Intemet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Intemet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。     

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。     

一种网格资源优化分配方案

 本文提出了基于线性规划的网格异构资源分配问题的建模和求解方法.该方案综合考虑了资源分配问题的资源共享、作业优先级、作业对多种资源的依赖以及算法自身的策略等多种因素和约束条件.然后提出了网格环境下对独立作业进行网格资源分配的网格服务架构.实验表明基于线性规划的资源分配方法在速度和精确性两方面都是有效的,并且能保持高作业吞吐量.基于网格服务的架构也使该系统具有可扩展性和可伸缩性.     

云计算中一种基于排队论的资源分配方案

为了满足网络不断发展条件下对更高资源使用效率的要求,提出了一种基于排队论的资源分配方案。在这一方案里,云计算中的资源分配被分为单级资源分配和多级资源分配。资源分配的任务流被抽象为一个队列模型,实现资源的高效调度与利用。推导和分析了这一队列模型的多个性质,如到达任务数的性质和任务到达间隔的性质。根据建立的稳态方程,得到了模型的性能指标,如队列长度、等待队列长度等。通过数值仿真,对提出的基于排队论的资源分配方案进行了验证。     

QoS接纳控制

网络中支持服务质量(QoS),在网络所有用户都能接受要求的服务性能情况下,决定网络是否接纳一个新的流量流的接纳控制算法,是QoS的关键技术。文中描述了接纳控制方案的基本概念及其基本结构,比较了集成服务(IntServ)和区分服务(DiffServ)的性能。IntServ框架结构流量接纳控制每个单一流的QoS性能和资源分配;DiffServ模型则必须考虑一些流的聚集,因此,DiffServ模型具有更大的可扩展性。最后,介绍了一些基本的接纳控制方法,包括以参数为基础的接纳控制和以测量为基础的接纳控制。     

网络路由基于对策论的资源分配策略

对策论提供对独立参与者之间冲突进行建模的框架,可用以综合考虑路由选择和拥塞控制问题.经典的对策论不一定直接能应用于网络.本文在路由选择的多Agent系统的基础上,给出具有"惩恶扬善"行为的基于对策论的路由资源分配策略.它奖励避免拥塞、惩罚行为不合要求的用户.在用户都是理性的前提下,系统能稳定在纳什均衡状态.     

车联网中网络切片资源分配方案

为了满足车联网中不同应用的服务质量(Quality of Service, QoS)要求,提出了一种基于网络切片技术的车联网频谱资源分配方案。该方案考虑数据接入控制,通过联合优化频谱资源块(Resource Block, RB)分配和车辆信号发射功率控制,在安全服务切片低时延高可靠性的约束下,最大化信息娱乐服务切片的平均和吞吐量。将车联网资源管理建模为一个混合整数随机优化问题,利用李雅普诺夫(Lyapunov)优化理论将该优化问题分解为接入控制和RB分配与功率控制两个子问题,并分别对其进行求解,得到每个时隙的接入控制和资源分配方案。仿真结果表明,所提出的资源分配方案能够有效提高信息娱乐服务切片的平均和吞吐量,并且可以通过调整引入的控制参数值来实现吞吐量和时延的动态平衡。同时,与已有方案相比,该方案具有更好的时延性能。     

服务计算中避免死锁和活锁的资源分配算法

服务计算系统资源层的目标是满足服务实例的资源分配需求,保证其成功执行而不陷入死锁和活锁.首先将服务资源分配行为形式化为有限状态机;其次提出一种避免死锁和活锁的资源分配算法,它采用并发请求资源的方式,且不需要并发服务实例之间交换消息.仿真实验结果表明,该算法能够避免服务资源分配过程中的死锁和活锁,表现出较高资源分配性能.     

面向成本优化的云计算资源分配方法研究

针对云计算运营环境中,云服务提供商租用云资源提供商的资源,向用户提供服务的场景,以优化云服务提供商的成本支出,增加其运营收益为目标,设计了一种面向成本优化的虚拟机资源分配方法.该方法全面考虑了现货、预约和按需3种资源分配模式,引入风险控制因子规避现货市场的资源风险,制定出成本优化的资源分配方案.所提方法在满足用户满意度基础上,有效实现了虚拟机资源成本的优化,增加了云服务提供商的收益.     

基于QoS的语义Web服务组合优化算法

在面向服务的环境下,存在众多可满足服务请求者要求的服务组合方案,如何从中选出最优或近似最优方案是Web服务组合优化要解决的问题.设计出一个不必探索整个解空间的优化算法——SBG算法,为服务请求者提供最优选择方案.实验结果表明,这种方法可有效提高选择方案的求解效率.     

Evolutionary non‐cooperative spectrum sharing game: long‐term coexistence for collocated cognitive radio networks

Collocated cognitive radio networks (CRNs) employ coexistence protocols to share the spectrum when it is not being used by the licensed primary users. These protocols work under the assumption that all spectrum bands provide the same level of quality of service, which is somewhat simplistic because channel conditions as well as the licensee's usage of allocated channels can vary significantly with time and space. These circumstances dictate that some channels may be considered better than others; therefore, CRNs are expected to have a preference over the choice of available channels. Because all CRNs are assumed to be rational and select the best available channels, it can lead to an imbalance in contention for disparate channels, degraded quality of service, and an overall inefficient utilization of spectrum resource. In this paper, we analyze this situation from a game theoretic perspective and model the coexistence of CRNs with heterogeneous spectrum as an evolutionary anti‐coordination spectrum‐sharing game. We derive the evolutionarily stable strategy (ESS) of the game by proving that it cannot be invaded by a greedy strategy. We also derive the replicator dynamics of the proposed evolutionary game, a mechanism with which players can learn from their payoff outcomes of strategic interactions and modify their strategies at every stage of the game and subsequently converge to ESS. Because all CRNs approach ESS based solely upon the common knowledge payoff observations, the evolutionary game can be implemented in a distributed manner. Finally, we analyze the game from the perspective of fairness using Jain's fairness index under selfish behavior from CRNs. Copyright © 2016 John Wiley & Sons, Ltd.     

