Game theoretic approaches to cooperation in wireless networks

GAME THEORETIC APPROACHES TO COOPERATION IN WIRELESS NETWORKS AI XIN NATIONAL UNIVERSITY OF SINGAPORE 2010 GAME THEORETIC APPROACHES TO COOPERATION IN WIRELESS NETWORKS AI XIN (B.Eng, Xi’dian University) A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING NATIONAL UNIVERSITY OF SINGAPORE 2010 Acknowledgements I would like to give my heartfelt thanks to my supervisor, Dr. Vikram Srinivasan and Prof. Tham Chen Khong, for their guidance, support and encouragement throughout my study. I would also like to thank my parents and my husband. They always give me their unconditional love and support. Last, but not least, I want to thank my friends and colleagues in CNDS lab for their kind assistance and suggestions on research and other issues. The interesting discussion during lunch and coffee time is so enjoyable. Contents Acknowledgements ii Summary vi List of Figures viii List of Tables x List of symbols xi Abbreviations xiii Introduction 1.1 Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 1.5 Thesis overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Game Theory 2.1 Strategic Game Model and Nash Equilibrium 20 . . . . . . . . . . . . . 21 2.2 Optimality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 2.3 Complexity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 2.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 Coverage Game in Wireless Sensor Networks 33 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 3.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 3.3 Problem Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 3.4 Algorithm Description . . . . . . . . . . . . . . . . . . . . . . . . . . 44 3.5 Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.6 Simulation and Discussion . . . . . . . . . . . . . . . . . . . . . . . . 64 3.7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 WiFi Sharing Game in Wireless Community Networks 77 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 4.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 4.3 System Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 4.4 System Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 4.5 User and System Behavior . . . . . . . . . . . . . . . . . . . . . . . . 97 4.6 Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 4.7 Experiments with Real Data . . . . . . . . . . . . . . . . . . . . . . . 105 4.8 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 iv WiFi Sharing Game with Priority Pricing 115 5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 5.2 System Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 5.3 System Modelling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 5.4 User Behaviors and System Convergence . . . . . . . . . . . . . . . . 133 5.5 Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138 5.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143 Conclusion and Future Work 6.1 145 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 Bibliography 150 List of Publications 163 v Summary In this thesis, we use game theoretical approaches to study several cooperation issues in wireless networks. Firstly, we investigate the coverage problem in wireless sensor networks. We assume that nodes are randomly scattered in a field and the goal is to partition these nodes into K sets. At any given time, nodes belonging to only one of these sets actively sense the field. A key challenge is to achieve this partition in a distributed manner with purely local information and yet provide near optimal coverage. We formulate this coverage problem as a coverage game and prove that the optimal solution is a pure Nash equilibrium. We then design synchronous and asynchronous algorithms, which converge to the pure Nash equilibrium. Moreover, we analyze the optimality and complexity of the pure Nash equilibrium in the coverage game, and validate the theoretical results through extensive simulations. Next, we investigate the WiFi sharing problem in wireless community networks (WCNs). WCNs, where users share wireless bandwidth, has attracted tremendous interest from academia and industry. Companies such as FON have been successful in attracting large communities of users. However, solutions such as FON either require users to buy specialized FON routers or implement firmware modifications to existing routers. We propose a solution which does not require such sophisticated hardware and only requires users to install a client software in their PCs. While this solution appears simple, it raises several issues of incentivizing users to share their bandwidth and also issues of preventing users from cheating behaviors which give them an unfair advantage. By making simple but plausible assumptions about user behavior, we show via analysis and extensive simulations that the system converges to a Pareto Optimal Nash equilibrium. We further validate our system model, by running trace-driven simulations on real world data. Finally, we study the fairness problem in credit-based WiFi sharing community. Under credit system, users obtain no more service than they share. Some users, located in unpopular areas accumulate few credits and are unable to access other networks when they roam. Meanwhile, other users located in hot-spots, accumulate extra credits, which they have no way to spend. A priority pricing based WiFi sharing solution (“PP-WiSh”), which is also a pure client software solution, is provided to solve this problem. PP-WiSh allows users located in popular areas to spend the excess credits they accumulate for better service and also helps users located in unpopular areas to accumulate extra credits which they can utilize when roaming. We formulate the priority pricing WiFi sharing problem as a distributed optimization problem and theoretically analyze the equilibrium pricing solution of users in the community. Moreover, we prove that all the users with rational and intelligent behaviors will converge to this equilibrium and we demonstrate the convergence and performance improvements through experiments using real world trace data. vii we did some experiments using the real world WiFi trace data, however, this data only addresses the users’ network access patterns. Regarding the other more complex user behaviors, e.g. cooperation and competition, cheating and punishment, etc., for now we only analyze them in a theoretical way, and make some simply assumptions in our experiment. The future researchers can consider to the experiments in a real WiFi sharing community networks (e.g. FON), so that they can have the real world users’ cooperation and competition behaviors in WiFi sharing, and thus further improve our WiFi sharing design to improve the whole community performance. 