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

The Grid 2: Blueprint for a New Computing Infrastructure

A survey on cloud computing security

We study the virtual machine live migration (LM) and disaster recovery (DR) from a networking perspective, considering long-distance networks, for example, between data centers. These networks are usually constrained by limited available bandwidth, increased latency and congestion, or high cost of use when dedicated network resources are used, while their exact characteristics cannot be controlled. LM and DR present several challenges due to the large amounts of data that need to be transferred over long-distance networks, which increase with the number of migrated or protected resources. In this context, our work presents the way LM and DR are currently being performed and their operation in long-distance networking environments, discussing related issues and bottlenecks and surveying other works. We also present the way networks are evolving today and the new technologies and protocols (e.g., software-defined networking, or SDN, and flexible optical networks) that can be used to boost the efficiency of LM and DR over long distances. Traffic redirection in a long-distance environment is also an important part of the whole equation, since it directly affects the transparency of LM and DR. Related works and solutions both from academia and the industry are presented.

Survey: Live Migration and Disaster Recovery over Long-Distance Networks

Marc Dacier's topic is: intrusion detection vs. detection of errors caused by intentionally malicious faults. Although research on intrusion detection has been carried out for more than two decades, it has recently received increased attention due to the success of the Internet. A recent survey conducted by the IBM Global Security Laboratory indicates that more than 20 intrusion-detection products are now available on the market, whereas two years ago there were only three. Despite this growth of product offerings, intrusion-detection solutions are still in their infancy. Not only is there a lack of understanding of what an intrusion really is, but also how it should be handled. Moreover, from a technical point of view, many critical issues remain unsolved.In this talk, Marc presents what has been done in the intrusion domain in the past, and highlights new research directions that need to be addressed. He will highlight the relationship between intrusion detection and fault tolerance, drawing on the body of knowledge that has been developed within the traditional dependability community, and noting the opportunities for these two communities to work together to solve this important problem.Sami Saydjari's topic is: the detection of novel, previously unseen attacks. Although intrusion detection is a field still in its infancy, two broad approaches have evolved: pattern-based detection and anomaly-based detection. Pattern-based detection, sometimes called misuse-based detection, relies on matching known patterns of attacks already suffered. Anomaly-based detection, on the other hand, relies on detecting behaviors that are abnormal with respect to some normal standard. An example is that of a masquerader trying to hide behind someone else's login; unless the masquerader is clever indeed, his activities will stand out as anomalous against a victim's profile of normal behavior. Anomaly-based detection techniques appear to hold the best hope of detecting new variants of attacks.Sami emphasizes that although there exist some low-level sensors that can detect known attacks, the research community must move quickly in learning how to detect novel attacks at much higher detection rates (state of the art is around 80%) while keeping the false positive rates very low (0.1% or better). Detecting novel attacks will require better anomaly detection algorithms. Achieving a 99.9% detection rate will require gaining a firm understanding of the "sweet spots" of various detection algorithms, as well as an understanding of how to fuse the results of the best of the best. There is also a need to better represent knowledge of attack patterns in a canonical form, to be able to share that knowledge across multiple detection tools, and to be able to judge tools on the basis of how effectively they use knowledge, as opposed to which tool can include the largest corpus of precompiled (pattern-based) knowledge into its on-line database.The session concludes with an open discussion of how research communities can work together to reduce undependability caused by intentionally malicious faults.

Intrusion Detection

Grid computing has recently migrated from traditional high performance and distributed computing to pervasive and utility computing based on the advanced capabilities of the wireless networks and the lightweight, thin devices. This has as result the emergence of a new computing paradigm which is the Mobile Grid. This paper presents the simulation results in order to choose the best routing protocol to give the highest performance when implement the routing protocols in the target mobile grid application. The simulations comparing three ad hoc routing protocols named DSDV, DSR and AODV. The simulations have shown that the conventional routing protocols like DSR have a dramatic decrease in performance when mobility is high. However the AODV and DSDV are perform very well when mobility is high.

