Cooperation in wireless networks with selfish users

In emerging self-organizing wireless networks, each device is controlled by a potentially selfish participant who can tamper with the networking protocols in his/her device. This behavior is dangerous as it can lead to inefficient global utilization and the collapse of service provisioning in the network. Motivating the participants to cooperate with each other becomes a key issue in such networks. The mathematical principles of game theory provide a flexible and powerful framework and tool set to study the behavior of rational selfish participants in strategic interaction. We apply game theory to analyze the performance of protocols wireless networks with selfish users and to design incentives for users to cooperate so that they are driven to operate at efficient equilibria.We provide a thorough survey on game theory applied in wireless networks and illustrate how to apply game theoretic tools to enhance cooperation via three specific case studies: routing in wireless ad-hoc networks, spectrum sharing in cognitive radio networks and incentive design in community-based social mobile networks.In the case study of routing problem in wireless ad-hoc networks, the goal is to find a reliable routing path. We investigate a pricing mechanism and proposed a polynomial-time construction that can generate a Nash equilibrium path in which no route participant has an incentive to cheat. We show that there is a critical price threshold beyond which an equilibrium path exists with high probability. We also illustrate that there exists an optimal price setting beyond the price threshold at which the source can maximize its utility. We evaluate the approach using simulations based on realistic wireless topologies. In the case study of spectrum sharing problem in cognitive radio networks, we consider in detail the specific case where two secondary users opportunistically access two channels on which each user has potentially different valuations. We formulate the problem as a non-cooperative simultaneous strategic game and identify the equilibria in this game. For cases where the resulting Nash equilibria are not efficient, we proposed a novel distributed coordinated channel access mechanism that can be implemented with low overhead. This mechanism is based on the Nash bargaining solution and can guarantee full utilization of the available spectrum resources. Resulting gains are quantified for this mechanism. We also consider the user truthfulness in exchanging channel valuation information. We show that truthfulness is not guaranteed in the bargaining process, so that there is a tradeoff between enforcing truthfulness and efficiency. In the case study of cooperation in community-based mobile social applications, we motivate the work through a personal safety application, where we point out a fundamental tension between users desire for preserving the privacy of their own data and their need for fine-grained information about others. We model the privacy-participation tradeoffs in this safety application as a non-cooperative game and design a tit-for-tat (TFT) mechanism to give users incentives to reveal their local information to the application. We propose an algorithm that yields a Pareto optimal Nash equilibrium. We show that this algorithm, which can be implemented in a distributed manner, guarantees polynomial time convergence.