A Dynamic Network Game of the Fintech Industry

Economies of scale,economies of scope,and technology spillover are decisive eco-nomic elements that are crucial to the development in the Fintech industry.Thesepositive externalities are often realized through network links.In this paper,we presenta dynamic network offinancialfirms which exhibits these decisive elements.Thenetwork game equilibria are characterized.A Pareto efficient solution involving col-laboration of allfirms is provided.To obtain a fair-share distribution of cooperativegains,the Shapley value is adopted as the sharing mechanism.Payoff distributionmechanisms which guarantee the fulfilment of the Shapley value distribution in eachstage of the cooperation duration are derived.

Distributed Nash Equilibrium Seeking for General Networked Games With Bounded Disturbances

This paper is concerned with anti-disturbance Nash equilibrium seeking for games with partial information.First,reduced-order disturbance observer-based algorithms are proposed to achieve Nash equilibrium seeking for games with firstorder and second-order players,respectively.In the developed algorithms,the observed disturbance values are included in control signals to eliminate the influence of disturbances,based on which a gradient-like optimization method is implemented for each player.Second,a signum function based distributed algorithm is proposed to attenuate disturbances for games with secondorder integrator-type players.To be more specific,a signum function is involved in the proposed seeking strategy to dominate disturbances,based on which the feedback of the velocity-like states and the gradients of the functions associated with players achieves stabilization of system dynamics and optimization of players'objective functions.Through Lyapunov stability analysis,it is proven that the players'actions can approach a small region around the Nash equilibrium by utilizing disturbance observerbased strategies with appropriate control gains.Moreover,exponential(asymptotic)convergence can be achieved when the signum function based control strategy(with an adaptive control gain)is employed.The performance of the proposed algorithms is tested by utilizing an integrated simulation platform of virtual robot experimentation platform(V-REP)and MATLAB.

A Matrix Approach to the Modeling and Analysis of Networked Evolutionary Games With Time Delays

Using the semi-tensor product method, this paper investigates the modeling and analysis of networked evolutionary games(NEGs) with finite memories, and presents a number of new results. Firstly, a kind of algebraic expression is formulated for the networked evolutionary games with finite memories, based on which the behavior of the corresponding evolutionary game is analyzed. Secondly, under a proper assumption, the existence of Nash equilibrium of the given networked evolutionary games is proved and a free-type strategy sequence is designed for the convergence to the Nash equilibrium. Finally, an illustrative example is worked out to support the obtained new results.

A Game-Theoretic Approach to Elastic Control in Software-Defined Networking

Elastic control could balance the distributed control plane in Software-Defined Networking(SDN). Dynamic switch migration has been proposed to achieve it. However, existing schemes mainly focus on how to execute migration operation, but not why. This paper designs a decision-making mechanism based on zero-sum game theory to reelect a new controller as the master for migrated switches. It first chooses a switch for migration in the heavy controller which invites its neighbors as the game players to compete for the master role of this switch in the game-playing field(GPF) which is an occasional and loose domain for game-playing. Second, based on the concept of GPF, we design a decentralized strategy to play the game and determine which player as the final master. We implement it by extending the Open Flow protocol. Finally, numerical results demonstrate that our distributed strategy can approach elastic control plane with better performance.

Distributed power control algorithm based on game theory for wireless sensor networks

Energy saving is the most important issue in research and development for wireless sensor networks. A power control mechanism can reduce the power consumption of the whole network. Because the character of wireless sensor networks is restrictive energy, this paper proposes a distributed power control algorithm based on game theory for wireless sensor networks which objects of which are reducing power consumption and decreasing overhead and increasing network lifetime. The game theory and OPNET simulation shows that the power control algorithm converges to a Nash Equilibrium when decisions are updated according to a better response dynamic.

Fuzzy mathematics and game theory based D2D multicast network construction

Device to device(D2 D) multi-hop communication in multicast networks solves the contradiction between high speed requirements and limited bandwidth in regional data sharing communication services. However, most networking models demand a large control overhead in eNodeB. Moreover, the topology should be calculated again due to the mobility of terminals, which causes the long delay. In this work, we model multicast network construction in D2 D communication through a fuzzy mathematics and game theory based algorithm. In resource allocation, we assume that user equipment(UE) can detect the available frequency and the fuzzy mathematics is introduced to describe an uncertain relationship between the resource and UE distributedly, which diminishes the time delay. For forming structure, a distributed myopic best response dynamics formation algorithm derived from a novel concept from the coalitional game theory is proposed, in which every UE can self-organize into stable structure without the control from eNodeB to improve its utilities in terms of rate and bit error rate(BER) while accounting for a link maintenance cost, and adapt this topology to environmental changes such as mobility while converging to a Nash equilibrium fast. Simulation results show that the proposed architecture converges to a tree network quickly and presents significant gains in terms of average rate utility reaching up to 50% compared to the star topology where all of the UE is directly connected to eNodeB.

