异构无线网络中基于Stackelberg博弈的分布式定价和资源分配算法

针对异构无线网络资源管理问题,结合多主多从Stackelberg博弈模型,提出了一种同时满足网络运营商和用户效用最大的异构无线网络定价和资源分配方案。首先设计了一种基于收益和花费的移动用户效用函数,并证明在运营商的价格确定后,效用函数满足凹函数的条件,保证了移动用户间非合作博弈的纳什均衡点存在。为了获取移动用户的最优带宽策略和运营商的最优价格策略,提出了一种分布式迭代算法。最后通过仿真实验取得了参与者的最优策略和子博弈完美纳什均衡。     

面向5G-ICN切片的分层缓存策略

多接入边缘计算(Multiple Access Edge Computing,MEC)和网络切片在5G网络中扮演了重要角色。网络切片的灵活可编程性和MEC的去中心化促进了信息中心网络(Information Centric Network,ICN)的部署。但是,ICN中缓存资源分配的位置和数量严重影响了运营商的收益。为此,首先将移动虚拟网络运营商(Mobile Virtual Network Operator,MVNO)和多个内容提供商(Content Provider,CP)建模为一主多从的Stackelberg博弈;其次,将MVNO内部的缓存资源分配建模为一个联合缓存成本和传输能耗的混合整数规划问题,并利用改进的精英遗传算法得到最佳位置;最后,通过博弈迭代算法得到运营商的最优定价和CP的最优放置数量。仿真结果表明,该算法具有较高的有效性以及较好的缓存资源分配能力,能够降低传输能耗和缓存成本,与贪婪搜索(Iteration Greedy Search,IGS)算法、联合缓存分配和延时控制(Joint Cache Allocation and Delay Control,JCADC)算法相比传输能耗分别节省了5%、11%,运营商的收益分别提高了32%、44%。     

基于Stackelberg博弈的网络虚拟化资源分配方法

在网络虚拟化环境中,基于Stackelberg博弈模型提出了静态博弈算法下网络运营商对频谱的定价策略及静态和动态博弈算法下各虚拟运营商的频谱分配方法,并推导了各运营商收益最大时的纳什均衡点。该方法能同时满足网络运营商和虚拟网络运营商收益最大化的需求。仿真结果验证了算法的有效性及纳什均衡点的存在性。     

基于Stackelberg Game诱导策略的网络调度算法

首先建立了网络Stackelberg Game模型,分析了该模型下Nash均衡的存在性,给出了网络的队最优解.在网络资源管理中,引入基于Stackelberg Game的网络诱导策略,利用动态博弈和多次逐步诱导的方法,提出了一种网络由一般状态到最优运行状态的动态调度算法.队最优解保证了网络在最优运行状态下的稳定性.数值仿真验证了该算法的有效性.     

基于Stackelberg博弈的动态频谱接入控制

为了解决多主用户和多次级用户共存网络的频谱资源分配问题,提出了一种基于斯塔科尔伯格（Stackelberg）博弈的动态频谱接入控制算法。该算法通过三阶段Stackelberg博弈模拟主用户频谱竞价,博弈过程中次级用户以最大化传输速率为目的接入主用户频谱,同时设计了一种迭代过程来求解纳什均衡。实验计算与结果分析证明了纳什均衡唯一存在性的充要条件,并说明了迭代过程的收敛性以及主用户最佳效用的影响因素。     

基于信道定价的无线虚拟网络资源分配策略:匹配/Stackelberg分层博弈

针对分层匹配博弈不能跟踪信道变化以及循环迭代收敛慢等问题,该文提出一种基于信道定价的无线虚拟网络资源分配策略:匹配/Stackelberg分层博弈.分别以基于流带宽的用户满意度、系统带宽及切片功率作为报酬函数建立3级联合优化模型,并采用匹配/Stackelberg分层博弈求解.在博弈下层,定义移动虚拟网络操作者(MVNOs)m—切片n对mn及其与用户(UEs)的1对1匹配博弈以代替UEs与MVNOs的多对1匹配,对mn定义基于信道平均信息的切片功率价格,加速上、下一致收敛并使UEs适应信道选择最优mn,证明均衡点存在并给出了低复杂度的分布式拒绝-接收算法;在博弈上层,基于UEs与mn已匹配关系,形成基础资源提供者(InPs)与mn的Stackelberg博弈,给出了基于局部信道信息的功率定价和分配策略,使系统效用及频谱效率基于信道最优.最后定义了双层循环稳定条件及过程.仿真表明,该策略在信道跟踪、频谱效率、效用方面均优于随机定价的匹配/Stackelberg分层博弈以及传统分层匹配博弈.     

