Infrastructure topology optimization under competition through cross-entropy

In this article, we study a two-level non-cooperative game between providers acting on the same geographic area. Each provider has the opportunity to set up a network of stations so as to capture as many consumers as possible. Its deployment being costly, the provider has to optimize both the number of settled stations as well as their locations. In the first level each provider optimizes independently his infrastructure topology while in the second level they price dynamically the access to their network of stations. The consumers’ choices depend on the perception (in terms of price, congestion and distances to the nearest stations) that they have of the service proposed by each provider. Each providers' market share is then obtained as the solution of a fixed point equation since the congestion level is supposed to depend on the market share of the provider, which increases with the number of consumers choosing the same provider. We prove that the two-stage game admits a unique equilibrium in price at any time instant. An algorithm based on the cross-entropy method is proposed to optimize the providers' infrastructure topology and it is tested on numerical examples providing economic interpretations.     

An MPEC formulation and its cutting constraint algorithm for continuous network design problem with multi-user classes

Continuous network design problem (CNDP) is to determine the set of link capacity expansions and the corresponding equilibrium flows for which the measures of performance index for the network is optimal. Conventionally, CNDP assumed users to be homogeneous, that is, all travelers on the same link of the network are identical insofar as congestion effect and they have the same value of time (VOT). In fact, it does not accord with the real situation that all have the same VOT. So, multiple user classes with different VOT should be considered. This paper examines the CNDP with different VOT for multiple user classes, which is generally expressed as a mathematical programming with equilibrium constraint (MPEC). Then, the cut constraint algorithm (CCA) is presented to solve the problem. The numerical experiments on the examples from the literature are illustrated to demonstrate that our model and algorithm are feasible.     

The concert queueing game: strategic arrivals with waiting and tardiness costs

We consider the noncooperative choice of arrival times by individual users, who seek service at a first-come first-served queueing system that opens up at a given time. Each user wishes to obtain service as early as possible, while minimizing the expected wait in the queue. This problem was recently studied within a simplified fluid-scale model. Here, we address the unscaled stochastic system, assuming a finite (possibly random) number of homogeneous users, exponential service times, and linear cost functions. In this setting, we establish that there exists a unique Nash equilibrium, which is symmetric across users, and characterize the equilibrium arrival-time distribution of each user in terms of a corresponding set of differential equations. We further establish convergence of the Nash equilibrium solution to that of the associated fluid model as the number of users is increased. We finally consider the price of anarchy in our system and show that it exceeds 2, but converges to this value for a large population size.     

On Cost Allocation in Hub-Like Networks

We consider telecommunication network design in which each pair of nodes can communicate via a direct link and the communication flow can be delivered through any path in the network. The cost of flow through each link is discounted if and only if the amount of flow exceeds a certain threshold. This exploitation of economies of scale encourages the concentration of flows and use of relatively small number of links. We will call such networks hub-like networks. The cost of services delivered through a hub-like network is distributed among its users who may be individuals or organizations with possibly conflicting interests. The cooperation of these users is essential for the exploitation of economies of scale. Consequently, there is a need to find a fair distribution of the cost of providing the service among users of such network. In order to describe this cost allocation problem we formulate the associated cooperative game, to be referred to as the hub-like game. Special attention is paid to users' contribution to economies of scale. We then demonstrate that certain cost allocation solutions (the core and the nucleolus of the hub-like game), which provide users with the incentive to cooperate, can be efficiently characterized.     

