Call number: LD2668 .T4 1986 F47 / Master of Science / Industrial and Manufacturing Systems Engineering

Management of water resources has become more complex in recent years as a result of changing attitudes towards sustainability and the attribution of greater attention to environmental issues, especially under a scenario of water scarcity risk introduced by climate changes and anthropogenic pressures. This thesis addresses the conflicts in optimizing multi-purpose hydropower operations under an environment where objectives are often conflicting and uncertain. Mathematical programming formulations can be used to achieve flexible, feasible and optimal operation and planning solutions to satisfy expectations of multiple stake-holders, including regulatory environmental compliance and sustainability. Innovative optimization models using MINLP with binary variables, fuzzy set theory, partial constraint satisfaction and multi-objective formulations incorporating unit commitment problem and adaptive real-time operations are developed and applied to a real life case study. These methodologies provide advances and valuable insights on optimal operations of hydropower systems under uncertain decision making environments. / by Andre Rodrigues Ferreira. / Thesis (M.S.C.S.)--Florida Atlantic University, 2009. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2009. Mode of access: World Wide Web.

by Kim-sau Chung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1994. / Includes bibliographical references (leaves 65-66). / Table of symbols --- p.3 / Introduction --- p.4 / Chapter Chapter one: --- On v-informativeness of informers --- p.9 / Chapter Section one: --- Introduction --- p.9 / Chapter Section two: --- Verifiability structure --- p.12 / Chapter Section three: --- Principal-informer-agent problem --- p.17 / Chapter Section four: --- On v-informativeness of informers --- p.23 / Chapter Section five: --- Conclusion --- p.30 / Chapter Chapter two: --- Idiosyncratic or uniform contracts for the Chinese state enterprises --- p.32 / Chapter Section one: --- Introduction --- p.32 / Chapter Section two: --- The model --- p.36 / Chapter Section three: --- Complete information case --- p.40 / Chapter Section four: --- Incomplete information with type I informer --- p.41 / Chapter Section five: --- Incomplete informaticri with type II informer --- p.45 / Chapter Section six: --- Incomplete information with type III informer --- p.58 / Chapter Section seven: --- Incomplete information with type IV informer --- p.59 / Chapter Section eight: --- Comparative values of mid-tier governmental units to the central government --- p.59 / Chapter Section nine: --- Conclusion --- p.63 / Reference --- p.65

by Siu-yeung Chan. / Publication date from spine. / Thesis (Ph.D.)--Chinese University of Hong Kong, 1995. / Includes bibliographical references (leaves 254-278). / Chapter CHAPTER I --- INTRODUCTION --- p.1 / Chapter 1.1 --- Background of the Study --- p.1 / Chapter 1.2 --- Research Problems and Objectives --- p.5 / Chapter 1.3 --- Justification for the Study --- p.7 / Chapter 1.4 --- Research Model and Hypotheses --- p.9 / Chapter 1.4.1 --- Research Model --- p.9 / Chapter 1.4.2 --- Research Hypotheses --- p.10 / Chapter 1.5 --- Research Methodology --- p.12 / Chapter 1.6 --- Definitions of Key Terms --- p.14 / Chapter 1.7 --- Scope of the Study --- p.16 / Chapter 1.8 --- Organisation of the Thesis --- p.17 / Chapter CHAPTER II --- LITERATURE REVIEW ON BEHAVIOURAL DECISION THEORY --- p.19 / Chapter 2.1 --- Introduction --- p.19 / Chapter 2.2 --- Behavioural