A game theoretic framework for bandwidth allocation and pricing inbroadband networks

In this paper, we present a game theoretic framework for bandwidth allocation for elastic services in high-speed networks. The framework is based on the idea of the Nash bargaining solution from cooperative game theory, which not only provides the rate settings of users that are Pareto optimal from the point of view of the whole system, but are also consistent with the fairness axioms of game theory. We first consider the centralized problem and then show that this procedure can be decentralized so that greedy optimization by users yields the system optimal bandwidth allocations. We propose a distributed algorithm for implementing the optimal and fair bandwidth allocation and provide conditions for its convergence. The paper concludes with the pricing of elastic connections based on users' bandwidth requirements and users' budget. We show that the above bargaining framework can be used to characterize a rate allocation and a pricing policy which takes into account users' budget in a fair way and such that the total network revenue is maximized     

Combinatorial double-sided auctions for network bandwidth allocation: a budget-balanced and decentralized approach

Telecommunication networks are now an interconnection of competitive operators that need to cooperate to ensure end-to-end delivery of traffic. Inter-domain agreements have to be performed, and pricing is seen as a relevant way to reward intermediate domains for forwarding the traffic of others. In previous works, Vickrey–Clark–Groves (VCG) double-sided auctions have been applied because they provide proper incentives, lead to an efficient use of the network, and verify other relevant characteristics. However, it has been highlighted that the resource allocation schemes applying VCG auction are neither budget-balanced nor solvable in a decentralized way. In this paper, we apply combinatorial double-sided auction to allocate the bandwidth resources over nodes. While previous works were using a centralized algorithm, we use here a new pricing rule, leading to a new budget-balanced pricing scheme for which allocations and charges can be computed in a decentralized way. We also analyze the impact of this scheme on the game over declared costs of nodes.     

对策论方法在信息网络资源分配中的应用

在研究复杂信息网络的资源分配问题时,网络资源提供者和用户之间对资源的使用存在不同的优化目标,导致对资源分配策略存在多种评价准则。为便于网络管理者进行分布式的资源管理和计费,采用对策论模型分析用户对资源的竞争和处理网络传输拥塞正日益受到广泛的重视。本文首先指出资源分配和计费管理的几个主要难点,比较了中心化与非中心化控制策略的差别,而后综述了采用对策论模型进行资源分配和管理的优点,重点讨论了在非中心化条件下对策均衡解与资源利用效率以及网络计费管理策略之间的关系,最后对基于对策论模型的信息网络流量控制与管理策略进行总体评述。     

A Noncooperative Game-Theoretic Framework for Radio Resource Management in 4G Heterogeneous Wireless Access Networks

Fourth generation (4G) wireless networks will provide high-bandwidth connectivity with quality-of-service (QoS) support to mobile users in a seamless manner. In such a scenario, a mobile user will be able to connect to different wireless access networks such as a wireless metropolitan area network (WMAN), a cellular network, and a wireless local area network (WLAN) simultaneously. We present a game-theoretic framework for radio resource management (that is, bandwidth allocation and admission control) in such a heterogeneous wireless access environment. First, a noncooperative game is used to obtain the bandwidth allocations to a service area from the different access networks available in that service area (on a long-term basis). The Nash equilibrium for this game gives the optimal allocation which maximizes the utilities of all the connections in the network (that is, in all of the service areas). Second, based on the obtained bandwidth allocation, to prioritize vertical and horizontal handoff connections over new connections, a bargaining game is formulated to obtain the capacity reservation thresholds so that the connection-level QoS requirements can be satisfied for the different types of connections (on a long-term basis). Third, we formulate a noncooperative game to obtain the amount of bandwidth allocated to an arriving connection (in a service area) by the different access networks (on a short-term basis). Based on the allocated bandwidth and the capacity reservation thresholds, an admission control is used to limit the number of ongoing connections so that the QoS performances are maintained at the target level for the different types of connections.     