An Ergodic Algorithm for the Power-Control Games for CDMA Data Networks

In this paper, we consider power control for the uplink of a direct-sequence code-division multiple-access data network. In the uplink, the purpose of power control is for each user to transmit enough power so that it can achieve the required quality of service without causing unnecessary interference to other users in the system. One method that has been very successful in solving this purpose for power control is the game-theoretic approach. The problem for power control is modified as a Nash equilibrium problem in which each user can choose its transmit power in order to maximize its own utility, and a Nash equilibrium is an ideal solution of the power-control game. We present a noncooperative power-control game in which each user can choose the transmit power in a way that it gets the sufficient signal-to-interference-plus-noise ratio and maximizes its own utility. To ensure the existence of a solution, we also propose the variational inequality problem which is connected with the proposed game. On a linear receiver, we deal with the matched filter receiver. Next we present a new ergodic algorithm for the proposed power control because the existing iterative algorithms can not be applied effectively to the proposed power control. We also present convergence analysis for the proposed algorithm. In addition, applying the proposed algorithm to the proposed power control, we provide numerical examples for the transmit power, the signal-to-interference-plus-noise ratio and so on. Numerical results for the proposed algorithm shall show that as compared with the existing power-control game and its method, all users in the network can enjoy the sufficient signal-to-interference-plus-noise ratio and achieve the required quality of service.      

多用户类多准则交通分配的势博弈与拥挤定价

交通管理者在解决路网拥挤问题时,并不知道出行者的出行效用,同时管理者难以对出行者的路径选择行为做出准确的观测.运用势博弈理论分析多用户类多准则交通行为的演化过程,得到了固定需求和弹性需求情形下的可容许动态(一种刻画出行者通过转换路径增加当前效用的近似调整行为的演化动态),证明当路段时间函数和逆需求函数为严格单调、连续、可微时,所对应的交通分配是势博弈问题的惟一Nash均衡点.进一步研究了固定需求下的可变拥挤道路收费问题,得到了在当前系统状态下实现系统最优交通分配的拥挤收费水平.     

双模式交通网络中的ATIS信息定价研究

先进的出行者信息系统(ATIS)是一种服务商品,已有的研究多从提高市场占有率的角度对单模式交通网络中的ATIS进行信息定价。多模式交通网络中影响ATIS市场占有率的因素众多,而且ATIS的提供成本往往与信息质量和使用规模同时相关。因此,信息定价问题应从ATIS服务提供商利润最大化的角度进行研究。本文把ATIS信息的单次使用费用和ATIS的信息质量同时作为决策变量,将双模式路网中ATIS的定价问题描述为一个双层规划模型。其中,混合用户均衡模型为下层模型,收益模型为上层模型。然后,基于上海市虹口区的路网数据,对下层模型进行了数值分析,并讨论了相关经济效益问题。此外,本文提出了求解下层模型的MSAF算法,并进一步嵌套了粒子群(PSO)算法,最终得到ATIS服务提供商的最优ATIS信息定价和信息质量提供方案。     

开源软件服务提供商的市场策略及社区参与策略研究

开源软件由开源社区内的成员自发参与并协同完成开发,是一种高效的、有别于传统的软件生产模式。开源社区的主要成员有软件用户及开源软件服务提供商。本文通过构建三阶段模型,研究了服务提供商的市场策略及开源社区内用户创新对服务提供商参与策略的影响。研究发现:(1)若市场上高价值用户较少,服务提供商应采取低质量、低价格的市场策略,否则应采取高质量、高价格策略。(2)服务提供商要避免搭便车行为,即为了增加服务利润,它必须投入资源参与开源社区、提高软件质量。(3)当服务市场上目标用户较多且开源社区内用户参与动机较强时,服务提供商应采取高参与策略,否则采取低参与策略。本文的研究对服务提供商如何利用和参与开源社区具有指导意义。     

基于多层博弈的智能电网住宅电力实时需求响应机制

通过建立多层博弈模型刻画智能电网系统中电力公司、家庭电力管理中心和家庭内各个电器设备间的电力实时需求响应过程。在此模型中,每个时段电力公司将电价通知各个家庭,每个家庭的电力管理中心接收到实时电价信息后为家庭内各个电器设备分配虚拟电价,各个设备则确定各自最优用电量并将其反馈给家庭电力管理中心,由其确定该家庭总用电量并发送至电力公司,电力公司再计算得到最优电价。证明了所建多层博弈模型的均衡存在唯一性,并得到均衡解。仿真结果验证了模型的有效性,并给出其实际应用价值。     