Decision Theory: Historical Development --- p.20 / Chapter 2.3 --- Bounded Rationality --- p.22 / Chapter 2.4 --- Lens Model --- p.25 / Chapter 2.5 --- Heuristics and Biases --- p.27 / Chapter 2.5.1 --- Overview --- p.27 / Chapter 2.5.2 --- Availability Heuristic --- p.28 / Chapter 2.5.3 --- Anchoring and Adjustment Heuristic --- p.29 / Chapter 2.5.4 --- Representativeness Heuristic --- p.31 / Chapter 2.5.5 --- Conjunction Fallacy --- p.32 / Chapter 2.5.6 --- Hindsight Bias --- p.34 / Chapter 2.5.7 --- Order Effects in Brief Updating --- p.35 / Chapter 2.5.7.1 --- Evidence Encoding --- p.36 / Chapter 2.5.7.2 --- Response Mode --- p.37 / Chapter 2.5.7.3 --- Adjustment Weighting --- p.38 / Chapter 2.5.7.4 --- Order Effects --- p.39 / Chapter 2.5.8 --- Framing Effect --- p.40 / Chapter 2.5.9 --- Sunk Cost Effect --- p.42 / Chapter 2.5.10 --- Confirmation Bias --- p.44 / Chapter 2.5.11 --- Accountability --- p.47 / Chapter 2.5.12 --- Base-Rate Fallacy --- p.49 / Chapter 2.5.12.1 --- Reduction of the Base-Rate Fallacy --- p.51 / Chapter 2.5.12.1.1 --- The Relevance of Base-Rate Information --- p.51 / Chapter 2.5.12.1.2 --- The Relevance of Case-Specific Evidence --- p.53 / Chapter 2.5.12.2 --- Effects of Need for Cognition on the Base-Rate Fallacy --- p.54 / Chapter 2.5.13 --- Overconfidence Effect --- p.56 / Chapter 2.5.13.1 --- Calibration and Calibration Curve --- p.58 / Chapter 2.5.13.2 --- Factors Affecting Appropriateness of Confidence --- p.60 / Chapter 2.5.13.2.1 --- Task Factors --- p.60 / Chapter 2.5.13.2.2 --- Environmental Factors --- p.61 / Chapter 2.5.13.2.3 --- Individual Difference Factors --- p.63 / Chapter 2.5.13.3 --- Methods Promoting Appropriate Confidence --- p.64 / Chapter 2.5.13.4 --- Appropriateness of Experts' Confidence --- p.67 / Chapter 2.5.13.5 --- Conceptual and Methodological Issues --- p.68 / Chapter 2.6 --- Contingent Decision Behaviour --- p.72 / Chapter 2.6.1 --- Overview --- p.72 / Chapter 2.6.2 --- Factors Influencing Contingent Decision Behaviour --- p.73 / Chapter 2.6.3 --- Effects of Task Variables on Selecting Decision Strategies --- p.74 / Chapter 2.6.3.1 --- Task Complexity --- p.74 / Chapter 2.6.3.2 --- Response Mode --- p.77 / Chapter 2.6.3.3 --- Information Display Mode --- p.77 / Chapter 2.6.3.4 --- Agenda Effect --- p.78 / Chapter 2.6.4 --- Effects of Context Variables on Selecting Decision Strategies --- p.78 / Chapter 2.6.5 --- Effects of Effort and Accuracy on Selecting Decision Strategies --- p.79 / Chapter 2.7 --- Integrated Framework for Behavioural Decision Theory --- p.81 / Chapter 2.7.1 --- Principle of Bounded Rationality and the Three Research Frameworks --- p.82 / Chapter 2.7.2 --- Lens Model and Heuristics-and-Biases Frameworks --- p.83 / Chapter 2.7.3 --- Lens Model and Contingent Decision Behaviour Frameworks --- p.84 / Chapter 2.7.4 --- Heuristics-and-Biases and Contingent Decision Behaviour Frameworks --- p.85 / Chapter 2.8 --- Chapter Summary --- p.85 / Chapter CHAPTER III --- LITERATURE REVIEW ON BEHAVIOURAL DECISION RESEARCH IN ACCOUNTING --- p.88 / Chapter 3.1 --- Introduction --- p.88 / Chapter 3.2 --- Overview of BDR in Accounting and the Major Determinants of Decision-Making Performance --- p.89 / Chapter 3.3 --- Heuristics and Biases --- p.93 / Chapter 3.3.1 --- Overview --- p.93 / Chapter 3.3.2 --- Availability Heuristic --- p.94 / Chapter 3.3.3 --- Anchoring and Adjustment Heuristic --- p.96 / Chapter 3.3.4 --- Order Effects in Belief Updating --- p.99 / Chapter 3.3.4.1 --- Overview --- p.99 / Chapter 3.3.4.2 --- Model Predictions --- p.100 / Chapter 3.3.4.3 --- Order