/pdf/performance-evaluation-of-aodv-dsdv-dsr-routing-protocol-in-k3jobd1zhv.pdf

Performance evaluation of AODV, DSDV & DSR routing protocol in grid environment

Cloud computing has become a significant research area in large-scale computing, because it can share globally distributed resources Cloud computing has evolved with the development of large-scale data centers, including thousands of servers around the world However, cloud data centers consume vast amounts of electrical energy, contributing to high-operational costs, and carbon dioxide emissions Dynamic consolidation of virtual machines (VMs) using live migration and putting idle nodes in sleep mode allows cloud providers to optimize resource utilization and reduce energy consumption However, aggressive VM consolidation may degrade the performance Therefore, an energy-performance tradeoff between providing high-quality service to customers and reducing power consumption is desired In this paper, several novel algorithms are proposed for the dynamic consolidation of VMs in cloud data centers The aim is to improve the utilization of computing resources and reduce energy consumption under SLA constraints regarding CPU, RAM, and bandwidth The efficiency of the proposed algorithms is validated by conducting extensive simulations The results of the evaluation clearly show that the proposed algorithms significantly reduce energy consumption while providing a high level of commitment to the SLA Based on the proposed algorithms, energy consumption can be reduced by up to 28%, and SLA can be improved up to 87% when compared with the benchmark algorithms

Energy-Efficient Algorithms for Dynamic Virtual Machine Consolidation in Cloud Data Centers

Mobile computing has supplanted internet computing because of the proliferation of cloud-based applications and mobile devices (such as smartphones, palmtops, and tablets). As a result of this, wor...

https://journals.sagepub.com/doi/pdf/10.1177/2158244015580372

A Review of Bring Your Own Device on Security Issues

Intrusion Detection System (IDS) have become increasingly popular over the past years as an important network security technology to detect cyber attacks in a wide variety of network communication. IDS monitors' network or host system activities by collecting network information, and analyze this information for malicious activities. Cloud computing, with the concept of Software as a Service (SaaS) presents an exciting benefit when it enables providers to rent their services to users in perform complex tasks over the Internet. In addition, Cloud based services reduce a cost in investing new infrastructure, training new personnel, or licensing new software. In this paper, we introduce a novel framework based on Cloud computing called Cloud-based Intrusion Detection Service (CBIDS). This model enables the identification of malicious activities from different points of network and overcome the deficiency of classical intrusion detection. CBIDS can be implemented to detect variety of attacks in private and public Clouds.

A Cloud-based Intrusion Detection Service framework

The cloud provider plays a major role especially providing resources such as computing power for the cloud subscriber to deploy their applications on multiple platforms anywhere; anytime. Hence the cloud users still having problem for resource management in receiving the guaranteed computing resources on time. This will impact the service time and the service level agreements for various users in multiple applications. Therefore there is a need for a new resolution to resolve this problem. This survey paper conducts a study in resource allocation and monitoring in the cloud computing environment. We describe cloud computing and its properties, research issues in resource management mainly in resource allocation and monitoring and finally solutions approach for resource allocation and monitoring. It is believed that this paper would benefit both cloud users and researchers for further knowledge on resource management in cloud computing. On the other hand, the resources on the cloud are pooled in order to serve multiple subscribers. The provider use multi-tenancy model where the resources (physical and virtual) are reassigned dynamically based on the tenant requirement (5). The assigning of the resources will be based on the lease and SLA agreement, whereby different clients will need more or less amount of virtual resources. Subsequently, the growth of demands for cloud services is bringing more challenge for the provider to provide the resources to the client subscriber. Therefore, in this paper we provide a review on cloud computing which focus on resource management: allocation and monitoring. Our methodologies for this review are as follows:  We provide a cloud computing taxonomy covers the cloud definitions, characteristics and deployment models.  We then analyze the literatures and discuss about resource management, the process and the elements.  We then concentrate literatures on resource allocation and monitoring. We derived the problems, challenge and the approach solution for resource allocation and monitoring in the cloud. This paper organizes as follows: Section II introduces an overview of Cloud Computing, Section III discuss about resource management and its processes, Section IV discuss about related work with resource management in the cloud, section, Section V describes about approach solution to resource allocation and monitoring and, finally Section VI concludes the paper.

/pdf/a-survey-on-resource-allocation-and-monitoring-in-cloud-1laockphs3.pdf

Azizol Abdullah

Papers

Performance evaluation of AODV, DSDV & DSR routing protocol in grid environment

Energy-Efficient Algorithms for Dynamic Virtual Machine Consolidation in Cloud Data Centers

A Review of Bring Your Own Device on Security Issues

A Cloud-based Intrusion Detection Service framework

A Survey on Resource Allocation and Monitoring in Cloud Computing