多随从Stackelberg模型在电信供应链中的应用研究

为了对电信增值业务供应链进行进一步的研究,本文对服务提供商收入有信息费分成和广告收入两个组成的单个电信运营商多个服务提供商的单主多从Stackelberg模型进行建模和实证仿真分析,并与服务提供商只有信息费分成一种收入来源时做了对比。仿真结果表明,供应链存在双边际效应、主导企业最大程度榨取供应链上利润的资本本质,及企业利用信息不对称等可以提升自己的利润空间。最后,本文讨论了Stackelberg模型存在的缺陷,即存在均衡解与最优解之间的平衡问题等,并提出了一些有意义的结论和建议,可供电信供应链上的企业参考。     

基于Stackelberg博弈的虚拟化无线传感网络资源分配策略

虚拟化技术可有效缓解当前无线传感网络(WSN)中资源利用率较低、服务不灵活的问题。针对虚拟化WSN中的资源竞争问题,该文提出一种基于Stackelberg博弈的多任务资源分配策略。依据所承载业务的不同服务质量(QoS)需求,量化多个虚拟传感网络请求(VSNRs)的重要程度,进而,利用分布式迭代方法,获取WSN的最优价格策略和VSNRs的最优资源需求量,最后,根据纳什均衡所确定的最优价格、最优资源分配量,对多个VSNRs分配资源。仿真结果表明,所提策略不仅能满足用户的多样化需求,而且提升了节点和链路资源利用率。     

基于Stackelberg博弈的无线资源分配算法

4G系统可以随意更改速率控制方案以满足网络应用的需要,这样在传输协议中系统不遵守速率控制规则的行为更使得4G系统能耗大大提高。针对此4G系统接入选择问题,结合单跟随者Stackelberg博弈模型,文章提出了一种使用简单的效用函数和线性代价函数的4G系统无线资源分配算法,理论证明了其收敛的特性,而且通过仿真对基于Stackelberg博弈的4G系统无线资源分配算法的运行结果进行评价,证明了该算法在纳什均衡态的稳定性,取得了4G系统的最优传输效能策略和子博弈完美纳什均衡。     

基于信道定价的无线虚拟网络资源分配策略:匹配/Stackelberg分层博弈

针对分层匹配博弈不能跟踪信道变化以及循环迭代收敛慢等问题,该文提出一种基于信道定价的无线虚拟网络资源分配策略:匹配/Stackelberg分层博弈。分别以基于流带宽的用户满意度、系统带宽及切片功率作为报酬函数建立3级联合优化模型,并采用匹配/Stackelberg分层博弈求解。在博弈下层,定义移动虚拟网络操作者(MVNOs)m—切片n对m_n及其与用户(UEs)的1对1匹配博弈以代替UEs与MVNOs的多对1匹配,对\begin{document}${m_n}$\end{document}定义基于信道平均信息的切片功率价格,加速上、下一致收敛并使UEs适应信道选择最优,证明均衡点存在并给出了低复杂度的分布式拒绝-接收算法;在博弈上层,基于UEs与已匹配关系,形成基础资源提供者(InPs)与的Stackelberg博弈,给出了基于局部信道信息的功率定价和分配策略,使系统效用及频谱效率基于信道最优。最后定义了双层循环稳定条件及过程。仿真表明,该策略在信道跟踪、频谱效率、效用方面均优于随机定价的匹配/Stackelberg分层博弈以及传统分层匹配博弈。     

Incentive edge caching in software‐defined internet of vehicles: A Stackelberg game approach

In this paper, we investigate an incentive edge caching mechanism for an internet of vehicles (IoV) system based on the paradigm of software‐defined networking (SDN). We start by proposing a distributed SDN‐based IoV architecture. Then, based on this architecture, we focus on the economic side of caching by considering competitive cache‐enablers market composed of one content provider (CP) and multiple mobile network operators (MNOs). Each MNO manages a set of cache‐enabled small base stations (SBS). The CP incites the MNOs to store its popular contents in cache‐enabled SBSs with highest access probability to enhance the satisfaction of its users. By leasing their cache‐enabled SBSs, the MNOs aim to make more monetary profit. We formulate the interaction between the CP and the MNOs, using a Stackelberg game, where the CP acts first as the leader by announcing the popular content quantity that it which to cache and fixing the caching popularity threshold, a minimum access probability under it a content cannot be cached. Then, MNOs act subsequently as followers responding by the content quantity they accept to cache and the corresponding caching price. A noncooperative subgame is formulated to model the competition between the followers on the CP's limited content quantity. We analyze the leader and the follower's optimization problems, and we prove the Stackelberg equilibrium (SE). Simulation results show that our game‐based incentive caching model achieves optimal utilities and outperforms other incentive caching mechanisms with monopoly cache‐enablers whilst enhancing 30% of the user's satisfaction and reducing the caching cost.     

Caching resource management of mobile edge network based on Stackelberg game

Mobile edge caching technology is gaining more and more attention because it can effectively improve the Quality of Experience (QoE) of users and reduce backhaul burden. This paper aims to improve the utility of mobile edge caching technology from the perspectie of caching resource management by examining a network composed of one operator, multiple users and Content Providers (CPs). The caching resource management model is constructed on the premise of fully considering the QoE of users and the servicing capability of the Base Station (BS). In order to create the best caching resource allocation scheme, the original problem is transformed into a multi-leader multi-follower Stackelberg game model through the analysis of the system model. The strategy combinations and the utility functions of players are analyzed. The existence and uniqueness of the Nash Equilibrium (NE) solution are also analyzed and proved. The optimal strategy combinations and the best responses are deduced in detail. Simulation results and analysis show that the proposed model and algorithm can achieve the optimal allocation of caching resource and improve the QoE of users.     

