Coalitional game theory for communication networks

In this tutorial, we provided a comprehensive overview of coalitional game theory, and its usage in wireless and communication networks. For this purpose, we introduced a novel classification of coalitional games by grouping the sparse literature into three distinct classes of games: canonical coalitional games, coalition formation games, and coalitional graph games. For each class, we explained in details the fundamental properties, discussed the main solution concepts, and provided an in-depth analysis of the methodologies and approaches for using these games in both game theory and communication applications. The presented applications have been carefully selected from a broad range of areas spanning a diverse number of research problems. The tutorial also sheds light on future opportunities for using the strong analytical tool of coalitional games in a number of applications. In a nutshell, this article fills a void in existing communications literature, by providing a novel tutorial on applying coalitional game theory in communication networks through comprehensive theory and technical details as well as through practical examples drawn from both game theory and communication application.     

基于博弈论的认知无线电网络数据伪造对抗研究

博弈论是认知无线电技术的重要分析工具。数据伪造攻击是认知无线电网络中物理层面临的一种安全威胁,在这种攻击中,攻击者向其他次用户发送虚假的主用户感知数据,进而干扰合法次用户利用空闲的频谱。结合军用认知无线电网络的应用背景,利用信号博弈理论对数据伪造攻击进行建模,建立博弈模型并最终得到了均衡的条件。最后对实验结果进行分析,验证了模型的有效性。     

Dynamic computation offloading in time-varying environment forultra-dense networks: a stochastic game approach

To meet the demands of large-scale user access with computation-intensive and delay-sensitive applications, combining ultra-dense networks (UDNs) and mobile edge computing (MEC)are considered as important solutions. In the MEC enabled UDNs, one of the most important issues is computation offloading. Although a number of work have been done toward this issue, the problem of dynamic computation offloading in time-varying environment, especially the dynamic computation offloading problem for multi-user, has not been fully considered. Therefore, in order to fill this gap, the dynamic computation offloading problem in time-varying environment for multi-user is considered in this paper. By considering the dynamic changes of channel state and users queue state, the dynamic computation offloading problem for multi-user is formulated as a stochastic game, which aims to optimize the delay and packet loss rate of users. To find the optimal solution of the formulated optimization problem, Nash Q-learning (NQLN) algorithm is proposed which can be quickly converged to a Nash equilibrium solution. Finally, extensive simulation results are presented to demonstrate the superiority of NQLN algorithm. It is shown that NQLN algorithm has better optimization performance than the benchmark schemes.     

Hybrid protection algorithms based on game theory in multi-domain optical networks

With the network size increasing, the optical backbone is divided into multiple domains and each domain has its own network operator and management policy. At the same time, the failures in optical network may lead to a huge data loss since each wavelength carries a lot of traffic. Therefore, the survivability in multi-domain optical network is very important. However, existing survivable algorithms can achieve only the unilateral optimization for profit of either users or network operators. Then, they cannot well find the double-win optimal solution with considering economic factors for both users and network operators. Thus, in this paper we develop the multi-domain network model with involving multiple Quality of Service (QoS) parameters. After presenting the link evaluation approach based on fuzzy mathematics, we propose the game model to find the optimal solution to maximize the user’s utility, the network operator’s utility, and the joint utility of user and network operator. Since the problem of finding double-win optimal solution is NP-complete, we propose two new hybrid protection algorithms, Intra-domain Sub-path Protection (ISP) algorithm and Inter-domain End-to-end Protection (IEP) algorithm. In ISP and IEP, the hybrid protection means that the intelligent algorithm based on Bacterial Colony Optimization (BCO) and the heuristic algorithm are used to solve the survivability in intra-domain routing and inter-domain routing, respectively. Simulation results show that ISP and IEP have the similar comprehensive utility. In addition, ISP has better resource utilization efficiency, lower blocking probability, and higher network operator’s utility, while IEP has better user’s utility.     

Detection of evoked potentials with the use of the stochastic filtering theory

For detecting evoked potentials (EPs) in electroencephalogram (EEG) signals, a mathematical model of EEG without EP is constructed and equations of stochastic filtering are synthesized. From the analysis of updating sequences, an EP detection criterion is formulated. An EP detection algorithm is developed and studied, and its efficiency is confirmed by means of simulation.     

Repeated game theory as a framework for algorithm development in communication networks

This article presents a tutorial on how to use repeated game theory as a framework for algorithm development in communication networks. The article starts by introducing the basis of one‐stage games and how the outcome of such games can be predicted, through iterative elimination and Nash equilibrium. In communication networks, however, not all problems can be modeled using one‐stage games. Some problems can be better modeled through multi‐stage games, as many problems in communication networks consist of several iterations or decisions that need to be made over time. Of all the multi‐stage games, the infinite‐horizon repeated games were chosen to be the focus in this tutorial, because optimal equilibrium settings can be achieved, contrarily to the suboptimal equilibria achieved in other types of game. With the theoretical concepts introduced, it is then shown how the developed game theoretical model, and devised equilibrium, can be used as a basis for the behavior of an algorithm, which is supposed to solve a particular problem and will be running at specific network devices. Copyright © 2015 John Wiley & Sons, Ltd.     

