Title from PDF of title page (University of Missouri--Columbia, viewed on Feb 15, 2010). The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file. Dissertation advisor: Dr. X. H. Wang Vita. Includes bibliographical references.

 Surge in WLAN development leads to urgent demand for more efficient bandwidth allocation methods. The bandwidth resource becomes more and more scarce. As a consequence, it demands both revenue maximizing and cost efficient allocation methods. To develop this sort of allocation methods, a dilemma between the target of maximizing service quality (in terms of user revenue) and the target of cost efficient allocation must be resolved. In this thesis, two novel auction-based time-slotted WLAN bandwidth allocation models are established, namely the Combination of Single-slot Second-Price Sealed Auction (CSSA) and the Multi-slot Vickrey Auction versus Homogeneous Objects (MVAH). The two models propose a new approach to the solution of the dilemma: user revenue is formulated by not only its revenue gain or loss related to the access to the bandwidth resource, but also by a series of WLAN transmission factors, including Packet Collision Rate and Minimal Packet Transmission error rate. In the two models, wireless bandwidth is time-slotted and bandwidth users compete for the access to these time slots. Initially, each bandwidth user joins a bidding group which is represented by its bidder. There is only one bandwidth provider in the coverage area of the WLAN. After being assigned virtual credit budget, every bidder bids for arbitrary slot combination in each bidding trial or all slots in one bidding trial, according to the bidding rule of adopted allocation model. Non-cooperative game formulation is thereafter introduced to analyze the revenue of each bidder, revenue of the provider, and revenue of the whole allocation system. Specifically, each bidder’s revenue function is differentiated by its bid; the extreme points of this partial differential equation, i.e., the best bids for the bidder, are computed. The bidding strategy formula for each single bidder is derived from the game formulation under the bidder’s budget limit. Each bidder adjusts its bids to attain the optimal revenue obtained from the bidding strategy formula. The allocation pattern is therefore formed. By means of calculation of the all-bidder revenue to whole system revenue ratio, the system efficiency values for both allocation models are analyzed. Conclusions can be derived from the formula of system efficiency: 1) CSSA benefits about 1 percent higher system efficiency unit than MVAH when only average throughputs of user groups differ. And both models iii- gain optimal system efficiencies when bidder’s average throughput differs 65 times pairwise. 2) The larger the number of users connecting to each bidder, the lower the system efficiency. And CSSA model attains higher system efficiency than MVAH when user numbers of user groups differ more than 3.2 times pairwise. In accordance with the pursuit of maximum system efficiency, new WLANs satisfying both revenue maximizing and cost efficient allocation demands can be established. / published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy

This dissertation focuses on strategic behavior and database privacy. First, we look at strategic behavior as a tool for distributed computation. We blend the perspectives of game theory and mechanism design in proposals for distributed solutions to the classical set cover optimization problem. We endow agents with natural individual incentives, and we show that centrally broadcasting non-binding advice effectively guides the system to a near-optimal state while keeping the original incentive structure intact. We next turn to the database privacy setting, in which an analyst wishes to learn something from a database, but the individuals contributing the data want to protect their personal information. The notion of differential privacy allows us to do both by obscuring true answers to statistical queries with a small amount of noise. The ability to conduct a task differentially privately depends on whether the amount of noise required for privacy still permits statistical accuracy. We show that it is possible to give a satisfying tradeoff between privacy and accuracy for a computational problem called independent component analysis (ICA), which seeks to decompose an observed signal into its underlying independent source variables. We do this by releasing a perturbation of a compact representation of the observed data. This approach allows us to preserve individual privacy while releasing information that can be used to reconstruct the underlying relationship between the observed variables. In almost all of the differential privacy literature, the privacy requirement must be specified before looking at the data, and the noise added for privacy limits the statistical utility of the sanitized data. The third part of this dissertation ties together privacy and strategic behavior to answer the question of how to determine an appropriate level of privacy when data contributors prefer more privacy but an analyst prefers more accuracy. The proposed solution to this problem views privacy as a public good and uses market design techniques to collect these preferences and then privately select and enforce a socially efficient level of privacy.

published_or_final_version / abstract / Physics / Master / Master of Philosophy

No description available.

Automated devices enabled by wireless communications are deployed for a variety of purposes. As they become more ubiquitous, their interaction becomes increasingly important for coexistence when sharing a scarce resource, and for leveraging potential cooperation to achieve larger design goals. This thesis investigates the use of game theory as a tool for design and analysis of networked systems of automated devices in the areas of naval defence, wireless environmental monitoring through sensor networks, and cognitive radio wireless communications. In the first part, decentralized operation of naval platforms deploying electronic countermeasures against missile threats is studied. The problem is formulated as a stochastic game in which platforms independently plan and execute dynamic strategies to defeat threats in two situations: where coordination is impossible due to lack of communications, and where platforms hold different objectives but can coordinate, according to the military doctrine of Network Enabled Operations. The result is a flexible, robust model for missile deflection for advanced naval groups. Next, the problem of cooperative environmental monitoring and communication in energy-constrained wireless sensor networks is considered from a game-theoretic perspective. This leads to novel protocols in which sensors cooperatively trade off performance with energy consumption with low communication and complexity overhead. Two key results are an on-line adaptive learning algorithm for tracking the correlated equilibrium set of a slowly varying sensor deployment game, and an analysis of the equilibrium properties of threshold policies in a game with noisy, correlated measurements. Finally, the problem of dynamic spectrum access for systems of cognitive radios is considered. A game theoretic formulation leads to a scheme for competitive bandwidth allocation which respects radios' individual interests while enforcing fairness between users. An on-line adaptive learning scheme is again proposed for negotiating fair, equilibrium resource allocations, while dynamically adjusting to changing conditions.

We create pure strategy versions of Robert Axelrod's well known norms and metanorms games. To analyze the evolutionary behaviour of these games, we utilize replicator dynamics complemented with agent based model simulations. Our findings show that the only evolutionarily stable strategy in the norms game is one in which a player defects and is lenient. The metanorms game, however, has two evolutionarily stable strategies. The first is a repeat from the norms game, that is, a player defects and is always lenient. The other is one in which a player follows the norm and punishes those who are lenient and those who defect. We also introduce the concept of providing an incentive for players to play a certain strategy in our controlled norms game. This particular game has two evolutionarily stable strategies. In the first, a player follows the norm, while in the second, a player does not. We wish to transition the population of players from a state in which the majority of players initially do not follow the norm to one in which the majority of players do. During this transition, we look to minimize the total use of our incentive. We also utilize agent based model simulations to explore the effect of imposing simple network connections and heterogeneity onto a population of agents playing these games.

No description available.

No description available.

The author suggests using lessons from Game Theory to improve the negotiation process and to construct more fitting agreements upon the breakdown of the family unit in the cases of separation or divorce. Currently many settlement agreements are inappropriate for the parties for a variety of reasons, including not establishing the parties' true interests during the negotiations. Furthermore, an inappropriate agreement may not be reopened by the court, given strict procedural and jurisprudential requirements. Game Theory lessons promote communication, cooperation, and forgiveness without allowing either party to be manipulated. These elements, already found in Collaborative Law, favour incorporating the lessons from Game Theory into this negotiation process.