Evolutionary snowdrift game on heterogeneous Newman-Watts small-world network

We study the evolutionary snowdrift game in a heterogeneous Newman-Watts small-world network. The heterogeneity of the network is controlled by the number of hubs. It is found that the moderate heterogeneity of the network can promote the cooperation best. Besides, we study how the hubs affect the evolution of cooperative behaviours of the heterogeneous Newman-Watts small-world network. Simulation results show that both the initial states of hubs and the connections between hubs can play an important role. Our work gives a further insight into the effect of hubs on the heterogeneous networks.

A Game Theoretic Approach for Energy-Efficient In-Network Caching in Content-Centric Networks

Recently,content-centric networking(CCN) has become a hot research topic for the diffusion of contents over the Internet.Most existing works on CCN focus on the improvement of network resource utilization.Consequently,the energy consumption aspect of CCN is largely ignored.In this paper,we propose a distributed energyefficient in-network caching scheme for CCN,where each content router only needs locally available information to make caching decisions considering both caching energy consumption and transport energy consumption.We formulate the in-network caching problem as a non-cooperative game.Through rigorous mathematical analysis,we prove that pure strategy Nash equilibria exist in the proposed scheme,and it always has a strategy profile that implements the socially optimal configuration,even if the routers are self-interested in nature.Simulation results are presented to show that the distributed solution is competitive to the centralized scheme,and has superior performance compared to other popular caching schemes in CCN.Besides,it exhibits a fast convergence speed when the capacity of content routers varies.

A Game Theoretic Approach for Inter-Network Interference Mitigation in Wireless Body Area Networks

Wireless Body Area Network(WBAN) is an emerging technology to provide real-time health monitoring and ubiquitous healthcare services. In many applications, multiple wireless body area networks have to coexist in a small area, resulting in serious inter-network interference. This not only reduces network reliability that is especially important in emergency medical applications, but also consumes more power of WBANs. In this paper, an inter-network interference mitigation approach based on a power control algorithm is proposed. Power control is modeled as a non-cooperative game, in which both inter-network interference and energy efficiency of WBANs are considered. The existence and uniqueness of Nash Equilibrium in the game are proved, and an optimal scheme based on best response is proposed to find its Nash Equilibrium. By coordinating the transmission power levels among networks under interference environment, the total system throughput can be increased with minimum power consumed. The effectiveness of the proposed method has been illustrated by simulation results, where the performance of the proposed approach is evaluated in terms of overall utility and power efficiency and convergence speed.

Bioinformatic Game Theory and Its Application to Biological Affinity Networks

The exact evolutionary history of any set of biological taxa is unknown, and all phylogenetic reconstructions are approximations. The problem becomes harder when one must consider a mix of vertical and lateral phylogenetic signals. In this paper we propose a game theoretic approach to constructing biological networks. The key hypothesis is that evolution is driven by distinct mechanisms that seek to maximize two competing objectives, taxonomic conservation and diversity. One branch of the mathematical theory of games is brought to bear. It translates this evolutionary game hypothesis into a mathematical model in two-player zero-sum games, with the zero-sum assumption conforming to one of the fundamental constraints in nature in mass and energy conservation. We demonstrate why and how a mechanistic and localized adaptation to seek out greater information for conservation and diversity may always lead to a global Nash equilibrium in phylogenetic affinity. Our game theoretic method, referred to as bioinformatic game theory, is used to construct network clusters. As an example, we applied this method to clustering of a multidomain protein family. The protein clusters identified were consistent with known protein subfamilies, indicating that this game-theoretic approach provides a new framework in biological sequence analysis, especially in studying gene-genome and domain-protein relationships.

Networked Evolutionary Model of Snow-Drift Game Based on Semi-Tensor Product

This paper investigates the networked evolutionary model based on snow-drift game with the strategy of rewards and penalty. Firstly, by using the semi-tensor product of matrices approach, the mathematical model of the networked evolutionary game is built. Secondly, combined with the matrix expression of logic, the mathematical model is expressed as a dynamic logical system and next converted into its evolutionary dynamic algebraic form. Thirdly, the dynamic evolution process is analyzed and the final level of cooperation is discussed. Finally, the effects of the changes in the rewarding and penalty factors on the level of cooperation in the model are studied separately, and the conclusions are verified by examples.

A Stackelberg Differential Game Based Bandwidth Allocation in Satellite Communication Network

In this paper, a Stackelberg differential game based approach is proposed to solve the bandwidth allocation problems in satellite communication network. All the satellites are divided into two groups, one has high download requirements, and the other one has low download requirements. Each satellites group has its own controller for bandwidth allocation, and can get payments from the satellites for the allocated resources. The relationships between the controllers and satellites are formed as a Stackelberg game. In our model, differential equation is introduced to describe the bandwidth dynamics for the whole satellite communication network. Combine the differential equation and Stackelberg game together, we can formulate the bandwidth allocation problems in satellite communication network as a Stackelber differential game. The solutions to the proposed game is solved based the Bellman dynamic equations. Numerical simulations are given to prove the effeteness and correctness of the proposed approach.