Effects On Effectiveness --- p.102 / Chapter 3.3.4.4 --- Factors Affecting the Order Effects --- p.103 / Chapter 3.3.4.5 --- Summary of Accounting Research on the Order Effects in Belief Updating --- p.105 / Chapter 3.3.5 --- Conjunction Fallacy --- p.106 / Chapter 3.3.6 --- Framing Effect --- p.107 / Chapter 3.3.7 --- Confirmation Bias --- p.110 / Chapter 3.3.8 --- Hindsight Bias --- p.113 / Chapter 3.3.9 --- Accountability --- p.116 / Chapter 3.3.10 --- Base-Rate Fallacy --- p.118 / Chapter 3.3.10.1 --- Overview --- p.118 / Chapter 3.3.10.2 --- Attention to Base Rates --- p.119 / Chapter 3.3.10.3 --- Attention to Source Reliability --- p.123 / Chapter 3.3.10.4 --- Insensitivity to Sample Size --- p.127 / Chapter 3.3.10.5 --- Summary for Accounting Research on the Base-Rate Fallacy --- p.129 / Chapter 3.3.11 --- Overconfidence Effect --- p.129 / Chapter 3.3.11.1 --- Appropriateness of Auditors' Confidence --- p.130 / Chapter 3.3.11.2 --- Factors Affecting the Appropriateness of Auditors' Confidence --- p.131 / Chapter 3.4 --- Behavioural Decision Research in Financial Distress Prediction --- p.136 / Chapter 3.4.1 --- Overview --- p.136 / Chapter 3.4.2 --- Prediction Performance --- p.137 / Chapter 3.4.2.1 --- Prediction Accuracy --- p.137 / Chapter 3.4.2.2 --- Appropriateness of Confidence --- p.138 / Chapter 3.4.3 --- Factors Affecting Prediction Performance --- p.139 / Chapter 3.4.3.1 --- Overview --- p.139 / Chapter 3.4.3.2 --- Information Load --- p.139 / Chapter 3.4.3.3 --- Information Cue Choice Versus Weighing of Cues --- p.140 / Chapter 3.4.3.4 --- Base-Rate Information --- p.141 / Chapter 3.4.3.5 --- Task Predictability --- p.144 / Chapter 3.4.3.6 --- Reward Structure --- p.145 / Chapter 3.4.3.7 --- Individual Differences --- p.145 / Chapter 3.4.4 --- Group Judgment Accuracy --- p.146 / Chapter 3.4.5 --- Section Summary --- p.147 / Chapter 3.5 --- Motivation for the Current Study --- p.149 / Chapter 3.5.1 --- Research Opportunity 1 --- p.149 / Chapter 3.5.2 --- Research Opportunity 2 --- p.150 / Chapter 3.5.3 --- Research Opportunity 3 --- p.152 / Chapter 3.5.4 --- Research Opportunity 4 --- p.153 / Chapter 3.6 --- Chapter Summary --- p.154 / Chapter CHAPTER IV --- RESEARCH MODEL AND HYPOTHESES --- p.156 / Chapter 4.1 --- Introduction --- p.156 / Chapter 4.2 --- Research Model --- p.156 / Chapter 4.3 --- Research Hypotheses --- p.158 / Chapter 4.3.1 --- Hypothesis 1 --- p.158 / Chapter 4.3.2 --- Hypothesis 2 --- p.160 / Chapter 4.3.3 --- Hypothesis 3 --- p.163 / Chapter 4.3.4 --- Hypothesis 4 --- p.166 / Chapter 4.3.5 --- Hypothesis 5 --- p.168 / Chapter 4.4 --- Chapter Summary --- p.172 / Chapter CHAPTER V --- RESEARCH METHOD AND DESIGN --- p.173 / Chapter 5.1 --- Introduction --- p.173 / Chapter 5.2 --- Research Method --- p.173 / Chapter 5.3 --- Experimental Design --- p.175 / Chapter 5.4 --- Subjects --- p.177 / Chapter 5.5 --- Construction of the Experiment Instrument --- p.179 / Chapter 5.5.1 --- Selection of Sample Firms for Prediction Tasks --- p.180 / Chapter 5.5.1.1 --- Definition of Firms being in Financial Distress --- p.180 / Chapter 5.5.1.2 --- Identification of Firms in Financial Distress --- p.182 / Chapter 5.5.1.3 --- Selection of Healthy Firms --- p.182 / Chapter 5.5.1.4 --- Sample Firms in the Instrument --- p.183 / Chapter 5.5.2 --- Selection of Financial Ratios --- p.184 / Chapter 5.5.2.1 --- Logit Analysis --- p.185 / Chapter 5.5.2.2 --- Pilot Interviews --- p.187 / Chapter 5.5.2.3 --- Final Financial Ratios Used in the Instrument --- p.188 / Chapter 5.5.3 --- Modification of the Need for Cognition Scale --- p.189 / Chapter 5.5.4 --- Translation of the Experiment Instrument --- p.191 / Chapter 5.5.5 --- Pretest of the Experiment Instrument --- p.191 / Chapter 5.6 --- Administration of Experiment --- p.192 / Chapter 5.7 --- Operationalisation and Measurement of Variables --- p.193 / Chapter 5.7.1 --- Relevance of Base-Rate Information --- p.193 / Chapter 5.7.2 --- Need For Cognition --- p.195 / Chapter 5.7.3 --- Perceived Informativeness of Case-Specific Evidence --- p.197 / Chapter 5.7.4 --- Appropriateness of Confidence --- p.199 / Chapter 5.8 --- Data Analysis Methods --- p.201 / Chapter 5.9 --- Chapter Summary --- p.203 / Chapter CHAPTER VI --- ANALYSIS OF DATA --- p.205 / Chapter 6.1 --- Introduction --- p.205 / Chapter 6.2 --- Descriptive Data about the Subjects --- p.205 / Chapter 6.3 --- Stepwise Logit Analysis --- p.207 / Chapter 6.4 --- Statistical Testing for Hypotheses --- p.210 / Chapter 6.4.1 --- Testing Hypothesis 1 --- p.211 / Chapter 6.4.2 --- Unbalanced ANOVA Model --- p.212 / Chapter 6.4.3 --- Testing the Base Rate Pre-occupied by the Subjects --- p.215 / Chapter 6.4.4 --- Testing Hypothesis 2 --- p.217 / Chapter 6.4.5 --- Testing Hypothesis 3 --- p.218 / Chapter 6.4.6 --- Testing Hypothesis 4 --- p.220 / Chapter 6.4.7 --- Testing Hypothesis 5 --- p.222 / Chapter 6.5 --- Supplementary Statistical Testing of Hypotheses --- p.224 / Chapter 6.5.1 --- Separate Models for Hypotheses 2 to 5 --- p.224 / Chapter 6.5.2 --- Effects of Other Interactions --- p.224 / Chapter 6.5.3 --- Analysing NC As a Continuous Variable --- p.225 / Chapter 6.5.4 --- Repeated Measures ANOVA --- p.226 / Chapter 6.5.5 --- Additional Analysis ´ؤ Controlling for Task Predictability --- p.228 / Chapter 6.6 --- Chapter Summary --- p.232 / Chapter CHAPTER VII --- "SUMMARY, DISCUSSIONS AND IMPLICATIONS" --- p.234 / Chapter 7.1 --- Recap of the Study --- p.234 / Chapter 7.2 --- Conclusions and Discussions --- p.237 / Chapter 7.2.1 --- Hypothesis 1 --- p.237 / Chapter 7.2.2 --- Hypothesis 2 --- p.239 / Chapter 7.2.3 --- Hypothesis 3 --- p.241 / Chapter 7.2.4 --- Hypothesis 4 --- p.243 / Chapter 7.2.5 --- Hypothesis 5 --- p.244 / Chapter 7.2.6 --- Overall Conclusions --- p.246 / Chapter 7.3 --- Implications for Theory --- p.246 / Chapter 7.4 --- Implications for Practice --- p.248 / Chapter 7.5 --- Limitations of the Study --- p.249 / Chapter 7.6 --- Recommendations for Further Research --- p.252 / REFERENCES --- p.254 / APPENDIX A: EXPERIMENT INSTRUMENT (IN ENGLISH) --- p.279 / APPENDIX B: EXPERIMENT INSTRUMENT (IN CHINESE) --- p.306 / APPENDIX C: STEPWISE LOGIT ANALYSIS RESULTS --- p.333

Thesis. 1977. Ph.D.--Massachusetts Institute of Technology. Alfred P. Sloan School of Management. / Vita. / Bibliography : leaves 336-346. / Ph.D.

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1981. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Includes bibliographical references. / by Kevin Lloyd Boettcher. / M.S.

In infinitely repeated games, we also give definitions to risk attitude and reputation. As art infinitely repeated game is a repetition of a constituent strategic game, we transform each single round of an infinitely repeated game as a risk game. We extend the definitions of risk strategies and risk strategy equilibrium to infinitely repeated games. We also research some properties of risk strategy equilibrium and show that players can obtain higher payoffs in risk strategy equilibrium than in pure strategy Nash equilibrium. / In multi-agent systems, agents often need to make decisions, especially under uncertainty. When a decision-maker needs to choose