Bargaining game theoretic power control in selfish cooperative relay networks

Wireless cooperative communications require appropriate power allocation (PA) between the source and relay nodes. In selfish cooperative communication networks, two partner user nodes could help relaying information for each other, but each user node has the incentive to consume his power solely to decrease its own symbol error rate (SER) at the receiver. In this paper, we propose a fair and efficient PA scheme for the decode-and-forward cooperation protocol in selfish cooperative relay networks. We formulate this PA problem as a two-user cooperative bargaining game, and use Nash bargaining solution (NBS) to achieve a win-win strategy for both partner users. Simulation results indicate that the NBS is fair in that the degree of cooperation of a user only depends on how much contribution its partner can make to decrease its SER at the receiver, and efficient in the sense that the SER performance of both users could be improved through the game.     

Game Theoretic subcarrier and power allocation for wireless OFDMA networks

This paper proposes a bargaining game theoretic resource(including the subcarrier and the power) allocation scheme for wireless orthogonal frequency division multiple access(OFDMA) networks.We define a wireless user s payoff as a function of the achieved data-rate.The fairness resource allocation problem can then be modeled as a cooperative bargaining game.The objective of the game is to maximize the aggregate payoffs for the users.To search for the Nash bargaining solution(NBS) of the game,a suboptimal subcarrier allocation is performed by assuming an equal power allocation.Thereafter,an optimal power allocation is performed to maximize the sum payoff for the users.By comparing with the max-rate and the max-min algorithms,simulation results show that the proposed game could achieve a good tradeoff between the user fairness and the overall system performance.     

Cooperative network design: A Nash bargaining solution approach

The Network Design problem has received increasing attention in recent years. Previous works have addressed this problem considering almost exclusively networks designed by selfish users, which can be consistently suboptimal. This paper addresses the network design issue using cooperative game theory, which permits to study ways to enforce and sustain cooperation among users. Both the Nash bargaining solution and the Shapley value are widely applicable concepts for solving these games. However, the Shapley value presents several drawbacks in this context.For this reason, we solve the cooperative network design game using the Nash bargaining solution (NBS) concept. More specifically, we extend the NBS approach to the case of multiple players and give an explicit expression for users’ cost allocations. We further provide a distributed algorithm for computing the Nash bargaining solution. Then, we compare the NBS to the Shapley value and the Nash equilibrium solution in several network scenarios, including real ISP topologies, showing its advantages and appealing properties in terms of cost allocation to users and computation time to obtain the solution.Numerical results demonstrate that the proposed Nash bargaining solution approach permits to allocate costs fairly to users in a reasonable computation time, thus representing a very effective framework for the design of efficient and stable networks.     

无线传感器网络基于议价解的合作策略

针对无线传感器网络（WSN）的合作多样性问题,对结合节点能耗和吞吐量的对称合作模式进行了讨论。基于Raiffa-Kalai-Smorodinsky议价解（RBS）,将对称合作问题转换成议价问题,提出了一种提高网络传输效率的WSN对称合作策略。分析了由[n]传感器节点和一个sink 组成的对称合作模型,并在此基础上,讨论了RBS最优带宽分配策略的实现过程。仿真结果表明,该对称合作策略可以大大提高传感器节点的传输效率。     

机会网络自私节点的Bertrand博弈与激励机制研究

在真实的网络环境中,很多节点可能是自私的,它们不愿意牺牲自己的资源为其他节点转发消息。针对这种情况,提出一种基于博弈论的激励机制,可以激励节点与其他节点相互合作。该机制为二阶段激励,激励节点接收消息以协助其他节点转发,同时激励节点转发更多的消息。把源节点与中继节点之间的竞争与合作模型化为Bertrand（伯特兰德）博弈,定义了源节点和中继节点的效用函数。求解了源节点的最佳定价策略和中继节点最佳的转发计划,验证了源节点与中继节点之间存在唯一的纳什均衡。模拟仿真结果表明提出的激励机制能够鼓励自私节点参与合作,能提高路由算法的传递率,同时降低了消息传递延迟。与基于声誉的激励机制相比,所提激励机制能使消息传递成功率提高31.4%、平均时延降低9.7%。     