基于非合作竞价博弈的网络资源分配算法的应用研究

本文运用博弈理论对资源分配技术进行了深入研究,提出了能够反映供求关系的基于竞价的网络资源定价机制,并设计了端系统的效用函数,论证了资源分配博弈中Nash均衡点的存在性和唯一性以及Nash均衡解.基于所提资源分配博弈模型,设计了一种网络资源分配算法(RANG).仿真实验表明,RANG算法能够为端系统的资源数量提供参考,规范端系统竞价,从而使得整个资源的分配趋于合理.     

EIM: An Enforceable Incentive Mechanism for Dynamic Non-cooperative Multi-radio Channel Allocation in Wireless Mobile Networks

Multi-radio channel allocation (MRCA) is a key issue to improve the system performance supporting all kinds of mobile applications in wireless networks. However, existed work on non-cooperative MRCA just considers the cases under the extreme saturation load condition and static game, which means that it is assumed that all the nodes always have packets to send and mobile terminals just change the channel once. Such assumption is obviously impractical for actual wireless network and isn’t suitable for the mobility of applications without intelligent spectrum management. Meanwhile, the existed schemes are unable to support mobile applications with time-varying channel. In this paper, an enforceable incentive mechanism called EIM is proposed for dynamic non-cooperative multi-radio channel allocation to support mobile applications. In order to optimize the overall performance of mobility management, in the proposed EIM, the strong assumption of saturation network traffic is relaxed, which makes the mobile terminals are able to have time-varying bandwidth requirements. Then, the MRCA problem is modeled as an infinite repeated game. Detailed theoretical analysis proves that there exist multiple pure Nash Equilibriums (NEs) for the game, and, under certain condition, there also exist NEs which are not Pareto-Optimal. Hence, based on the punishment strategy, the proposed EIM can achieve social welfare. Detailed numerical and simulation results show that the proposed EIM can improve the system throughput about 15 % compared with the existed works, which can provide an efficient method to manage channel resource and get better ubiquitous online access to preferred mobile services.     

Class-based quality of service over air interfaces in 4G mobilenetworks

We present a framework for quality of service provisioning over the air interfaces in future wireless networks, including 3G enhancement and 4G mobile networks. The framework is based on the paradigm of service classes, wherein each class can exhibit a characteristic behavior in terms of resource allocation over the air interface. Using this QoS framework, future wireless network operators can define their own sets of service classes, choose the preferred way of implementing the QoS behavior of these classes, and offer class-based pricing schemes. The user application can choose the service class that best suits its expectations in terms of QoS and cost of access. A class-based bandwidth scheduling scheme is described as a mechanism to implement this QoS framework over CDMA air interfaces. This scheme incorporates the paradigm of service classes, in conjunction with fair resource allocation and air interface congestion resilience, while allocating air interface bandwidth to mobile users     

一种基于市场模型的网络带宽分配方法

价格手段最近被用来控制网络拥塞和管理网络资源的分配,而价格手段的一个重要特点是可以促进资源的合理分配和利用。本文提出一种基于市场模型的网络带宽分配方法,该方法根据用户的宽带需求和网络系统带宽的使用状况,计算出网络带宽的市场价格,并通过用户有的价格参数进行带宽资源的协凋与分配,分析表明,该方法可以达到优化系统效率和提高用户满意度的目标。     

A multi‐cell adaptive resource allocation scheme based on potential game for ICIC in LTE‐A

Intercell interference coordination in Third Generation Partnership Project long‐term evolution‐advanced system has received much attention both from the academia and the standardization communities. Moreover, the network architecture of long‐term evolution‐advanced system is modified to take into account coordinated transmission. In this article, we study the dynamic resource allocation problem and potential game theory and propose a multicell adaptive distributed resource allocation algorithm based on potential game. The allocation process is divided into two steps; subchannel is allocated first, and then, transmitted power is optimized dynamically according to a novel pricing factor. Besides, existence and uniqueness of Nash equilibrium of the proposed game model are assured. As a result, intercell interference is well coordinated. Simulation results show that transmitted power is saved efficiently and system fairness is improved to a large extent, accompanied with good performance gain of total and cell‐edge throughputs. Copyright © 2013 John Wiley & Sons, Ltd.     