among a number of choices, each having a certain probability to happen, one of the traditional ways discussed in economics is to calculate the expected utility of each choice and choose the one with the maximum expected utility. However, most of the humans do not do so in real situations. Very often, humans choose a choice with a lower expected utility. One of the famous examples is the Allais paradox. / In strategic games, we define risk attitude and reputation, which are factors that decision-makers take into account in making decisions. We transform a strategic game to a risk game. We propose a new kind of strategies, called risk strategies. In the transformed risk game, we find a new kind of equilibrium, called risk strategy equilibrium. We also find out some properties of risk strategy equilibrium. In addition, we find that players can obtain higher payoffs in risk strategy equilibrium than in pure strategy Nash equilibrium. / One of the key properties defining an intelligent agent is social ability. This means that an intelligent agent should be able to interact with other agents or humans. Before designing an intelligent agent for any multi-agent system, we need to first understand how agents should behave and interact in that particular application. / One way to understand how agents should behave in a particular application is to model the application as a game. Besides, many real-life situations can be modeled as games. So, we extend the model of attractiveness maximization and apply the extended model to strategic games and infinitely repeated games. / The reason why most of the people do not maximize the expected utility is that people have different attitudes towards risk in different situations and people are generally risk-averse. To model this human behavior, we propose another way of decision-making, called attractiveness maximization. In this model, every choice has an attractiveness, which is calculated from the risk attitude of the decision-maker, probability, and utility. In making decisions, decision-makers choose the choice with the maximum attractiveness. Using attractiveness maximization, the phenomenon that human do not maximize expected utility can be explained. We also find some properties of the model of attractiveness maximization, which match the human behaviors. / We develop several applications of attractiveness maximization and risk strategies. First, we apply the proposed concepts to the Iterated Prisoner's Dilemma, which is widely used by economists and sociologists to model and simulate many of the human interactions. Simulation shows that agents have improved performance and are reactive as well as pro-active. Second, we construct behavioral predictors and an adaptive strategy for Minority Games, which model many real life situations like the financial market, auctions and resources competitions. Simulations show that the adaptive strategy works much better than previous models. Third, we model a resource allocation problem as a Minority Game and apply the behavioral predictors and the adaptive strategy to the resource allocation problem. Simulations also show that agents with the proposed adaptive strategy are able to make more right decisions and better resource utilization than previous work. / Lam, Ka Man. / "August 2007." / Adviser: Leung Ho Fung. / Source: Dissertation Abstracts International, Volume: 69-02, Section: B, page: 1107. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (p. 159-173). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract in English and Chinese. / School code: 1307.