基于Stackelberg博弈的双层水下传感器网络功率分配算法

针对水下传感器协作通信网络中能量消耗严重的问题,为了平衡节点间的能量消耗,同时提高系统的信道容量,提出了基于节点剩余能量的分布式博弈功率分配算法。将用户节点和中继节点间的交易模型构建为双层的Stackelberg博弈,使剩余能量少的节点提供较少的功率进行转发服务,反之则提供较多的功率进行服务,从而平衡节点间的能量消耗。与未考虑剩余能量的算法相比,在有2、3和4个中继节点时,信道容量分别提升了9.4%、23.1%和16.7%。仿真结果表明,该算法不仅提高了系统总的信道容量,而且延长了水下传感器协作通信网络的生存时间。     

无线多跳网络中基于博弈论的协作激励机制研究

无线多跳网络中网络传输性能容易受到自私节点的影响。本文首先对目前的节点协作激励机制进行了总结,然后,针对分簇路由中簇间路由场景,运用博弈论中非合作博弈的思想,建立博弈模型以激励簇内节点通过协作通信的方式帮助簇头进行数据包的转发,最后给出了基于非合作博弈的激励机制中纳什均衡解的求解过程。     

基于能耗的分簇频谱感知方法

在协作频谱感知中,当信道经历衰落和阴影时,各用户的感知性能会有不同程度影响,某些受影响严重的次用户甚至可能会严重影响到整个感知网络的性能.同时参与协作的用户数越多,认知传感器网络面临的问题越大.为了解决这些问题,提出了一种基于能耗的分簇协作感知算法.该算法引入基于节点能量的LEACH分簇算法,将认知传感器网络中的各个节点按该分簇算法分入若干簇内;在每个簇内,构造了同时考虑检测性能和能量消耗的效用函数,基于该效用函数对最佳协作用户数和用户进行选择,使每个簇内的检测性能和能耗达到很好的折中;在汇聚节点运用OR规则将簇头发送过来的感知信息进行融合,得到最终判决结果.仿真结果表明,该基于能耗的分簇协作频谱感知算法可以有效地延长认知传感器网络的生存时间,节省网络的能耗,并且保证良好的检测性能.     

基于服务质量机会测量的传感器网络协作控制机制*

为了消除制约无线传感器网络性能的因素和提高网络控制效率,基于实时网络服务质量机会测量,提出了传感器网络协作控制机制。首先,基于发送端节点和接收端节点状态以及中继节点的协作,测定无线传感器网络实时状态。其次,分析能耗品质和负载品质对网络性能的影响规律。接着,讨论不同分频调制方式对网络性能的影响规律。最后,制定了网络状态感知的机会分频调制的传感器网络协作控制机制。数学分析和实验结果表明,所提出的传感器网络协作控制机制对无线传感器网络的实时性、可靠性和吞吐率等方面具有较强的保障能力。     

无线传感器网络中基于效用的节点合作机制

在无线传感器网络中,由于能量和资源有限,不是每个节点都愿意为邻节点提供转发服务。讨论了无线传感器网络中自私节点的问题,提出了一个博弈模型,设计了一个基于节点信誉和能量的效用函数来监测恶意节点和自私节点,并鼓励节点中有更多的合作。在所提算法中,每个节点维护有邻节点的信誉表,参与转发的节点可以获得信誉作为奖励,而表现自私的节点则会丢失信誉作为惩罚。同时,转发会消耗节点能量,节点的信誉值和剩余能量必须都大于阈值才能在网络中共存。这样,恶意节点最终会被排除网络,自私节点则可以在激励下通过调整转发概率来避免被孤立。     

Multi-user symmetric cooperation based on nash bargaining solution in cooperative relay networks

This paper presents a symmetric cooperation strategy for cooperative relay networks with multiple users. The multi-user symmetric cooperation model and the relay selection algorithm are proposed. Then, the time slot allocation problem is cast into a bargaining problem, and the optimal time slot allocation solution is obtained by Nash bargaining solution (NBS). Moreover, we also consider the implementations of the cooperation strategy, i.e., the grouping and admission control algorithm. Simulation results show that users can obtain larger rates under the symmetric cooperation strategy than the non-cooperative case.     

