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

We investigate new algorithms for efficiently establishing a multicast session in a mesh network while protecting the session from a link failure, e.g., a fiber cut in an optical network.

Algorithms for Provisioning Survivable Multicast Sessions against Link Failures in Mesh Networks

The authors study the interconnection of CSMA/CD (carrier sense multiple access with collision detection) local area networks (LANs) or LAN segments using a transparent bridge. The main concern was to study the performance and the implementation of a transparent bridge employing a novel bridging technique called cut-through bridging. The authors developed an approximate performance model of a multisegment CSMA/CD LAN whose segments are connected by a transparent bridge (cut-through or store-and-forward variety). It is found that, at light loads, the cut-through bridged system provided a lower average frame delay than a normal-bridged system, whereas at heavy loads, it achieved the same maximum throughput as the latter. Also, the normalized channel capacity of a bridged system could exceed unity because of the availability of multiple channels for parallel frame transmissions. The analysis was found to be quite accurate upon verification by simulation. Also, implementation of a normal transparent bridge requiring two Ethernet Etherlink interfaces and bridge software for interconnecting CSMA/CD LAN segments is reported. >

http://ieeexplore.ieee.org/iel2/808/2325/00063964.pdf

On transparent bridging of CSMA/CD networks

Traffic in optical backbone networks is increasing and becoming heterogeneous with respect to bandwidth and QoS requirements due to the popularity of high-bandwidth services such as cloud computing, e-science, telemedicine, etc which need to coexist with traditional services (HTTP, etc) Mixed-line-rate (MLR) networks which support lightpaths of different rates are being studied to support the heterogeneous traffic demands Here, we study the important topic of degraded services in MLR networks, where a service can accept degradation in bandwidth to a certain extent in case of a failure for lower cost, a concept called partial protection Network operators may wish to support degraded services to optimize network resources and reduce cost We develop a multipath routing scheme to support degraded services in MLR networks, and our illustrative examples show that significant cost savings can be achieved vs full protection

Degraded services in mixed-line-rate networks using multipath routing

We study a novel scheme to manage networks with heterogeneous traffic efficiently under resource crunch. We consider different types of revenue models for different service classes. We show that degradation of services and redistribution of resources while satisfying QoS under resource crunch can improve both availability and revenue.

Network adaptability under resource crunch

This paper studies optimal traffic provisioning under service heterogeneity to alleviate the dramatic decrease in network resources, a.k.a. resource crunch, caused by large-area network failures or a traffic surge. Some services are sensitive to capacity provided, while others (e.g., video streaming) can operate with reduced bandwidth (degraded service). Degraded-service-tolerant connections can be admitted and recovered with reduced service under resource crunch. Our adaptive solutions distribute capacity among competing services when some may get degraded service under resource crunch but satisfying the Service-Level Objectives (SLOs).

Biswanath Mukherjee

Papers

Algorithms for Provisioning Survivable Multicast Sessions against Link Failures in Mesh Networks

On transparent bridging of CSMA/CD networks

Degraded services in mixed-line-rate networks using multipath routing

Network adaptability under resource crunch

Network adaptability to disasters by exploiting degraded-service tolerance