Clustering routing algorithm of wireless sensor networks based on Bayesian game

To avoid uneven energy consuming in wireless sen- sor networks, a clustering routing model is proposed based on a Bayesian game. In the model, Harsanyi transformation is introduced to convert a static game of incomplete information to the static game of complete but imperfect information. In addition, the existence of Bayesian nash equilibrium is proved. A clustering routing algorithm is also designed according to the proposed model, both cluster head distribution and residual energy are considered in the design of the algorithm. Simulation results show that the algorithm can balance network load, save energy and prolong network lifetime effectively.

Using the Cooperative Game for Service Placement of Virtual Network Functions

To address the issues that middleboxes as a fundamental part of today's networks are facing, Network Function Virtualization(NFV)has been recently proposed, which in essence asserts to migrate hardware-based middleboxes into software-based virtualized function entities.Due to the demands of virtual services placement in NFV network environment, this paper models the service amount placement problem involving with the resources allocation as a cooperative game and proposes the placement policy by Nash Bargaining Solution(NBS). Specifically,we first introduce the system overview and apply the rigorous cooperative game-theoretic guide to build the mathematical model, which can give consideration to both the responding efficiency of service requirements and the allocation fairness.Then a distributed algorithm corresponding to NBS is designed to achieve predictable network performance for virtual instances placement.Finally, with simulations under various scenarios,the results show that our placement approach can achieve high utilization of network through the analysis of evaluation metrics namely the satisfaction degree and fairness index. With the suitable demand amount of services, the average values of two metrics can reach above 90%. And by tuning the base placement, our solution can enable operators to flexibly balance the tradeoff between satisfaction and fairness of resourcessharing in service platforms.

A Dynamic Distributed Spectrum Allocation Mechanism Based on Game Model in Fog Radio Access Networks

With the explosive growth of highspeed wireless data demand and the number of mobile devices, fog radio access networks(F-RAN) with multi-layer network structure becomes a hot topic in recent research. Meanwhile, due to the rapid growth of mobile communication traffic, high cost and the scarcity of wireless resources, it is especially important to develop an efficient radio resource management mechanism. In this paper, we focus on the shortcomings of resource waste, and we consider the actual situation of base station dynamic coverage and user requirements. We propose a spectrum pricing and allocation scheme based on Stackelberg game model under F-RAN framework, realizing the allocation of resource on demand. This scheme studies the double game between the users and the operators, as well as between the traditional operators and the virtual operators, maximizing the profits of the operators. At the same time, spectrum reuse technology is adopted to improve the utilization of network resource. By analyzing the simulation results, it is verified that our proposed scheme can not only avoid resource waste, but also effectively improve the operator's revenue efficiency and overall network resource utilization.

Differential Game Based Link Resource Management for Next Generation Optical Network

In this paper, we investigate the link resource management problem for optical networks, to achieve the resource cost during the information transmission. We use the differential game to formulate the cost control problem for the link resource management, to minimize the resource allocation cost functions, which dynamic behaviours are described by differential equations. Each link controls its transmission bandwidth based on the Nash equilibriums of the differential game. The effectiveness of the proposed model is given through numerical simulations.

Fairness Assessment in Networked Games with Olfactory and Haptic Senses

In this paper, we carry out QoE (Quality of Experience) assessment of fairness between players in a networked balloon bursting game with olfactory and haptic senses. We also make a comparison of the fairness among different types of networked games with olfactory and haptic senses in the assessment. Then, we clarify the differences owing to usage of olfactory and haptic senses among the games. As a result, we illustrate that the fairness is largely affected by the delay difference, and we also demonstrate that the allowable range depends on the type of games, type of senses which are employed in the games, and the play methods.

QoE Assessment of Fairness between Players in Networked Virtual 3D Objects Identification Game Using Haptic, Olfactory, and Auditory Senses

In this paper, we carry out QoE (Quality of Experience) assessment to investigate influences of olfactory and auditory senses on fairness for a networked virtual 3D object identification game with haptics. In the game, two players try to identify objects which are placed in a shared 3D virtual space. In the assessment, we carry out the game in four cases. Smells and sounds are presented in the first case, only sounds are done in the second case, and only smells are done in the third case. In the last case, we present neither smell nor sound. As a result, we demonstrate that the fairness deteriorates more largely as the difference in conditions between two users becomes larger.

Using Bayesian Game Model for Intrusion Detection in Wireless Ad Hoc Networks

Wireless ad ho network is becoming a new research fronter, in which security is an important issue. Usually some nodes act maliciously and they are able to do different kinds of Denial of Service (Dos). Because of the limited resource, intrusion detection system (IDS) runs all the time to detect intrusion of the attacker which is a costly overhead. In our model, we use game theory to model the interactions between the intrusion detection system and the attacker, and a realistic model is given by using Bayesian game. We solve the game by finding the Bayesian Nash equilibrium. The results of our analysis show that the IDS could work intermittently without compromising on its effectiveness. At the end of this paper, we provide an experiment to verify the rationality and effectiveness of the proposed model.