Pricing peer-produced services: Quality,capacity, and competition issues

Peer production has played an important role in the economics of Web 2.0 related services in which user participation and contribution become the main driving dynamics. However, the quality of peer-produced services is uncertain because of inherently decentralized and heterogeneous participants. In the paper, utilizing reliability and game theoretic models, we develop a QoS measure and pricing schemes for this emerging type of service under various market structures. Our results suggest that a monopolistic platform provider has no incentive to offer multiple quality classes of service. Two competing platform providers may offer identical service contracts but still receive non-negative profit. If they offer heterogeneous service contracts, the provider with the lower quality service may provide higher quality than he advertises. This research contributes to the literature with a number of unique and interesting implications for the issues of service contract design, capacity planning, and market interactions for operations of community-based or peer-produced services.     

A stackelberg game approach to distributed spectrum management

We consider a cognitive radio system with one primary (licensed) user and multiple secondary (unlicensed) users. Given the interference temperature constraint, the secondary users compete for the available spectrum to fulfill their own communication need. Borrowing the concept of price from market theory, we develop a decentralized Stackelberg game formulation for power allocation. In this scheme, the primary user (leader) announces prices for the available tones such that a system utility is maximized. Using the announced prices, secondary users (followers) compete for the available bandwidth to maximize their own utilities. We show that this Stackelberg game is polynomial time solvable under certain channel conditions. When the individual power constraints of secondary users are inactive (due to strict interference temperature constraint), the proposed distributed power control method is decomposable across the tones and unlike normal water-filling it respects the interference temperature constraints of the primary user. When individual power constraints are active, we propose a distributed approach that solves the problem under an aggregate interference temperature constraint. Moreover, we propose a dual decomposition based power control method and show that it solves the Stackelberg game asymptotically when the number of tones becomes large.     

Optimal static pricing for a tree network

We study the static pricing problem for a network service provider in a loss system with a tree structure. In the network, multiple classes share a common inbound link and then have dedicated outbound links. The motivation is from a company that sells phone cards and needs to price calls to different destinations. We characterize the optimal static prices in order to maximize the steady-state revenue. We report new structural findings as well as alternative proofs for some known results. We compare the optimal static prices versus prices that are asymptotically optimal, and through a set of illustrative numerical examples we show that in certain cases the loss in revenue can be significant. Finally, we show that static prices obtained using the reduced load approximation of the blocking probabilities can be easily obtained and have near-optimal performance, which makes them more attractive for applications.     

A Cournot–Nash–Bertrand game theory model of a service-oriented Internet with price and quality competition among network transport providers

This paper develops a game theory model of a service-oriented Internet in which profit-maximizing service providers provide substitutable (but not identical) services and compete with the quantities of services in a Cournot–Nash manner, whereas the network transport providers, which transport the services to the users at the demand markets, and are also profit-maximizers, compete with prices in Bertrand fashion and on quality. The consumers respond to the composition of service and network provision through the demand price functions, which are both quantity and quality dependent. We derive the governing equilibrium conditions of the integrated game and show that it satisfies a variational inequality problem. We then describe the underlying dynamics, and provide some qualitative properties, including stability analysis. The proposed algorithmic scheme tracks, in discrete-time, the dynamic evolution of the service volumes, quality levels, and the prices until an approximation of a stationary point (within the desired convergence tolerance) is achieved. Numerical examples demonstrate the modeling and computational framework.     

Service outsourcing under co-opetition and information asymmetry

Co-opetition refers to the phenomenon that firms simultaneously cooperate and compete in order to maximize their profits. This paper studies the contracting for an outsourcing supply chain (a user company vs. a service provider) in the presence of co-opetition and information asymmetry. The user company outsources part of his service capacity at a discount price to the service provider for sale. The service provider charges a commission for doing outsourcing work and competes with the user company for the service capacity to satisfy their respective demands. We solve for the service provider’s optimal commission decision and the user company’s optimal outsourcing decisions (outsourcing volume and price discount) when the user company has private information about his service capacity. Specifically, we highlight the following observations. For the service provider, a menu of two-part tariffs that consist of a fixed commission and a per-volume commission can reveal the true type of the user company’s capacity; the user company’s optimal outsourcing proportion is quasi-convex and the optimal price discount is non-decreasing in his capacity volume, which is counterintuitive.     