Assuming that all unmet demand is fully lost, we begin our study by confining the sales lever to be price only, that is, z = p , and ignoring the cost for executing the sales lever. Given a stationary (s, S, p) policy, we find that the profit function for the lost-sales case exhibits the same structure as the one for the backlogging case. We further show that the relaxed assumption on the news-vendor type profit function can also be satisfied by a broad class of demand function. We can therefore extend the optimizing algorithm and the optimality analysis developed earlier to the lost-sales case. We further demonstrate that the results can be extended to the general sales lever decisions. / Assuming that unmet demand is fully backlogged, a newsvendor-type profit function which is defined as the resulting expected one-period profit with sales lever being optimized for every inventory level, fails to be unimodal. By assuming the newsvendor-type profit function to have a finite number of local maxima, we develop an efficient algorithm for finding the optimal ( s, S, z) policy with the long-run average profit derived by the renewal theory. We further identify the conditions under which the (s, S, z) policy is globally optimal. / Issues on the interfaces between operations management and marketing research have attracted much attention recently. The developments integrating marketing decisions into inventory management are not only of academic interest, but also of practical importance. With uncertain demand, this research studies the joint determination of inventory and sales lever decisions such as price, incentives to salesforce, and short-term promotions, or a combination of them. / We consider a single-item, periodic-review system with the objective of maximizing the long-run average profit over an infinite planning horizon. Demand in a period is a non-negative, discrete random variable with its distribution dependent on the sales lever chosen for the period. A replenishment order can be placed at the beginning of a period incurring both fixed and variable ordering costs. The sales lever is determined jointly, and its execution may incur possible cost, for example, promotion cost. For such a model, we take particular interest in a so-called (s, S, z) policy, which operates as follows: whenever the inventory level falls to or below s, an order is placed to bring it up to S; when the inventory level is above s, no order is issued; the choice of sales lever z depends on the inventory level. / We finally conduct an extensive numerical study for both the backlogging and lost-sales cases. We compare the benefits of the dynamic sales lever strategy with those of the semi-dynamic as well as the static sales lever strategy, and find that the profit gains are significant. By sensitivity analysis, we bring out the impact of cost parameters on the optimal solutions. / Wei Ying. / "December 2006." / Adviser: Youhua Frank Chen. / Source: Dissertation Abstracts International, Volume: 68-09, Section: A, page: 3961. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (p. 125-131). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest dissertations and theses, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract in English and Chinese. / School code: 1307.

