro and macro senses. In the micro sense, our topology formation process is appropriate because this represents competitive and distributed situation observed in the real AS level Internet topology formation process. In the macro sense, some of statistical properties of emergent topologies from our process are similar to those of which also observed in the real AS level Internet topology. Finally, we demonstrate the numerical simulations of our process which is deterministic variation of dynamic process of network formation game with transfers. This is also the new result in the field of the game theory.

Based on game theory, a distributed power control algorithm with sequential subchannel nulling is proposed for ad-hoc networks. It is shown that the proposed method, by sharing subchannels appropriately according to the interference profiles, can reduce the power consumption of the network while satisfying the target rate of each link.

Custody transfer in delay tolerant networks (DTNs) provides reliable end-to-end data delivery by delegating the responsibility of data transfer among special nodes (custodians) in a hop-by-hop manner. However, storage congestion occurs when data increases and/or the network is partitioned into multiple sub-networks for a long time. The storage congestion can be alleviated by message ferries which move around the network and proactively collect data from the custodians. In such a scenario, data should be aggregated to some custodians so that message ferries can collect them effectively. In this paper, we propose a scheme to aggregate data into selected custodians, called aggregators, in a fully distributed and autonomous manner with the help of evolutionary game theoretic approach. Through theoretical analysis and several simulation experiments, taking account of the uncooperative behavior of nodes, we show that aggregators can be selected in a self-organized manner and the number of aggregators can be controlled to a desired value.

In this paper, we propose a rational m-out-of-n secret sharing scheme, a dealer wishes to entrust a secret with a group of n players such that any subset of m or more players can reconstruct the secret, but a subset of less than m players cannot learn anything about the secret. The reconstruction protocol of our scheme is fair and stable in the rational settings, allowing all players to obtain the designated secret. Our scheme is based on RSA-OAEP with the distributed decryption. The security of our scheme relies on a computational assumption and uses the random oracles. The size of each share in our scheme is independent of the utility function and the computation cost of the reconstruction protocol is constant. Moreover, our scheme prevents the attacks with at most m-1 coalitions.

In the present paper, the performance of cooperative relaying networks with adaptive relaying scheme selection is analyzed. Cooperative relaying is a new technique to achieve spatial diversity gain by using neighboring stations. However, when multiple stations transmit simultaneously, the number of interference signals increases. Therefore, the introduction of cooperative relaying in radio communication systems does not always increase the network capacity due to the co-channel interference. Therefore, in order to achieve high spectral efficiency, it is necessary to select cooperative relaying or non-cooperative relaying adaptively. Assuming both centralized and decentralized adaptive controls, the spectrum efficiency is evaluated. The performance under decentralized control is evaluated using a game-theoretic approach. Simulation results show that the introduction of cooperative relaying with centralized control always increases the spectral efficiency. On the other hand, Simulation results also show that, when each source selects a relaying scheme independently and selfishly to maximize its own spectral efficiency, the introduction of the cooperative relaying may reduce the spectral efficiency due to the increase in the number of interference signals.

In this paper, we focus on the adaptive resource allocation issue for uplink OFDMA systems. The resources are allocated according to a proportional fairness criterion, which can strike an alterable balance between fairness and efficiency. Optimization theory is used to analyze the multi-constraint resource allocation problem and some heuristic characteristics about the optimal solution are obtained. To deal with the cohesiveness of the necessary conditions, we resort to bargaining theory that has been deeply investigated in game theory. Firstly, we summarize some assumptions about bargaining theory and show their similarities with the resource allocation process. Then we propose a priority-ranked bargaining model, whose primary contribution is applying the economic thought to the resource allocation process. A priority-ranked bargaining algorithm (PRBA) is subsequently proposed to permit the base station to auction the subcarriers one by one according to the users' current priority. By adjusting the predefined rate ratio flexibly, PRBA can achieve different degrees of fairness among the users' capacity. Simulation results show that PRBA can achieve similar performance of the max-min scheme and the NBS scheme in the case of appropriate predefined rate ratio.

Equipping wireless routers with multiple radios further improves the capacity by transmitting over multiple radios simultaneously using orthogonal channels. Efficient channel assignment schemes can greatly alleviate the interference effect of nearby transmissions. One of the distinctive features in wireless multi-hop networks is the lack of any central controller, in which each node makes its own decisions. Therefore, fully cooperative behaviors, such as cooperation for increasing link capacity, alleviating interferences for one another, might not be directly applied. In this paper, we aim to present some applications to show how such a framework can be invoked to design efficient channel assignment algorithms in a non-cooperative, topology-blind environment as well as in environments where the competing players share perfect information about channel usage and topology environment and so on. Simulation results are presented to illustrate the effectiveness of the algorithms.