Responsive pricing modeled with Stackelberg game for next-generation networks

In this paper, we study the problem of resource allocation between users in next-generation networks. The starting assumption is that the service provider tries to come up with convincing offers of service level to subscribers, based on demand responsive pricing scheme, while trying to maximize its profit. We developed two algorithms with different usage-based pricing strategies. Both algorithms solve pricing optimization problem using Stackelberg game with service provider acting as a leader and users behaving as followers. We developed the bandwidth management server to perform automatic optimal bandwidth allocation to each user's session and maximize its expected utility while maximizing the overall service provider's revenue. For both algorithms, we also performed the procedure for optimization of the capacity offered to users.     

On Bandwidth Allocation for Data Dissemination in Cellular Mobile Networks

Wireless bandwidth is a scarce resource in a cellular mobile network. As such, it is important to effectively allocate bandwidth to each cell such that the overall system performance is optimized. Channel allocation strategies have been extensively studied for voice communications in cellular networks. However, for data dissemination applications, studies on bandwidth allocation have thus far been limited to a single-cell environment. This paper investigates the problem of bandwidth allocation for data dissemination in a multi-cell environment, which, to the best of our knowledge, has not been investigated before. The performance objective is to minimize the overall expected access latency given the workload for each cell in a data dissemination system. Two heuristic techniques, called compact allocation and cluster-step allocation, are proposed to effectively allocate bandwidth for a cellular network. Simulation experiments are conducted to evaluate the performance of the proposed bandwidth allocation schemes. Experimental results show that the proposed schemes substantially outperform the uniform allocation and proportional allocation schemes.     

ADSL接入网多等级业务带宽分配机制研究

根据目前非对称数字用户线（ADSL）网络带宽资源分配和相应的服务质量（QoS）保障中存在的问题,文章提出了一个带宽资源的分配方案,将拉格朗日最优化算法引入带宽分配机制中,可以利用在线监测数据,在线性价格策略下调整对不同等级业务的带宽分配,同时实现网络提供商在一定资源约束下的收益最大化和最大限度满足不同用户的不同QoS要求。     

A Non-cooperative Differential Game Model for Frequency Reuse Based Channel Allocation in Satellite Networks

In this paper, channel resource allocation problem for LEO mobile satellite systems is investigated and a new dynamic channel resource allocation scheme is proposed based on differential game. Optimal channel resource allocated to each satellite beams are formulated as Nash equilibrium. It is proved that optimal channel resource allocation can be achieved and the differential game based scheme is applicable and acceptable. Numerical results shows that system performance can be improved based on the proposed scheme.     

Pricing, provisioning and peering: dynamic markets fordifferentiated Internet services and implications for networkinterconnections

This paper presents a decentralized auction-based approach to pricing of edge-allocated bandwidth in a differentiated services Internet. The players in our network economy model are one raw-capacity seller per network, one broker per service per network, and users, to play the roles of whole-sellers, retailers, and end-buyers, respectively, in a two-tier wholeseller/retailer market, which is best interpreted as a “sender-pay” model. With the progressive second price auction mechanism as the basic building block, we conduct a game theoretic analysis, deriving optimal strategies for buyers and brokers, and show the existence of networkwide market equilibria. In addition to pricing, another key consideration in building differentiated network services is the feasibility of maintaining stable and consistent service level agreements across multiple networks where demand-driven dynamic allocations are made only at the edges. Based on the proposed game-theoretic model, we are able to construct an explicit necessary and sufficient condition for the stability of the game, which determines the sustainability of any set of service level agreement configurations between Internet service providers. These analytical results are validated with simulations of user and broker dynamics, using the distributed progressive second price auction as the spot market mechanism in a scenario with three interconnected networks, and two services based on the proposed standard expedited forwarding and assured forwarding per-hop behavior     

