A Game-Theoretic Perspective on Resource Management for Large-Scale UAV Communication Networks

As a result of rapid development in electronics and communication technology,large-scale unmanned aerial vehicles(UAVs)are harnessed for various promising applications in a coordinated manner.Although it poses numerous advantages,resource management among various domains in large-scale UAV communication networks is the key challenge to be solved urgently.Specifically,due to the inherent requirements and future development trend,distributed resource management is suitable.In this article,we investigate the resource management problem for large-scale UAV communication networks from game-theoretic perspective which are exactly coincident with the distributed and autonomous manner.By exploring the inherent features,the distinctive challenges are discussed.Then,we explore several gametheoretic models that not only combat the challenges but also have broad application prospects.We provide the basics of each game-theoretic model and discuss the potential applications for resource management in large-scale UAV communication networks.Specifically,mean-field game,graphical game,Stackelberg game,coalition game and potential game are included.After that,we propose two innovative case studies to highlight the feasibility of such novel game-theoretic models.Finally,we give some future research directions to shed light on future opportunities and applications.

The Game-Theoretical Approach to the Simulation of Sustainable Development Strategies

Choosing a strategy for sustainable development is national level aimed at the simultaneous fulfillment of economic, a fundamental problem that requires non-trivial approaches at the social and environmental goals. This contradiction is possible to be adequately described in the complex game-theoretic models. But analysis of them is complicated by the problems of algorithmic solvability and the payoff functions construction. Also, the volume of data required creates considerable complexity increased by the conditions of situations uncertainty and conflict. At the same time, international organizations, such as UN （United Nations）, ITU （International Telecommunications Union）, are widely used index system. Indices, built on the aggregation of elementary indicators, allow the estimation of the components of the system and its overall development. The paper discusses the basic concepts of game-theoretic approach to the problems of finding strategies for sustainable development, using indicative analysis techniques. In the proposed approach, estimating of sustainability is considered as the result of finding the optimal values of the payoff functions in general game-theoretical model where the players are matched indices. The interests of the player are to increase of the corresponding index and the optimal situation is implemented as a set of optimal payoff functions values. This allows switching from processing of large amounts of data describing the behavior of the ecological-economic system by the aid of indicators to aggregate estimations, which significantly reduce the sample, and also facilitates the interpretation of the results.

Game-theoretic Applications for Decision-making Behavior on the Energy Demand Side:a Systematic Review

As an essential characteristic of the smart grid,energy demand users are being transformed from passive roles to active decision-makers.To analyze their decision-making behaviors,game theory has been widely applied on the demand side.This paper focuses on the classification and in-depth analysis of recent studies that propose game-theoretic approaches for decision optimi-zation of multiple demand users.This analysis classifies scenarios into various game participant categories,in-cluding distributed energy prosumers,small-and mid-dle-sized users,and large energy consumers.The in-depth analysis of each scenario,covering non-cooperative game,cooperative game,Stackelberg game,Bayesian game,and evolutionary game,is conducted by analyzing market operation mechanisms,model assumptions/formulations,and solution methods.Based on a comprehensive review of such studies,it is concluded that game-theoretic appli-cations on the demand side can benefit both the grid and the users,e.g.,reductions in the peak-to-average ratios and energy costs of the users.The prospects for the ap-plications of game theory on the demand side are dis-cussed,including application scenarios and methodologies.The overview presented in this paper is expected to sup-port researchers in comprehending typical game-theoretic concepts,keeping with the latest research developments,and identifying new and innovative appli-cations for the energy demand side.Index Terms—Energy demand side,game theory,Game-theoretic application,demand response,deci-sion-making behavior.

Some Game-Theoretic Characterizations for Rapid Filters on ω

Infinite game is a power tool in studying various objects and finding descriptions of some properties of filters in mathematics.Game-theoretic characterizations for meager filters,Q-filters and Ramsey filters were obtained by Tomek Bartoszynski,Claude Laflamme and Marion Scheepers.In this paper,the authors obtain two game-theoretic characterizations for rapid filters onω.

Hybrid model of inter-stage spectrum trading in multistage game-theoretic framework

Dynamic spectrum access（DSA）,consisting of spectrum sharing and spectrum trading stage,becomes a promising approach to increase the efficiency of spectrum usage and system performance.In this paper,from the perspective of individual interest optimization,we focus on strategy adaptation of network users and their interaction in spectrum trading process.Considering adverse effects on decision-making accuracy and the fairness among network users via local information acquirement,a hybrid game model based on global information of relevant spectrum is proposed to formulate intelligent behaviors of both primary and secondary users.Specifically,by using the evolutionary game theory,a spectrum-selection approach for the evolution process of secondary users is designed to converge to the evolutionary equilibrium gradually.Moreover,competition among primary users is modeled as a non-cooperative game and an iterative algorithm is employed to achieve the Nash equilibrium.The simulation results show that the proposed hybrid game model investigates network dynamics under different network parameter settings.

