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2000, IEEE Signal Processing Magazine
Game theoretical techniques have recently become prevalent in many engineering applications, notably in communications. With the emergence of cooperation as a new communication paradigm, and the need for self-organizing, decentralized, and autonomic networks, it has become imperative to seek suitable game theoretical tools that allow to analyze and study the behavior and interactions of the nodes in future communication networks. In this context, this tutorial introduces the concepts of cooperative game theory, namely coalitional games, and their potential applications in communication and wireless networks. For this purpose, we classify coalitional games into three categories: Canonical coalitional games, coalition formation games, and coalitional graph games. This new classification represents an application-oriented approach for understanding and analyzing coalitional games. For each class of coalitional games, we present the fundamental components, introduce the key properties, mathematical techniques, and solution concepts, and describe the methodologies for applying these games in several applications drawn from the state-of-the-art research in communications. In a nutshell, this article constitutes a unified treatment of coalitional game theory tailored to the demands of communications and network engineers.
Ieee Signal Processing Magazine Special Issue on Game Theory For Signal Processing and Communication, 2009
Game theoretical techniques have recently become prevalent in many engineering applications, notably in communications. With the emergence of cooperation as a new communication paradigm, and the need for self-organizing, decentralized, and autonomic networks, it has become imperative to seek suitable game theoretical tools that allow to analyze and study the behavior and interactions of the nodes in future communication networks. In this context, this tutorial introduces the concepts of cooperative game theory, namely coalitional games, and their potential applications in communication and wireless networks. For this purpose, we classify coalitional games into three categories: Canonical coalitional games, coalition formation games, and coalitional graph games. This new classification represents an application-oriented approach for understanding and analyzing coalitional games. For each class of coalitional games, we present the fundamental components, introduce the key properties, mathematical techniques, and solution concepts, and describe the methodologies for applying these games in several applications drawn from the state-of-the-art research in communications. In a nutshell, this article constitutes a unified treatment of coalitional game theory tailored to the demands of communications and network engineers.
IEEE Wireless Communications, 2000
Information Theory Proceedings …, 2011
Cooperation between rational users has emerged as a new networking paradigm to improve the performance of wireless networks. In this paper, transmitter cooperation between wireless nodes in a Gaussian multiple access channel is studied under the framework of coalitional game theory. The stability of the grand coalition, the coalition of all users, is studied by modeling the game in partition form, in contrast to previous approaches using characteristic form games, in scenarios with infinite and finite cooperation capacity between transmitters. In both cases, irrespective of the channel gains, the grand coalition is shown to be the sum rate optimal and stable, in the sense that users do not have any incentive to leave the coalition.
A wireless relay network (WRN) has recently emerged as an effective way to increase communication capacity and extend a coverage area with a low cost. In the WRN, multiple service providers (SPs) can cooperate to share their resources (e.g., relay nodes and spectrum), to achieve higher utility in terms of revenue. Such cooperation can improve the capacity of the WRN, and thus throughput for terminal devices (TDs). However, this cooperation can be realized only if fair allocation of aggregated utility, which is the sum of the utility of all the cooperative SPs, can be achieved. In this paper, we investigate the WRN consisting of SPs at the upper layer and TDs at the lower layer and present a game theoretic framework to address the cooperation decision making problem in the WRN. Specifically, the cooperation of SPs is modeled as an overlapping coalition formation game, in which SPs should form a stable coalitional structure and obtain a fair share of the aggregated utility. We also study the problem of allocating aggregated utility based on the concept of Shapley value, which stabilizes the cooperation of SPs in the WRN. The cooperation of TDs is modeled as a network formation game, in which TDs establish links among each other to form a stable network structure. Numerical results demonstrate that the proposed distributed algorithm obtains the aggregated utility approximating the optimal solutions and achieves good convergence speed.