认知无线网络中一种非合作博弈功率控制算法

针对现有的功率控制算法中存在的干扰问题和功率消耗过大问题,设计出一种新的效用函数,并根据此效用函数提出了一个基于非合作博弈的新的功率控制算法。首先,在效用函数中分别为信干噪比和功率设定了不同的代价因子,并将信道状态概念引入到代价因子里面,使其能够更加合理地控制用户,避免用户过度增加发射功率,同时减小了用户间的干扰;其次,证明了该算法纳什均衡的存在性和唯一性;最后,给出了所提算法的流程图。仿真结果表明,与Nash算法相比,在保证非授权用户服务质量( QoS)前提下,该算法功率消耗明显降低,并且具有较好的抗背景噪声性能;与K-G( Koskie-Gajic)算法相比,该算法保证了所有的用户的信干噪比满足上下限阈值要求,并且提高了系统容量。     

基于议价博弈论的无线协作中继网络性能改进算法

针对自私性无线协作中继(CR)网络中的放大再中继(AF)和解码再中继(DF)协议,分别给出 公平且有效率的协作中继功率分配方案。两种方案虽然具体研究内容有差别,但有着共同 的研究策略。首先,将节点间的协作功率选择问题建模为纳什议价博弈问题(NBP);然后, 通过求取其纳什议价解(NBS)获得协作节点的共赢策略;最后,针对AF和DF协议分别给出计 算机仿真。仿真结果表明,所提出协作中继性能改进算法的效率性体现在所有协作节点在AF 和DF协议中均获得信号接收质量的提高,其公平性则体现在任意节点为其协作伙伴所贡献的 转发功率大小仅取决于对方为其带来的性能增益大小。     

On the use of fractional Brownian motion in the theory ofconnectionless networks

An abstract model for aggregated connectionless traffic, based on the fractional Brownian motion, is presented. Insight into the parameters is obtained by relating the model to an equivalent burst model. Results on a corresponding storage process are presented. The buffer occupancy distribution is approximated by a Weibull distribution. The model is compared with publicly available samples of real Ethernet traffic. The degree of the short-term predictability of the traffic model is studied through an exact formula for the conditional variance of a future value given the past. The applicability and interpretation of the self-similar model are discussed extensively, and the notion of ideal free traffic is introduced     

A stochastic game framework for joint frequency and power allocation in dynamic decentralized cognitive radio networks

Cognitive radio networks (CRNs) have been recognized as a promising solution to improve the radio spectrum utilization. This article investigates a novel issue of joint frequency and power allocation in decentralized CRNs with dynamic or time-varying spectrum resources. We firstly model the interactions between decentralized cognitive radio links as a stochastic game and then proposed a strategy learning algorithm which effectively integrates multi-agent frequency strategy learning and power pricing. The convergence of the proposed algorithm to Nash equilibrium is proofed theoretically. Simulation results demonstrate that the throughput performance of the proposed algorithm is very close to that of the centralized optimal learning algorithm, while the proposed algorithm could be implemented distributively and reduce information exchanges significantly.     

Toward an integrated dynamic defense system for strategic detecting attacks in cloud networks using stochastic game

Telecommunication Systems - In a complex network as a cloud computing environment, security is becoming increasingly based on deception techniques. To date, the static nature of cyber networks...     

基于非合作博弈的OFDMA无线多跳中继网络上行链路资源分配算法

研究了基于OFDMA多址技术的无线多跳中继网络上行链路资源分配问题。首先,在最大发射功率等约束条件下,建立了多小区OFDMA无线多跳中继网络上行链路的资源分配优化模型。将非合作博弈论和定价机制引入后,该优化问题可转化为在每个子信道上独立地进行功率分配。基于非合作博弈的功率分配模型中的纳什均衡点的存在性和唯一性得到了证明,并给出了具体的分布式求解算法。仿真结果表明,所提算法能在大幅减少系统总发射功率的情况下,有效地提升系统吞吐量,达到较高的能效比。     

The theory of functionals of stochastic backscattered fields

The theory of wave scattering by anisotropic statistically rough surfaces, which is an important part of statistical radiophysics, is considered. A new analytic method is developed and generalized for solving problems of radar imaging. The method involves analytic determination of the functionals of stochastic backscattered fields and can be applied to solve a wide class of physical problems with allowance for the finite width of an antenna’s pattern. The unified approach based on this method is used to analyze the generalized frequency response of a scattering radio channel, a generalized correlator of scattered fields, spatial correlation functions of stochastic backscattered fields, frequency coherence functions of stochastic backscattered fields, the coherence band of a spatial-temporal scattering radar channel, the kernel of the generalized uncertainty function, and the measure of noise immunity characterizing radar probing of the Earth’s surface or extended targets. The introduced frequency coherence functions are applied for thorough and consistent study of techniques for measuring the characteristics of a rough surface, aircraft altitude, and distortions observed when radar signals are scattered by statistically rough, including fractal, surfaces. To exemplify urgent applications, radiophysical synthesis of detailed digital reference radar terrain maps and microwave radar images that was proposed earlier is considered and improved with the use of the theory of fractals.     