A virtualized resource management scheme for heterogeneous cellular networks

Because of random deployment patterns of femtocells, interference scenarios in a heterogeneous cellular network can be very complicated because of its changing network topology. Especially when each eNodeB occupies a fixed bandwidth, interference management becomes much more difficult. The benefit of dynamic management for local resource optimation is limited. Recently, resource virtualization has been proposed as a dynamic resource management scheme to optimize network performance. In fact, resource virtualization is viewed as a more flexible model, in which mobile network service providers can control physical resources in a global scope. This paper presents a joint resource virtualization and allocation scheme for its applications in heterogeneous macro‐femto‐cellular networks. The proposed scheme involves two major processes. First, it virtualizes physical resources as logical resources. Second, it carries out logical resource allocation optimization globally and aggregates logical and physical resources for resource allocation. The proposed scheme takes into account spectrum reuse and frequency domain interference jointly in order to achieve a high spectral efficiency and provide rate‐on‐demand services to all users. Simulation results demonstrate the effectiveness of the proposed scheme. Copyright © 2016 John Wiley & Sons, Ltd.     

Resource planning and incentive engineering for a congested wireless access point: an integrated multiple time scale control mechanism

Wireless networks are playing an increasingly important role for global communications. Many resource allocation mechanisms have been proposed to efficiently utilize the limited radio resources in wireless networks to support a large number of mobile users with a diversity of applications. Among them, pricing frameworks that provide incentives to users to maximize their individual utility while optimizing allocation of network resources have attracted a lot of attention recently. Nevertheless, most of these pricing schemes require dynamic charging rates and may be too complex for wide acceptance by users, as most users would prefer relatively simple charging schemes. Moreover, use of a pricing framework to facilitate resource planning and future expansion at the service provider’s side has not yet been widely considered. In this paper, we propose Integrated Multiple Time Scale Control (IMTSC), a novel incentive engineering mechanism to facilitate resource allocation and network planning. Over different time scales, IMTSC combines the functions of network capacity planning, admission control for resource allocation, and tracking of users’ instantaneous traffic demands. The proposed mechanism is applied for access control at a congested access point in a wireless network. By decomposing the original problem into distributed optimization problems that are solved locally by the service provider through adjusting charging rate and remotely by individual users by appropriately changing her service requests, we show that maximization of user’s utility and increase of network efficiency can be simultaneously achieved. Results from extensive simulations demonstrate the effectiveness of the proposed IMTSC mechanism.     

Internet拥塞控制和资源分配中的对策论分析框架

本文从一个简单的 ,适用性很强的对策论模型出发 ,首先证明了当前Internet资源分配低效率的原因 :存在拥塞的外部效应 .进而提出了一个统一的对策论框架 ,以目前最具代表性的三个支持多业务的资源分配方案 :综合服务、区分服务和基于使用的计费为例 ,推导出这些方案在集中化控制和非集中化控制之下 ,Nash均衡的存在性及其性质 .得到了每种方案中各方参与者的优化问题的解 ,并给出了相应的物理解释 .     

On Congestion Pricing in a Wireless Network

The purpose of this paper is to study optimal pricing in a mobile distributed network with transmit power control. The paper proposes a linear congestion pricing scheme for the optimal distributed control of a wireless network. The optimal congestion price applies for the optimal resource control in a congested communication network where decisions on resource usage are made locally by the mobile nodes applying a learning automaton. Numerical examples for the convergence of a price controlled wireless network to a Pareto-optimal transmit power allocation are presented.     

认知无线网络频谱感知与节点协同问题综述

认知无线电是被公认的解决移动无线网络频谱资源短缺和频谱资源动态分配问题的最有效和最有潜力的技术。基于认知无线电技术目前在移动无线网络中的实际应用情况,详细分析了认知无线网络目前所存在的无线频谱资源感知、探测和接入机制以及多用户节点协同等问题,并综述了频谱资源分配算法和认知无线网络容量问题的最新研究进展,最后提出用博弈论来研究解决认知无线网络多用户协同问题中的用户自私行为。