Honeypot Game Theory against DoS Attack in UAV Cyber

A space called Unmanned Aerial Vehicle(UAV)cyber is a new environment where UAV,Ground Control Station(GCS)and business processes are integrated.Denial of service(DoS)attack is a standard network attack method,especially suitable for attacking the UAV cyber.It is a robust security risk for UAV cyber and has recently become an active research area.Game theory is typically used to simulate the existing offensive and defensive mechanisms for DoS attacks in a traditional network.In addition,the honeypot,an effective security vulnerability defense mechanism,has not been widely adopted or modeled for defense against DoS attack UAV cyber.With this motivation,the current research paper presents a honeypot game theorymodel that considersGCS andDoS attacks,which is used to study the interaction between attack and defense to optimize defense strategies.The GCS and honeypot act as defenses against DoS attacks in this model,and both players select their appropriate methods and build their benefit function models.On this basis,a hierarchical honeypot and G2A network delay reward strategy are introduced so that the defender and the attacker can adjust their respective strategies dynamically.Finally,by adjusting the degree of camouflage of the honeypot for UAV network services,the overall revenue of the defender can be effectively improved.The proposed method proves the existence of a mixed strategy Nash equilibrium and compares it with the existing research on no delay rewards and no honeypot defense scheme.In addition,this method realizes that the UAV cyber still guarantees a network delay of about ten milliseconds in the presence of a DoS attack.The results demonstrate that our methodology is superior to that of previous studies.

The impacts of market reform on the market penetration of natural gas-fired electricity and renewable energy in China

Natural gas-fired electricity(NGFE) is expected to play a more important role in the future due to its characteristics of low pollution, high efficiency and flexibility. However, its development in China is impeded by its high regulation price compared with coal power. Market reform is therefore of vital importance to promote the penetration of NGFE. The objective of this study is to analyze the impacts of market reform and the renewable electricity(RE) subsidy policy on the promotion of NGFE and RE. A dynamic game-theoretic model is developed to analyze the interaction among the NG supplier, the power sector and the power grid. Three scenarios are proposed with different policies, including a fixed regulation price of NG and electricity, real-time pricing(RTP) of NG and electricity, and subsidy targeted at RE. The results show that:(1) market reform can sharply decrease the NG price and consequently promote the development of NGFE and RE;(2) subsidy targeted at RE not only promotes the penetration of NGFE and RE, but also increases the utilization ratio of renewables significantly;(3) market reform and the subsidy also enhance consumers’ welfare by reducing their power consumption expenditure.

Application of Monetary Unit Sampling Based on Extended Audit Game

On account of the lack of monetary unit sampling( MUS), an extended audit game model based on uncertainty information,which centers on audit risk and combines audit game with statistical sampling,is established to improve the effectiveness of audit risks analysis and sampling errors control. In this paper,an example concerning practical problems is given to demonstrate the process of extended audit game and confirm the truth of the effectiveness of the method. Not only does this method enhance the role of audit technology and the extension of audit procedures in deterring material irregularities,but also helps the auditors measure and control audit risk and sample sizes under uncertainty,conducive to improving the effect of cost control,risk evaluation,and decisionmaking optimization in audit sampling.

Green Environment: Decision-Making and Power Utility Optimization towards Smart-Grid Options

Decision-making toward prudent energy conservation is a primary issue in the power utility management while con-ceiving green environment. Presented in this paper are relevant considerations and prudent ways of decision-making thereof. Examples are furnished to illustrate the underlying considerations and are discussed using practical examples. Specifically green ambient is considered and the underlying payoff resulting from each combination of strategies adopted (or courses of action taken) by the technology-option participants is evaluated. Game-theoretic pursuits are followed.

A Comprehensive Survey on STP Approach to Finite Games

Nowadays the semi-tensor product(STP)approach to finite games has become a promising new direction.This paper provides a comprehensive survey on this prosperous field.After a brief introduction for STP and finite(networked)games,a description for the principle and fundamental technique of STP approach to finite games is presented.Then several problems and recent results about theory and applications of finite games via STP are presented.A brief comment about the potential use of STP to artificial intelligence is also proposed.

ORDERED WEIGHTED AVERAGING AGGREGATION METHOD FOR PORTFOLIO SELECTION

Portfolio management is a typical decision making problem under incomplete,sometimes unknown, information. This paper considers the portfolio selection problemsunder a general setting of uncertain states without probability. The investor's preferenceis based on his optimum degree about the nature, and his attitude can be described by anOrdered Weighted Averaging Aggregation function. We construct the OWA portfolio selection model, which is a nonlinear programming problem. The problem can be equivalentlytransformed into a mixed integer linear programming. A numerical example is given andthe solutions imply that the investor's strategies depend not only on his optimum degreebut also on his preference weight vector. The general game-theoretical portfolio selectionmethod, max-min method and competitive ratio method are all the special settings of thismodel.