Design of price mechanisms for network resource allocation via price of anarchy

We study the design of price mechanisms for communication network problems in which a user’s utility depends on the amount of flow she sends through the network, and the congestion on each link depends on the total traffic flows over it. The price mechanisms are characterized by a set of axioms that have been adopted in the cost-sharing games, and we search for the price mechanisms that provide the minimum price of anarchy. We show that, given the non-decreasing and concave utilities of users and the convex quadratic congestion costs in each link, if the price mechanism cannot depend on utility functions, the best achievable price of anarchy is ${{4(3-2 \sqrt{2}) \approx 31.4 \% }}$ . Thus, the popular marginal cost pricing with price of anarchy less than 1/3 ≈ 33.3% is nearly optimal. We also investigate the scenario in which the price mechanisms can be made contingent on the users’ preference profile while such information is available.     

Application of duopoly multi-periodical game with bounded rationality in power supply market based on information asymmetry

In the power market, each entity is not completely rational when generate strategy, and the market information held by each entity is not exactly the same. In this paper, duopoly power providers with different selling adjustment structures are simplified from the actual grid background, where one provider can sell part of its power to another at contract price to store the power. Each provider is trying to maximize its profit by adjusting its power selling strategy. The process of evolutionary game with multi-periods bounded rational is established. One provider adjusts its selling strategy through the multi-periods market price and another through its multi-periods marginal profit. The quantity of power sold by each provider will tend to Nash equilibrium and how information asymmetry affects the stability of Nash equilibrium is analyzed through comparing dynamic power selling with and without information asymmetry. Information asymmetry has a great impact on one provider but not another. The numerical simulations also show that the information asymmetry will increase the stability region of the system. Different adjustment suggestions are proposed for different providers when information asymmetry occurs.     

Platform modelling and scheduling game with multiple intelligent cloud-computing pools for big data

We develop a generic game platform that can be used to model various real-world systems with multiple intelligent cloud-computing pools and parallel-queues for resources-competing users. Inside the platform, the software structure is modelled as Blockchain. All the users are associated with Big Data arrival streams whose random dynamics is modelled by triply stochastic renewal reward processes (TSRRPs). Each user may be served simultaneously by multiple pools while each pool with parallel-servers may also serve multi-users at the same time via smart policies in the Blockchain, e.g. a Nash equilibrium point myopically at each fixed time to a game-theoretic scheduling problem. To illustrate the effectiveness of our game platform, we model the performance measures of its internal data flow dynamics (queue length and workload processes) as reflecting diffusion with regime-switchings (RDRSs) under our scheduling policies. By RDRS models, we can prove our myopic game-theoretic policy to be an asymptotic Pareto minimal-dual-cost Nash equilibrium one globally over the whole time horizon to a randomly evolving dynamic game problem. Iterative schemes for simulating our multi-dimensional RDRS models are also developed with the support of numerical comparisons.     

Multiclass multicriteria mixed equilibrium on networks and uniform link tolls for system optimum

In this paper, we consider a unified framework of multiclass multicriteria mixed equilibrium, and the existence of uniform link tolls supporting such a mixed equilibrium as a system optimum. The network users are divided into different classes, and each class of traveler perceives his/her disutility associated with a route as a combination of two criteria given, respectively, by the travel time disutility and the time-irrelevant travel disutility. And users in a common class follow either user equilibrium (UE) principle or Cournot–Nash (CN) principle. A variational inequality model characterizing the multiclass multicriteria UE–CN mixed equilibrium behavior is developed. By utilizing the dual theory, we establish the existence of uniform link tolls supporting such mixed equilibrium as a system optimum.