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.     

基于博弈论的多小区OFDMA系统资源分配

立足于限制条件下实现多小区OFDMA系统容量最大或总传输功率最小的优化问题,比较分析了近年来提出的多种基于博弈论的资源分配算法。分析了纳什均衡点存在和唯一的条件,通过引入定价机制或虚拟裁判机制,使得到的解收敛于纳什均衡点。最后,探讨了联合中继节点或MIMO技术的多小区OFDMA系统资源分配算法,该算法能有效提高频谱效率,将成为未来研究的热点。     

Cognitive Radio Bandwidth Sharing Scheme Based on the Two-way Matching Game

Bandwidth is an extremely valuable and scarce resource, and may become congested to accommodate diverse services in wireless communications. To enhance the efficiency of bandwidth usage, the concept of cognitive radio has emerged as a new design paradigm. In this paper, a new bandwidth sharing algorithm is developed for cognitive radio networks. Under dynamically changing network environments, we formulate the bandwidth sharing problem as a two-way matching game model. In addition, modified game theory is adopted to reach a near Pareto optimal solution while avoiding bandwidth inefficiency. This approach can make the system more responsive to the current network situation. With a simulation study, it is demonstrated that the proposed scheme approximates an optimized solution under widely diverse traffic load intensities.     

Multimedia Service Discrimination Based on Fair Resource Allocation Using Bargaining Solutions

We deal with a resource allocation problem for multimedia service discrimination in wireless networks. We assume that a service provider allocates network resources to users who can choose and access one of the discriminated services. To express the rational service selection of users, the utility function of users is devised to reflect both service quality and cost. Regarding the utility function of a service provider, total profit and efficiency of resource usage have been considered. The proposed service discrimination framework is composed of two game models. An outer model is a repeated Stackelberg game between a service provider and a user group, while an inner model is a service selection game among users, which is solved by adopting the Kalai‐Smorodinsky bargaining solution. Through simulation experiments, we compare the proposed framework with existing resource allocation methods according to user cost sensitivity. The proposed framework performed better than existing frameworks in terms of total profit and fairness.     

Dynamic switch migration towards a scalable SDN control plane

Distributed control plane is a promising approach to scalable software‐defined networking (SDN). Live migration of switches from controllers that are overloaded to those that are underutilized may be a solution to handle peak switch traffic using available control resource. However, such migration has to be performed with a well‐designed mechanism to fully utilize available resources in all three resource dimensions: CPU, bandwidth, and memory. In this article, we first provide a resource model for SDN and reduce the switch migration decision to a centralized resource utilization maximization problem under constraints of CPU, bandwidth, and memory. Second, we show that the problem of maximizing resource utilization in an SDN is equivalent to that of maximizing game players' profits in the context of non‐cooperative game theory. Taking controllers and switches as game players and commodities respectively, the player policy is how to migrate switches among the control plane. Finally, we implement a proof of concept, called GAME‐Switch Migration (GAME‐SM). The numerical experiments using Mininet emulator validate nice properties of our game model in enhancing the performance of control plane in SDN. Copyright © 2016 John Wiley & Sons, Ltd.     

Tuning radio resource in an overlay cognitive radio network for TCP: greed isn't good [Accepted from Open Call]

In this article we illustrate the performance of Transmission Control Protocol in an overlay cognitive radio network under dynamic spectrum access. We show that the performance of TCP in overlay CR networks that implement DSA to be quite different from its performance in conventional networks, which do not allow DSA. The key difference is that secondary users in an overlay CR network have to cope with a new type of loss called service interruption loss, due to the existence of primary users. We demonstrate on an NS2 simulation testbed the surprising result: Excessive radio resource usage leads to a decrease in aggregate TCP throughput. This behavior is in contrast to the behavior of TCP in conventional networks, where throughput increases monotonically with the available radio resource.     

A Security Differential Game Model for Sensor Networks in Context of the Internet of Things

A particular challenging problem in designing Internet of Things is that how to detect and prevent internal attacks, because all nodes try their best to save their limited network resource. So it is difficult to achieve optimal objectives simultaneously, game theory provides an appropriate tool. In this paper, we propose a non-cooperative differential game model, which allows all nodes to choose the optimal amount of network resource to invest in information security contingent upon the state of game. In our model, we specifically consider how the vulnerability of information and the potential loss from such vulnerability affects the optimal amount of resources that should be devoted to securing that information. In the paper, the optimal strategies of selfish nodes and malicious nodes are obtained respectively. The simulation results show that our game model has a good performance in stability of the probability that the selfish nodes discover the malicious nodes under the optimal strategies of the selfish and the malicious nodes.     

基于不完全信息博弈的网格资源分配方法研究

针对网格环境下用户难以获得资源竞价所需的信息而导致的决策风险,将不完全信息资源竞价转化成完全信息下的重复博弈问题。分析了该博弈均衡解的存在性及求解过程,给出了相应的竞价算法,讨论了对用户低价联盟的抑制方法。仿真实验表明用户通过各阶段资源预配置的信息调整竞价策略,资源配置可逐步逼近均衡解,实现网格资源的优化配置。     

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.