Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

https://www.science.smith.edu/~jcardell/Courses/EGR328/Readings/WSNSurvey2.pdf

Wireless sensor network survey

Preface 1. Decision-Theoretic Foundations 1.1 Game Theory, Rationality, and Intelligence 1.2 Basic Concepts of Decision Theory 1.3 Axioms 1.4 The Expected-Utility Maximization Theorem 1.5 Equivalent Representations 1.6 Bayesian Conditional-Probability Systems 1.7 Limitations of the Bayesian Model 1.8 Domination 1.9 Proofs of the Domination Theorems Exercises 2. Basic Models 2.1 Games in Extensive Form 2.2 Strategic Form and the Normal Representation 2.3 Equivalence of Strategic-Form Games 2.4 Reduced Normal Representations 2.5 Elimination of Dominated Strategies 2.6 Multiagent Representations 2.7 Common Knowledge 2.8 Bayesian Games 2.9 Modeling Games with Incomplete Information Exercises 3. Equilibria of Strategic-Form Games 3.1 Domination and Ratonalizability 3.2 Nash Equilibrium 3.3 Computing Nash Equilibria 3.4 Significance of Nash Equilibria 3.5 The Focal-Point Effect 3.6 The Decision-Analytic Approach to Games 3.7 Evolution. Resistance. and Risk Dominance 3.8 Two-Person Zero-Sum Games 3.9 Bayesian Equilibria 3.10 Purification of Randomized Strategies in Equilibria 3.11 Auctions 3.12 Proof of Existence of Equilibrium 3.13 Infinite Strategy Sets Exercises 4. Sequential Equilibria of Extensive-Form Games 4.1 Mixed Strategies and Behavioral Strategies 4.2 Equilibria in Behavioral Strategies 4.3 Sequential Rationality at Information States with Positive Probability 4.4 Consistent Beliefs and Sequential Rationality at All Information States 4.5 Computing Sequential Equilibria 4.6 Subgame-Perfect Equilibria 4.7 Games with Perfect Information 4.8 Adding Chance Events with Small Probability 4.9 Forward Induction 4.10 Voting and Binary Agendas 4.11 Technical Proofs Exercises 5. Refinements of Equilibrium in Strategic Form 5.1 Introduction 5.2 Perfect Equilibria 5.3 Existence of Perfect and Sequential Equilibria 5.4 Proper Equilibria 5.5 Persistent Equilibria 5.6 Stable Sets 01 Equilibria 5.7 Generic Properties 5.8 Conclusions Exercises 6. Games with Communication 6.1 Contracts and Correlated Strategies 6.2 Correlated Equilibria 6.3 Bayesian Games with Communication 6.4 Bayesian Collective-Choice Problems and Bayesian Bargaining Problems 6.5 Trading Problems with Linear Utility 6.6 General Participation Constraints for Bayesian Games with Contracts 6.7 Sender-Receiver Games 6.8 Acceptable and Predominant Correlated Equilibria 6.9 Communication in Extensive-Form and Multistage Games Exercises Bibliographic Note 7. Repeated Games 7.1 The Repeated Prisoners Dilemma 7.2 A General Model of Repeated Garnet 7.3 Stationary Equilibria of Repeated Games with Complete State Information and Discounting 7.4 Repeated Games with Standard Information: Examples 7.5 General Feasibility Theorems for Standard Repeated Games 7.6 Finitely Repeated Games and the Role of Initial Doubt 7.7 Imperfect Observability of Moves 7.8 Repeated Wines in Large Decentralized Groups 7.9 Repeated Games with Incomplete Information 7.10 Continuous Time 7.11 Evolutionary Simulation of Repeated Games Exercises 8. Bargaining and Cooperation in Two-Person Games 8.1 Noncooperative Foundations of Cooperative Game Theory 8.2 Two-Person Bargaining Problems and the Nash Bargaining Solution 8.3 Interpersonal Comparisons of Weighted Utility 8.4 Transferable Utility 8.5 Rational Threats 8.6 Other Bargaining Solutions 8.7 An Alternating-Offer Bargaining Game 8.8 An Alternating-Offer Game with Incomplete Information 8.9 A Discrete Alternating-Offer Game 8.10 Renegotiation Exercises 9. Coalitions in Cooperative Games 9.1 Introduction to Coalitional Analysis 9.2 Characteristic Functions with Transferable Utility 9.3 The Core 9.4 The Shapkey Value 9.5 Values with Cooperation Structures 9.6 Other Solution Concepts 9.7 Colational Games with Nontransferable Utility 9.8 Cores without Transferable Utility 9.9 Values without Transferable Utility Exercises Bibliographic Note 10. Cooperation under Uncertainty 10.1 Introduction 10.2 Concepts of Efficiency 10.3 An Example 10.4 Ex Post Inefficiency and Subsequent Oilers 10.5 Computing Incentive-Efficient Mechanisms 10.6 Inscrutability and Durability 10.7 Mechanism Selection by an Informed Principal 10.8 Neutral Bargaining Solutions 10.9 Dynamic Matching Processes with Incomplete Information Exercises Bibliography Index