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Available: http: //www.omnetpp.org/ 162 List of Publications Journals • Xin Ai, Vikram Srinivasan, Chen-Khong Tham,Optimality and Complexity of Pure Nash equilibria in the Coverage Game, IEEE JSAC (Journal on Selected Areas in Communications), Special Issue on Game Theory in Communication Systems, Vol. 26, No. 7, Sep. 2008 • Xin Ai, Vikram Srinivasan, Chen-Khong Tham, Fair-WiSh: A Simple, Robust, Fair and Credit Based Wi-Fi Community Network, submitted to IEEE Transactions on Mobile Computing Conferences • Xin Ai, Vikram Srinivasan, Chen-Khong Tham, Wi-Sh: A Simple, Robust and Credit Based Wi-Fi Community Network, in Poceedings of IEEE INFOCOM 2009 • Xin Ai, Vikram Srinivasan, Chen-Khong Tham, DRACo: Distributed, Robust an Asynchronous Coverage in Wireless Sensor Networks, in Proceedings of IEEE SECON 2007 • Xin Ai, Vikram Srinivasan, Chen-Khong Tham,Coverage Game in Wireless Sensor Networks, in proceedings of IEEE ICON 2006 164 [...]... the local information and interactions with the neighboring nodes Therefore, game theory, a study of interactions between autonomous agents, is applied in the wireless networks to analyze the interactive decision-making processes of the distributed wireless nodes, and design effective schemes to incentivize the cooperation among wireless nodes and achieve the network wide objectives A lot of interests... 11, 12, 13, 14] In the power control game, the players are the cellular telephone users in the cell Each player’s action is to choose the power level The player’s utility is modeled as an increasing function of SINR and a decreasing function of power By increasing power, the user can increase her SINR, however, it may require others to increase their own power to maintain the desired SINR Thus, once... convergence problem we studied in the wireless networks 13 1.3.3 Incentivizing Cooperation Previously many researchers studied the cooperation incentivizing mechanisms in ad hoc networks and obtained a lot of interesting results, however,until now few results have been turned into the commodities, or have the real impacts on our way of using wireless network today The possible reasons may come from both... Figure 1.1: The inefficient result caused by distributed behaviors the conflicts in decision making, even if all the nodes in the network share the same objective We use a simple coverage problem in wireless sensor networks (WSNs) to illustrate this point In WSNs, a large number of energy constrained sensor nodes are randomly deployed in a target field to monitor some activities in this area Since all the... quite interesting to study the interactions between the distributed nodes in the network using game theory In addition, we would like to mention that with the technology growth, the selfish behaviors in the network is gradually decreasing, since many human roles now can be replaced by the intelligent devices, e.g., sensor nodes, robot, etc These intelligent devices can be totally controlled by the engineers... assumed to be continuous and nondecreasing in the edge congestion, the total latency of the routes chosen by unregulated selfish network users is no more than twice of the total latency incurred by optimally routing 6 1.2.3 Cooperation in Ad Hoc Networks In ad hoc networks, each node acts not only as source/destination for traffic, but also as a router to forward packets for its neighbors What are the incentives... them, accessing to the internet are much more interesting In this case, users are looking for multipurpose networking platforms in which cost is an issue, Internet is a must and high bandwidth is preferred So recently a more practical “opportunistic ad hoc networking” is provided in [43], known as “Mesh Networks Mesh networks are built on a mix of fixed access points (e.g., WiFi access points) and mobile... interest in adopting it Recently the single hop mesh network, 14 so-called wireless community networks (WCNs), have already shown great potential in the wireless market WCNs are built mainly on 802.11 technology (WiFi) and aim at providing Internet access to a community of users that can share the same Internet access link Some examples of this are Seattle Wireless [44], ChampaignUrbana Community Wireless. .. very challenging task to execute it well Second scenario is the “engineering” scenario, where all the nodes in the system are programmed by the engineers, thus the engineers can choose whatever utility function they desire The challenge in this scenario lies in explaining why a particular utility function has been chosen and why game theory is being employed at all In addition, although game theory... configurations they like to benefit themselves the most Therefore, the cooperation incentivizing mechanism is indeed required in WCNs Moreover, this scheme should address the different features of WCNs, compared with the one in ad hoc networks For example, in WCNs there is only one intermediate relaying node (the WLAN AP), which is also connected to a fixed power supply and to the Internet; and in WCNs the functions . GAME THEORETIC APPROACHES TO COOPERATION IN WIRELESS NETWORKS AI XIN NATIONAL UNIVERSITY OF SINGAPORE 2010 GAME THEORETIC APPROACHES TO COOPERATION IN WIRELESS NETWORKS AI XIN (B.Eng,. 163 v Summary In this thesis, we use game theoretical approaches to study several coope ration issues in wireless networks. Firstly, we investigate the coverage problem in wireless sensor networks. . local information and interactions with the neighboring nodes. Therefore, game theory, a study of interactions between autonomous agents, is applied in the wireless networks to analyze the interactive