Game theory is a set of tools developed to model interactions between agents with conflicting interests . It is a field of applied mathematics that defines and evaluates interactive decision situations. It provides analytical tools to predict the outcome of complicated interactions between rational entities, where rationality demands strict adherence to a strategy based on observed or measured results . Originally developed to model problems in the field of economics, game theory has recently been applied to network problems, in most cases to solve the resource allocation problems in a competitive environment. The reason that game theory is an adapted choice for studying cooperative communications is various. Nodes in the network are independent agents, making decisions only for their own interests. Game theory provides us sufficient theoretical tools to analyze the network users' behaviors and actions. Game theory, also primarily deals with distributed optimization, which often requires local information only. Thus it enables us to design distributed algorithms. . This article surveys the literature on game theory as they apply to wireless networks. First, a brief overview of classifications of games, important definitions used in games (Nash Equilibrium, Pareto efficiency, Pure, Mixed and Fully mixed strategies) and game models are presented. Then, we identified five areas of application of game theory in wireless networks; therefore, we discuss related work to game theory in communication networks, cognitive radio networks, wireless sensor networks, resource allocation and power control. Finally, we discuss the limitations of the application of game theory in wireless networks.
Abstract Cooperation between nodes sharing a wireless channel is becoming increasingly necessary to achieve performance goals in a wireless network. The problem of determining the feasibility and stability of cooperation between rational nodes in a wireless network is of great importance in understanding cooperative behavior. This paper addresses the stability of the grand coalition of transmitters signaling over a multiple access channel using the framework of cooperative game theory.
Telecommunication Systems, 2016
In this paper we consider a wireless contextualization of the local routing protocol on scale-free networks embedded in a plane and analyze on the one hand how cooperation affects network efficiency, and on the other hand the stability of cooperation structures. Cooperation is interpreted on k-cliques as local exchange of topological information between cooperating agents. Cooperative activity of nodes in the proposed model changes the routing strategy at the level of the coalition group and consequently influences the entire routing process on the network. We show that the proposed cooperation model enhances the network performance in the sense of reduced passage time and jamming. Payoff of a certain node is defined based on its energy consumption during the routing process. We show that if the payoff of the nodes is the energy saving compared to the all-singleton case, basically coalitions are not stable, since increased activity within coalition increases costs. We introduce coalitional load balancing and net reward to enhance coalitional stability and thus the more efficient operation of the network. As in the proposed model cooperation strongly affects routing dynamics of the network, externalities will arise and the game is defined in a partition function form.
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 ...
Game theory has been recently introduced in wireless network design as a powerful modeling and analysing tool for competitive and completely distributed environments. It is a well-suited to describe mutual conflicting situations between multiple devices which attempt to communicate through a shared medium. In order to demonstrate suitability of a game-theoretic approach for optimisation of wireless networks, we first present the main idea, concepts and components of game theory. We then provide mapping of principles between the areas of game theory and wireless networks, and present some applications of game theory in wireless networks. We develop and implement a model for transmit power control optimisation in a wireless relay network consisting of wireless sensor network coordinator nodes using the category of potential games. In the game, we determine the Pareto efficient Nash equilibrium, which represents the optimal stable operating point of the network.
IEEE Transactions on Computational Intelligence and AI in Games, 2011
Although establishing cooperation in a wireless network is a dynamic process, most game theoretic coalition formation models proposed in the literature are static. We analyze a dynamic coalition formation game based on a Markovian model for the spectrum sharing problem in an interference channel. Our model is dynamic in the sense that distributed transmitter-receiver pairs, with partial channel knowledge, reach stable coalition structures (CSs) through a time-evolving sequence of steps. Depending on an interference environment, we show that the game process either converges to the absorbing state of the grand coalition or to the absorbing state of internal and external stability. We also show that, due to myopic links, it is possible that the core of the game is non-empty, but links cannot form the grand coalition to utilize the core rate allocations. We then formulate a condition for the formation of the stable grand coalition. Using simulation we show that coalition formation yields significant gains in terms of average rates per link for different network sizes. We also show average maximum coalition sizes for different distances between the transmitters and their own receivers. Finally, we analyze the mean and variance of the time for the game to reach the stable coalition structures.