博弈论 : 矛盾冲突分析 = Game theory : analysis of conflict

Well adapted to the loosely coupled nature of distributed interaction in large-scale applications, the publish/subscribe communication paradigm has recently received increasing attention. With systems based on the publish/subscribe interaction scheme, subscribers register their interest in an event, or a pattern of events, and are subsequently asynchronously notified of events generated by publishers. Many variants of the paradigm have recently been proposed, each variant being specifically adapted to some given application or network model. This paper factors out the common denominator underlying these variants: full decoupling of the communicating entities in time, space, and synchronization. We use these three decoupling dimensions to better identify commonalities and divergences with traditional interaction paradigms. The many variations on the theme of publish/subscribe are classified and synthesized. In particular, their respective benefits and shortcomings are discussed both in terms of interfaces and implementations.

/pdf/the-many-faces-of-publish-subscribe-59ahrjbweq.pdf

The many faces of publish/subscribe

Border Gateway Protocol (BGP) is the protocol backing the core routing decisions on the Internet. It maintains a table of IP networks or 'prefixes' which designate network reachability among autonomous systems (AS). Point of concern in BGP is its lack of effective security measures which makes Internet vulnerable to different forms of attacks. Many solutions have been proposed till date to combat BGP security issues but not a single one is deployable in practical scenario. Any security proposal with optimal solution should offer adequate security functions, performance overhead and deployment cost. This paper critically analyzes the deployment issues of best three proposals considering trade-off between security functions and performance overhead.

Comparative analysis of

Fair allocation of available bandwidth to competing flows is a simple form of quality of service (QoS) that can be provided to customers in public networks. A number of packet-scheduling and buffer-management techniques have been proposed in the literature to achieve this goal efficiently. However, the complexity of the existing algorithms prevents a high-speed implementation with the current state of router technology. We propose a computationally simpler mechanism based on token-bucket policing to achieve almost equal bandwidth allocation for a set of competing flows. The proposed method adjusts the token-bucket threshold dynamically and measures the instantaneous arrival rate of flows. It uses this information to decide whether or not to admit a packet arriving at the network edge. With minor modifications, our framework can be used in a variety of practical network environments ranging from the Internet to virtual private networks (VPNs) over Frame Relay. We present a detailed simulation study that evaluates the performance of our algorithm. The simulation results indicate that DTB is fair, efficient, and robust.

Dynamic token bucket (DTB): a fair bandwidth allocation algorithm for high-speed networks

We investigate the problem of provisioning shared-mesh-protected sub-wavelength connections in wavelength-convertible optical WDM networks. We propose protection-at-lightpath (PAL) level and protection-at-connection (PAC) level. We found PAL outperforms PAC in such network settings.

Survivable traffic grooming in WDM mesh networks

This paper studies how to optimize deadlinedriven bulk-data transfer to recycle spectrum fragments in elastic optical networks (EONs). We first formulate a mixed integer linear program (MILP) for offline optimization with one of two objectives: 1) maximize the average datatransfer percentage of data-oriented requests (DO-Rs), or 2) minimize the incompletable data transfers among the DO-Rs. Then, we propose two dynamic provisioning algorithms. One addresses the first objective by setting a threshold on the minimum transferred data per time slot, and the other considers both admission control and blocking-aware routing and spectrum allocation to optimize the service provisioning according to the second objective. Simulation results indicate that the proposed algorithms can effectively optimize the DO-Rs' data transfers according to their objectives, revitalize the spectrum fragments, and improve the network spectrum utilization significantly.

Optimizing deadline-driven bulk-data transfer to revitalize spectrum fragments in EONs [Invited]

A novel bridging architecture, called a cut-through bridge, which can be used to interconnect existing carrier-sense multiple access with collision detection (CSMA/CD) LANs is proposed. This bridge uses the cut-through switching concept. After providing a design of this bridge, the authors examine its performance via a detailed simulation model. They demonstrate the performance enhancement achievable by the cut-through bridge over a normal bridge, namely lower average frame delay while attaining the same maximum throughput as the latter. Since the cut-through bridge can be readily used to replace passive repeaters while achieving superior performance, it has promise for immediate application in existing CSMA/CD LANs. >

Cut-through bridging for CSMA/CD local area networks

We define the multi-layer resilient layer-1 VPN design problem, where the traffic matrix is given, and an optimal survivable VPN is designed by formulating the problem, first time, as an integer linear program.

Biswanath Mukherjee

Papers

Dynamic token bucket (DTB): a fair bandwidth allocation algorithm for high-speed networks

Survivable traffic grooming in WDM mesh networks

Optimizing deadline-driven bulk-data transfer to revitalize spectrum fragments in EONs [Invited]

Cut-through bridging for CSMA/CD local area networks

Multi-Layer Resilient Design for Layer-1 VPNs