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Abstract A two-dimensional version of the Pennsylvania State University mesoscale model has been applied to Winter Monsoon Experiment data in order to simulate the diurnally occurring convection observed over the South China Sea. The domain includes a representation of part of Borneo as well as the sea so that the model can simulate the initiation of convection. Also included in the model are parameterizations of mesoscale ice phase and moisture processes and longwave and shortwave radiation with a diurnal cycle. This allows use of the model to test the relative importance of various heating mechanisms to the stratiform cloud deck, which typically occupies several hundred kilometers of the domain. Frank and Cohen's cumulus parameterization scheme is employed to represent vital unresolved vertical transports in the convective area. The major conclusions are: Ice phase processes are important in determining the level of maximum large-scale heating and vertical motion because there is a strong anvil componen...

Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale two-dimensional model [presentation]

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

Driven by the visions of Internet of Things and 5G communications, recent years have seen a paradigm shift in mobile computing, from the centralized mobile cloud computing toward mobile edge computing (MEC). The main feature of MEC is to push mobile computing, network control and storage to the network edges (e.g., base stations and access points) so as to enable computation-intensive and latency-critical applications at the resource-limited mobile devices. MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision. The promised gains of MEC have motivated extensive efforts in both academia and industry on developing the technology. A main thrust of MEC research is to seamlessly merge the two disciplines of wireless communications and mobile computing, resulting in a wide-range of new designs ranging from techniques for computation offloading to network architectures. This paper provides a comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management. We also discuss a set of issues, challenges, and future research directions for MEC research, including MEC system deployment, cache-enabled MEC, mobility management for MEC, green MEC, as well as privacy-aware MEC. Advancements in these directions will facilitate the transformation of MEC from theory to practice. Finally, we introduce recent standardization efforts on MEC as well as some typical MEC application scenarios.

A Survey on Mobile Edge Computing: The Communication Perspective

Driven by the visions of Internet of Things and 5G communications, recent years have seen a paradigm shift in mobile computing, from the centralized Mobile Cloud Computing towards Mobile Edge Computing (MEC). The main feature of MEC is to push mobile computing, network control and storage to the network edges (e.g., base stations and access points) so as to enable computation-intensive and latency-critical applications at the resource-limited mobile devices. MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision. The promised gains of MEC have motivated extensive efforts in both academia and industry on developing the technology. A main thrust of MEC research is to seamlessly merge the two disciplines of wireless communications and mobile computing, resulting in a wide-range of new designs ranging from techniques for computation offloading to network architectures. This paper provides a comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management. We also present a research outlook consisting of a set of promising directions for MEC research, including MEC system deployment, cache-enabled MEC, mobility management for MEC, green MEC, as well as privacy-aware MEC. Advancements in these directions will facilitate the transformation of MEC from theory to practice. Finally, we introduce recent standardization efforts on MEC as well as some typical MEC application scenarios.

Owing to the multiple antennas equipped at modern Wi-Fi infrastructures, the angle-of-arrival (AoA) based indoor localization systems have successfully achieved the accuracy of tens of centimeters. However, the high accuracy is acquired at the cost of employing the additional resources in the domains of frequency, space or time, which requires complex processing and hinders the practical application. In this paper, we present the design and implementation of RcLoc, which takes full advantages of the flexible array orientations and receiver positions, based on limited resources. Particularly, RcLoc devises a receiver configuration scheme for guiding the system deployment. Optimized array orientation could effectively improve the AoA estimation accuracy and well-designed receiver positions contribute to the Cramer-Rao lower bound of localization error. In the stage of system realization, we further devise an array calibration method to calibrate the actual array and develop an improved AoA estimation algorithm, which make RcLoc robust to the array arrangement. We prototype RcLoc on commodity Wi-Fi devices without manual intervention. Comprehensive experiments in a multipath-rich indoor environment show that RcLoc achieves a median localization accuracy of 0.4 m, which provides useful insights for receiver deployment.