Game theory is a field of applied mathematics that developed in the context of economics and focuses on the strategic behavior of rational agents. Strategic behavior, occurs when the utility of each agent not only affected by his own choice of strategy but also depends on the strategy chosen by other actors. Type of game can be classified as a zero-sum games, nonzero-sum games, cooperative games and non-cooperative games. Game theory has many applications in various scientific fields such as political science, economics and business, biology, philosophy, computer science and logic, etc and have been recognized as an important tool in studying, modeling and interaction analysis. At the time, game theory has found many applications in the computer networks. These applications are redefined as a game framework in which players are trying to optimize an objective function. Those strategies that direct the network to an optimal Nash equilibrium are considered as efficient strategies for network games. In this paper, we offer an overview over applications of game theory in computer networks and arrange them inside different groups.
2009
Coalitional network games are real-valued functions defined on a set of play-ers (the society) organized into a network and a coalition structure. The network specifies the nature of the relationship each individual has with the other individ-uals and the coalition structure specifies a collection of groups among the society. Coalitional network games model situations where the total productive value of a network among players depends on the players ’ group membership. These games thus capture the public good aspect of bilateral cooperation, i.e., network games with externalities. After studying the specific structure of coalitional networks, we propose an allocation rule under the perspective that players can alter the coalitional network structure. This means that the value of all potential alternative coalitional networks can and should influence the allocation of value among players in any given coalitional network structure. JEL classification: A14, C70.
2008 3rd International Symposium on Communications, Control and Signal Processing, 2008
We develop a unifying analytical and optimizationbased framework for the design, operation and performance evaluation of networks of dynamic autonomous agents. The fundamental view is that agents in such a network are dynamic entities that collaborate because via collaboration they can accomplish objectives and goals much better than working alone, or even accomplish objectives that they cannot achieve alone at all. Yet the benefits derived from such collaboration require some costs (e.g. communications), or equivalently, the collaboration is subject to constraints. Understanding and quantifying this tradeoff between the benefits vs the costs of collaboration, leads to new methods that can be used to analyze, design and control/operate networks of agents. Although the inspiration for the framework comes from social and economic networks, the fundamental ideas and in particular the methodology of dynamic constrained coalitional games (DCCG) can unify many concepts and algorithms for networks in various areas: social networks, communication networks, sensor networks, economic networks, biological networks, physics networks. We then analyze a specific instance of such tradeoffs arising in the design of security aware network protocols. We extend network utility maximization (NUM) so as to encompass security metrics such as "trust". The trust values assigned to nodes are based on interaction history and community-based monitoring. The effect of these trust values on the resulting protocols is that in routing and media access scheduling node trustworthiness is automatically considered and used. We develop a distributed algorithm for the joint physical-MAC-routing protocol design. Our extension to NUM with security concerns leads to resilient networks.
2005
We discuss some new algorithmic and complexity issues in coalitional and dynamic/evolutionary games, related to the understanding of modern selfish and Complex networks. In particular: (a) We examine the achievement of equilibria via natural distributed and greedy approaches in networks. (b) We present a model of a coalitional game in order to capture the anarchy cost and complexity of constructing equilibria in such situations. (c) We propose a stochastic approach to some kinds of local interactions in networks, that can be viewed also as extensions of the classical evolutionary game theoretic setting.
Computer Networks, 2010
While the Quality of Service (QoS) offered to users may be enhanced through innovative protocols and new technologies, future trends should take into account the efficiency of resource allocation and network/terminal cooperation as well. Game theory techniques have widely been applied to various engineering design problems in which the action of one component has impact on (and perhaps conflicts with) that of any other component. Therefore, game formulations are used, and a stable solution for the players is obtained through the concept of equilibrium. This survey collects applications of game theory in wireless networking and presents them in a layered perspective, emphasizing on which fields game theory could be effectively applied. To this end, several games are modeled and their key features are exposed.
2019
The most important challenge in Wireless Sensor Networks (WSNs) is the energy constraint. Numerous solutions have been proposed to alleviate this problem, the most efficient of which is to cluster the sensor nodes. Although clustering in the realm of WSNs has widely been explored by researchers, a few effective mechanisms in grouping the nodes, including coalitional games, need more attention and research. This motivated us to employ cooperative games and to propose a Coalitional Game-Theoretic Clustering (CGTC) algorithm for WSNs. Basically two kinds of coalitions are formed regarding the location of sensor nodes, where local parameters play an important role in forming coalitions. Moreover, the Shapley value is adopted as the solution concept. The result of simulation confirms the effectiveness of CGTC in terms of energy efficiency.