Resource allocation scheme for orthogonal frequency division multiple access networks based on cooperative game theory

Cooperative game theory can be applied to orthogonal frequency division multiple access (OFDMA) networks for fair resource allocation. In this work, we consider a comprehensive cross‐layer framework including physical and medium access control layer requirements. We apply two cooperative games, nontransferable utility (NTU) game and transferable utility (TU) game, to provide fairness in OFDMA networks. In NTU game, fairness is achieved by defining appropriate objective function, whereas in TU game, fairness is provided by forming the appropriate network structure. For NTU game, we analyze the Nash bargaining solution as a solution of NTU game taking into account channel state information and queue state information. In a TU game, we show that coalition among subcarriers to jointly provide rate requirements leads to better performance in terms of power consumption. The subcarrier's payoff is determined according to the amount of payoff which that subcarrier brings to the coalition by its participation. We show that although NTU and TU games are modeled as rate adaptive and margin adaptive problems, respectively, both solutions provide a fair distribution of resources with minimum fairness index of 0.8. Copyright © 2012 John Wiley & Sons, Ltd.     

A hybrid,game theory based,and distributed clustering protocol for wireless sensor networks

Clustering has been well known as an effective way to reduce energy dissipation and prolong network lifetime in wireless sensor networks. Recently, game theory has been used to model clustering problem. Each node is modeled as a player which can selfishly choose its own strategies to be a cluster head (CH) or not. And by playing a localized clustering game, it gets an equilibrium probability to be a CH that makes its payoff keep equilibrium. In this paper, based on game theory, we present a clustering protocol named Hybrid, Game Theory based and Distributed clustering. In our protocol, we specifically define the payoff for each node when choosing different strategies, where both node degree and distance to base station are considered. Under this definition, each node gets its equilibrium probability by playing the game. And it decides whether to be a CH based on this equilibrium probability that can achieve a good trade-off between minimizing energy dissipation and providing the required services effectively. Moreover, an iterative algorithm is proposed to select the final CHs from the potential CHs according to a hybrid of residual energy and the number of neighboring potential CHs. Our iterative algorithm can balance the energy consumption among nodes and avoid the case that more than one CH occurs in a close proximity. And we prove it terminates in finite iterations. Simulation results show that our protocol outperforms LEACH, CROSS and LGCA in terms of network lifetime.     

Dynamic subcarrier and power allocation based on cooperative game theory in symmetric cooperative OFDMA networks

In order to improve the efficiency and fairness of radio resource utilization,a scheme of dynamic cooperative subcarrier and power allocation based on Nash bargaining solution(NBS-DCSPA) is proposed in the uplink of a three-node symmetric cooperative orthogonal frequency division multiple access(OFDMA) system.In the proposed NBS-DCSPA scheme,resource allocation problem is formulated as a two-person subcarrier and power allocation bargaining game(SPABG) to maximize the system utility,under the constraints of each user’s maximal power and minimal rate,while considering the fairness between the two users.Firstly,the equivalent direct channel gain of the relay link is introduced to decide the transmission mode of each subcarrier.Then,all subcarriers can be dynamically allocated to the two users in terms of their selected transmission mode.After that,the adaptive power allocation scheme combined with dynamic subcarrier allocation is optimized according to NBS.Finally,computer simulation is conducted to show the efficiency and fairness performance of the proposed NBS-DCSPA scheme.     

Optimal resource allocation scheme for cognitive radio networks with relay selection based on game theory

In this paper,we present a non-transferable utility coalition graph game(NTU-CGG) based resource allocation scheme with relay selection for a downlink orthogonal frequency division multiplexing(OFDMA) based cognitive radio networks to maximize both system throughput and system fairness.In this algorithm,with the assistance of others SUs,SUs with less available channels to improve their throughput and fairness by forming a directed tree graph according to spectrum availability and traffic demands of SUs.So this scheme can effectively exploit both space and frequency diversity of the system.Performance results show that,NTU-CGG significantly improves system fairness level while not reducing the throughput comparing with other existing algorithms.     

A game theory approach to constrained minimax state estimation

This paper presents a game theory approach to the constrained state estimation of linear discrete time dynamic systems. In the application of state estimators, there is often known model or signal information that is either ignored or dealt with heuristically. For example, constraints on the state values (which may be based on physical considerations) are often neglected because they do not easily fit into the structure of the state estimator. This paper develops a method for incorporating state equality constraints into a minimax state estimator. The algorithm is demonstrated on a simple vehicle tracking simulation.     

On measures of vulnerability of interconnection networks

With the advent of distributed and multiple processing systems, the study of interconnection networks has developed into a field of its own. In most cases, the performance measures used to characterize the reliability of such networks have been primitive.It is our purpose, in this brief paper, to survey the many available measures of the vulnerability of interconnection networks. The most widely known is classical connectivity; however, measures more recently introduced in the graph theory literature are probably a better practical metric of reliability. Our objective is to make these measures more widely known, and to spur the development of good algorithms to calculate them in practical instances.