Accurate Indoor Localization Assisted With Optimizing Array Orientations and Receiver Positions

Topology control with per-node transmission power adjustment is an effective way to extend network lifetime. However, due to the commonly used assumption of homogeneous wireless networks with uniform maximal transmission power, most topology control algorithms suffer from performance degradations in practical applications where physical characteristics of each node may be different. Hence, it is valuable to take heterogeneous networks into consideration. In such an environment, however, most of existing algorithms mainly consider the energy consumption caused by transmitting, meanwhile ignore the residual energy of network nodes, thus in fact they can not balance energy consumption efficiently. In this paper, a localized distributed topology control algorithms ESATC (Energy-aware Self-Adjust Topology Control) is proposed for extending network lifetime of heterogeneous wireless Ad Hoc networks. Based on overall consideration of power consumption and residual energy of two end nodes, ESATC builds a dynamic network topology that changes with the variation of node energy. Without location information, each node self-adjusts its transmission power according to the network information collected locally, which makes our algorithm suit for large scale networks. Theoretic analysis and experiment results show that ESATC provides routing with an underlying topology with bi-directional reachability and minimum-cost property. Compared with other algorithms, it can extend the lifetime of networks dramatically.

Energy-Aware Self-Adjusted Topology Control Algorithm for Heterogeneous Wireless Ad Hoc Networks

Interference Mitigation and Energy Management in 5G Heterogeneous Cellular Networks

This paper studies the joint transmit beamforming optimization in the downlink of a single-cell multiuser distributed antenna system. Due to the distributed nature of transmit antennas, the signals received from different distributed antenna units (DAUs) will experience various transmission delays, and it is difficult to realize accurate symbol-level time synchronization at the user terminal. Thus, we turn to finding a robust joint transmit beamforming algorithm by replacing the received signal-to-interference-plus-noise ratio (SINR) with its lower-bound value. Moreover, the joint transmission incurs huge amount of data sharing among DAUs. Under the per-DAU maximum transmit power constraint, we aim to minimize the system backhaul overhead while satisfying the quality-of-service (QoS) requirement of each user. Since the backhaul overhead minimization requires the transmit beam vectors to have a group sparse structure and is NP-hard, we first make a convex relaxation and then apply the reweighted method to improve the sparsity of the beam vectors. Furthermore, an admission control scheme is applied to guarantee the feasibility of the problem, which iteratively removes the unsatisfied user with the worst quality of experience (QoE) away from the system. Simulation results show that our proposed robust algorithm can achieve a much better performance than the traditional nonrobust algorithm when time asynchronism is less than 30% of the symbol duration and can significantly reduce the system backhaul overhead by designing group sparse transmit beam vectors.

Robust Joint Transmit Beamforming With QoS Guarantees in Time-Asynchronous DAS

Wireless body area network (WBAN) is an emerging short-range wireless communication network with sensor nodes located on, in or around the human body for healthcare, entertainment and ubiquitous computing. In WBANs, energy is severely constrained which is the prime consideration in the medium access control (MAC) protocol design. In this paper, we propose a novel MAC protocol named Energy-efficient Relay MAC with dynamic Power Control (ERPC-MAC) to save energy consumption. Without relying on the additional devices, ERPC-MAC employs relaying nodes to provide relay service for nodes which consume energy fast. Accordingly the superframe adjustment is performed and then the network topology can be smoothly switched from single-hop to multi-hop. Moreover, for further energy saving and reliability improvement, the dynamic power control is introduced to adjust the power level whenever a node transmits its packets to the coordinator or the relaying node. To the best of the authors’ knowledge, this is the first effort to integrate relay, topology adjustment and power control to improve the network performance in a WBAN. Comprehensive simulations are conducted to evaluate the performance. The results show that the ERPC-MAC is more superior to the existing standard and significantly prolongs the network lifetime.

Jiandong Li

Papers

Accurate Indoor Localization Assisted With Optimizing Array Orientations and Receiver Positions

Energy-Aware Self-Adjusted Topology Control Algorithm for Heterogeneous Wireless Ad Hoc Networks

Interference Mitigation and Energy Management in 5G Heterogeneous Cellular Networks

Robust Joint Transmit Beamforming With QoS Guarantees in Time-Asynchronous DAS

Energy-efficient Relay MAC with Dynamic Power Control in Wireless Body Area Networks