A hierarchical approach for resource allocation in hybrid cloud environments

Cloud computing is a key technology for online service providers. However, current online service systems experience performance degradation due to the heterogeneous and time-variant incoming of user requests. To address this kind of diversity, we propose a hierarchical approach for resource management in hybrid clouds, where local private clouds handle routine requests and a powerful third-party public cloud is responsible for the burst of sudden incoming requests. Our goal is to answer (1) from the online service provider’s perspective, how to decide the local private cloud resource allocation, and how to distribute the incoming requests to private and/or public clouds; and (2) from the public cloud provider’s perspective, how to decide the optimal prices for these public cloud resources so as to maximize its profit. We use a Stackelberg game model to capture the complex interactions between users, online service providers and public cloud providers, based on which we analyze the resource allocation in private clouds and pricing strategy in public cloud. Furthermore, we design efficient online algorithms to determine the public cloud provider’s and the online service provider’s optimal decisions. Simulation results validate the effectiveness and efficiency of our proposed approach.     

基于机制设计理论的云计算SLA响应时间优化

针对云计算SLA中响应时间这一衡量云服务质量的重要指标,本文提出了一种DSIC(占优策略激励兼容)机制.在所有云资源提供商都是理性的这一共同知识假定下,DISC机制能保证云资源提供商显示真实的资源成本信息,云服务提供商以此为前提选择预算约束下能够在最短时间内完成用户任务的云资源提供商,从而达到优化用户服务响应时间的目的.本文对该机制的性能进行了严格证明,最后提出了一种寻找最优资源提供商组合的算法.     

双层分级蜂窝网最优频谱分配与定价

针对异频组网的双层分级蜂窝网,提出了一种基于纳什谈判解法的最优频谱分配与定价策略,该策略能激励家庭基站采用开放用户组模式,最大化频谱效益。通过Stackelberg博弈建模,分析了频谱定价与用户需求的关系。通过纳什谈判解法,获得了最佳的频谱分配与定价策略,按需地为宏基站与家庭基站分配了带宽资源,定量地分析了家庭基站所提高的频谱效益。仿真结果表明,该策略相比非合作博弈方法,可有效提高运营商以及家庭基站拥有者所能获得的频谱效益,部署家庭基站将提高蜂窝网络的总效益。      

Dynamic theoretic proactive caching placement game for energy saving in H‐CRAN

Edge caching is an effective feature of the next 5G network to guarantee the availability of the service content and a reduced time response for the user. However, the placement of the cache content remains an issue to fully take advantage of edge caching. In this paper, we address the proactive caching problem in Heterogeneous Cloud Radio Access Network (H‐CRAN) from a game theoretic point of view. The problem is formulated as a bargaining game where the remote radio heads (RRHs) dynamically negotiate and decide which content to cache in which RRH under energy saving and cache capacity constraints. The Pareto optimal equilibrium is proved for the cooperative game by the iterative Nash bargaining algorithm. We compare between cooperative and noncooperative proactive caching games and demonstrate how the selfishness of different players can affect the overall system performance. We also showed that our cooperative proactive caching game improves the energy consumption of 40% as compared with noncooperative game and of 68% to no‐game strategy. Moreover, the number of satisfied requests at the RRHs with the proposed cooperative proactive caching scheme is significantly increased.     

软件定义小蜂窝网络中平衡调度缓存方案

在软件定义小蜂窝网络(Software-defined Small Cell Network, SDCN)中,面对小蜂窝间的干扰问题,现有基于编码和协作的缓存资源管理方案均未结合网络拓扑进行研究,也未考虑用户设备(User Equipment, UE)的接收缓存数,使得资源分配依旧面临不平衡的严峻挑战。针对上述问题,基于SDCN中的拓扑管理功能,运用贪婪算法以是否存在重叠干扰为判定条件对小基站(Small Base Station, SBS)进行划分。此外,以平衡UE接收编码缓存数量为目标,建立平衡调度缓存模型来调节不同区域SBS的分发时间,并借助二分搜索算法寻找其最优解。最后,通过设计自适应编码缓存策略,以应对网络负载的变化。仿真结果表明,所提方案在平衡资源分配与自适应方面性能优势明显,节约了网络资源,增加了网络的吞吐量。     

宽带接入控制中弹性业务的带宽资源分配研究

文章在宽带接入的范畴之内研究了宽带接入控制中弹性业务的一种带宽资源分布式分配方法,将网络运营商和用户建立为一个斯坦克尔伯格博弈模型(Stackelberg Game),网络运营商(Leader)设置带宽价格,用户(Follower)通过控制流量大小来对价格进行反映.文章论述了这种分布式决策与系统最优决策重合的理论依据,采用应用数学编程语言(AMPL)进行了仿真举例并分析了仿真结果.