The range and number of new applications and services are growing at an unprecedented rate. Computer networks need to be able to provide connectivity for these services and meet their constantly changing demands. This requires not only support of new network protocols and security requirements, but often architectural redesigns for long-term improvements to efficiency, speed, throughput, cost, and security. Networks are now facing a drastic increase in size and are required to carry a constantly growing amount of heterogeneous traffic. Unfortunately such dynamism greatly complicates security of not only the end nodes in the network, but also of the nodes of the network itself. To make matters worse, just as applications are being developed at faster and faster rates, attacks are becoming more pervasive and complex. Networks need to be able to understand the impact of these attacks and protect against them. Network control devices, such as routers, firewalls, censorship devices, and base stations, are elements of the network that make decisions on how traffic is handled. Although network control devices are expected to act according to specifications, there can be various reasons why they do not in practice. Protocols could be flawed, ambiguous or incomplete, developers could introduce unintended bugs, or attackers may find vulnerabilities in the devices and exploit them. Malfunction could intentionally or unintentionally threaten the confidentiality, integrity, and availability of end nodes and the data that passes through the network. It can also impact the availability and performance of the control devices themselves and the security policies of the network. The fast-paced evolution and scalability of current and future networks create a dynamic environment for which it is difficult to develop automated tools for testing new protocols and components. At the same time, they make the function of such tools vital for discovering implementation flaws and protocol vulnerabilities as networks become larger and more complex, and as new and potentially unrefined architectures become adopted. This thesis will present the design, implementation, and evaluation of a set of tools designed for understanding implementation of network control nodes and how they react to changes in traffic characteristics as networks evolve. We will first introduce Firecycle, a test bed for analyzing the impact of large-scale attacks and Machine-to-Machine (M2M) traffic on the Long Term Evolution (LTE) network. We will then discuss Autosonda, a tool for automatically discovering rule implementation and finding triggering traffic features in censorship devices. This thesis provides the following contributions: 1. The design, implementation, and evaluation of two tools to discover models of network control nodes in two scenarios of evolving networks, mobile network and censored internet 2. First existing test bed for analysis of large-scale attacks and impact of traffic scalability on LTE mobile networks 3. First existing test bed for LTE networks that can be scaled to arbitrary size and that deploys traffic models based on real traffic traces taken from a tier-1 operator 4. An analysis of traffic models of various categories of Internet of Things (IoT) devices 5. First study demonstrating the impact of M2M scalability and signaling overload on the packet core of LTE mobile networks 6. A specification for modeling of censorship device decision models 7. A means for automating the discovery of features utilized in censorship device decision models, comparison of these models, and their rule discovery

Ding, Ling. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (leaves [43]-45). / Abstract also in Chinese. / Thesis Committee --- p.i / Abstract --- p.ii / Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Background --- p.1 / Chapter 1.2 --- Motivation --- p.3 / Chapter 1.3 --- Thesis Organization --- p.4 / Chapter 2 --- Representative Skylines and Basic Properties --- p.6 / Chapter 2.1 --- Existing Formulation --- p.6 / Chapter 2.1.1 --- Max-dominance Representative Skyline --- p.6 / Chapter 2.1.2 --- Defects of the Existing Formulation --- p.7 / Chapter 2.2 --- Our Formulation --- p.9 / Chapter 2.2.1 --- Distance-based Representative Skyline --- p.9 / Chapter 2.2.2 --- Properties of Our Formulation --- p.10 / Chapter 2.3 --- Problem Definition --- p.12 / Chapter 3 --- The Two-dimensional Case --- p.13 / Chapter 3.1 --- Algorithm 2D-opt --- p.13 / Chapter 3.2 --- Time Complexity --- p.15 / Chapter 3.3 --- Computing Covering Circles --- p.15 / Chapter 4 --- The Higher-dimensional Case --- p.18 / Chapter 4.1 --- NP-hardness and 2-approximation --- p.18 / Chapter 4.1.1 --- Proof of NP-hardness --- p.18 / Chapter 4.1.2 --- Algorithm naive-greedy --- p.19 / Chapter 4.2 --- Algorithm I-greedy --- p.20 / Chapter 4.2.1 --- Conservative Skyline --- p.22 / Chapter 4.2.2 --- Access Order --- p.23 / Chapter 4.3 --- Computing the Maximum Representative Distance --- p.27 / Chapter 5 --- Experiments --- p.30 / Chapter 5.1 --- Data --- p.30 / Chapter 5.2 --- Representation Quality --- p.31 / Chapter 5.2.1 --- Representative Skylines --- p.31 / Chapter 5.2.2 --- Representation Error Comparison --- p.33 / Chapter 5.3 --- Efficiency --- p.34 / Chapter 5.3.1 --- Running Time Comparison --- p.34 / Chapter 5.3.2 --- Scalability Comparison --- p.37 / Chapter 6 --- Related Work --- p.39 / Chapter 7 --- Conclusions --- p.41 / A List of Publications --- p.42 / Bibliography --- p.43