IEEE Transactions on Wireless Communications, 2000
In this paper, we study the problem of cooperative interference management in an OFDMA twotier small cell network. In particular, we propose a novel approach for allowing the small cells to cooperate, so as to optimize their sum-rate, while cooperatively satisfying their maximum transmit power constraints. Unlike existing work which assumes that only disjoint groups of cooperative small cells can emerge, we formulate the small cells' cooperation problem as a coalition formation game with overlapping coalitions. In this game, each small cell base station can choose to participate in one or more cooperative groups (or coalitions) simultaneously, so as to optimize the tradeoff between the benefits and costs associated with cooperation. We study the properties of the proposed overlapping coalition formation game and we show that it exhibits negative externalities due to interference. Then, we propose a novel decentralized algorithm that allows the small cell base stations to interact and self-organize into a stable overlapping coalitional structure. Simulation results show that the proposed algorithm results in a notable performance advantage in terms of the total system sum-rate, relative to the noncooperative case and the classical algorithms for coalitional games with non-overlapping coalitions.
2017
Game Theory (GT) has been used with excellent results to model and optimize the operation of a huge number of real-world systems, including in communications and networking. Using a tutorial style, this paper surveys and updates the literature contributions that have applied a diverse set of theoretical games to solve a variety of challenging problems, namely in wireless data communication networks. During our literature discussion, the games are initially divided into three groups: classical, evolutionary, and incomplete information. Then, the classical games are further divided into three subgroups: non-cooperative, repeated, and cooperative. This paper reviews applications of games to develop adaptive algorithms and protocols for the efficient operation of some standardized uses cases at the edge of emerging heterogeneous networks. Finally, we highlight the important challenges, open issues, and future research directions where GT can bring beneficial outcomes to emerging wireles...
IEEE Journal on Selected Areas in Communications, 2008
Cooperation between rational users in wireless networks is studied using coalitional game theory. Using the rate achieved by a user as its utility, it is shown that the stable coalition structure, i.e., set of coalitions from which users have no incentives to defect, depends on the manner in which the rate gains are apportioned among the cooperating users. Specifically, the stability of the grand coalition (GC), i.e., the coalition of all users, is studied. Transmitter and receiver cooperation in an interference channel (IC) are studied as illustrative cooperative models to determine the stable coalitions for both flexible (transferable) and fixed (non-transferable) apportioning schemes. It is shown that the stable sum-rate optimal coalition when only receivers cooperate by jointly decoding (transferable) is the GC. The stability of the GC depends on the detector when receivers cooperate using linear multiuser detectors (non-transferable). Transmitter cooperation is studied assuming that all receivers cooperate perfectly and that users outside a coalition act as jammers. The stability of the GC is studied for both the case of perfectly cooperating transmitters (transferrable) and under a partial decode-and-forward strategy (non-transferable). In both cases, the stability is shown to depend on the channel gains and the transmitter jamming strengths.
Mobile Networks and Applications, 2011
Cooperation among wireless nodes has been recently proposed for improving the physical layer (PHY) security of wireless transmission in the presence of multiple eavesdroppers. While existing PHY security literature answered the question "what are the link-level secrecy rate gains from cooperation?", this paper attempts to answer the question of "how to achieve those gains in a practical decentralized wireless network and in the presence of a cost for information exchange?". For this purpose, we model the PHY security cooperation problem as a coalitional game with non-transferable utility and propose a distributed algorithm for coalition formation. Through the proposed algorithm, the wireless users can cooperate and self-organize into disjoint independent coalitions, while maximizing their secrecy rate taking into account the security costs during information exchange. We analyze the resulting coalitional structures for both decode-and-forward and amplify-and-forward cooperation and study how the users can adapt the network topology to environmental changes such as mobility. Through simulations, we assess the performance of the proposed algorithm and show that, by coalition formation using decode-and-forward, the average secrecy rate per user is increased of up to 25.3% and 24.4% (for a network with 45 users) relative to the non-cooperative and amplifyand-forward cases, respectively.
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