Energy-efficient topology control in wireless ad hoc networks with selfish nodes

In wireless ad hoc networks there is no fixed infrastructure or centralized controller to enforce cooperation between nodes. Therefore, nodes may act selfishly in running network protocols for conserving their own energy resources. In this paper, we consider the “topology control (TC) game” as the problem of creating an energy-efficient topology in wireless ad hoc networks in the presence of selfish nodes. We define a new TC game in which nodes are able to dynamically adjust their transmission power in a per-packet manner, and try to minimize their energy usage through considering both traffic load and transmission power parameters. After analyzing the problem, we propose several algorithms to find stable topologies in an environment composed of selfish nodes, using two types of global and local connectivity information. Finally, we evaluate the performance of the proposed algorithms by simulations. Our simulation results show that using appropriate local information can interestingly result in more efficient topologies than global information.     

Cooperative load balancing in distributed systems

A serious difficulty in concurrent programming of a distributed system is how to deal with scheduling and load balancing of such a system which may consist of heterogeneous computers. In this paper, we formulate the static load‐balancing problem in single class job distributed systems as a cooperative game among computers. The computers comprising the distributed system are modeled as M/M/1 queueing systems. It is shown that the Nash bargaining solution (NBS) provides an optimal solution (operation point) for the distributed system and it is also a fair solution. We propose a cooperative load‐balancing game and present the structure of NBS. For this game an algorithm for computing NBS is derived. We show that the fairness index is always equal to 1 using NBS, which means that the solution is fair to all jobs. Finally, the performance of our cooperative load‐balancing scheme is compared with that of other existing schemes. Copyright © 2008 John Wiley & Sons, Ltd.     

基于演化博弈论的移动Ad Hoc网络中继协作机制

从演化博弈论的角度,提出一种能有效激励无线Ad Hoc网络节点参与数据分组中继协作的纳什均衡策略:G-TFT(Generous Tit for Tat).以节点中继的分组数与所需的能量开销为均衡点,建立了中继协作过程的单阶段博弈模型G,验证了节点的自私性动机,将G扩展为基于时闻序列、策略可转换的演化博弈R,并根据R的纳什均衡提出了协作激励策略G-TFT.仿真结果表明.通过调整宽容因子g,G-TFT能有效地激励节点参与中继协作.     

基于合作贡献的移动社会网络自私路由协议

移动社会网络的路由工作中存在一个不合理的假设,即所有节点是无私合作的,愿意为其他节点转发数据.然而,MSN网络节点通常表现出自私性,因为在现实世界中,节点通常被人们所支配,而社会中的人们可能由于节点资源的匮乏不愿意节点参与转发.这种节点的自私行为无疑极大地降低了网络的性能.为了解决移动社会网络的自私路由问题,提出了一种...     

Cost minimization in utility computing systems

Utility computing is a form of computer service whereby the company providing the service charges the users for using the system resources. In this paper, we present system‐optimal and user‐optimal price‐based job allocation schemes for utility computing systems whose objective is to minimize the cost for the users. The system‐optimal scheme provides an allocation of jobs to the computing resources that minimizes the overall cost for executing all the jobs in the system. The user‐optimal scheme provides an allocation that minimizes the cost for individual users in the system for providing fairness. The system‐optimal scheme is formulated as a constraint minimization problem, and the user‐optimal scheme is formulated as a non‐cooperative game. The prices charged by the computing resource owners for executing the users jobs are obtained using a pricing model based on a non‐cooperative bargaining game theory framework. The performance of the studied job allocation schemes is evaluated using simulations with various system loads and configurations. Copyright © 2012 John Wiley & Sons, Ltd.     

基于能量收集技术的无线协作网络中继选择

针对目前能量收集技术能够收集到的可用能量受限,导致无线协作网络中继节点处易出现能量短板的问题,为了避免整个网络因中继节点大量死亡而瘫痪,提出了一种基于能量收集技术的无线协作网络中继选择方案,即联合最大能量和最大数据传输链路的中继选择方案。首先,基于节点的能量收集状况,选出每跳中能量最大的节点进行解码转发;然后,结合每连续两跳的链路传输状态,选出与源节点和目的节点之间的数据传输信道最优者作为中继节点。结合Nakagami-m信道衰落模型,将该方案与随机选择方案、最大数据链路信道增益(MaDs)方案和基于中继-窃听链路最小信道增益(BNBF)方案进行对比分析,结果表明:在满足收集的能量足够用于下一时隙能量收集和数据传输的前提下,用于能量收集的比例越小,网络中断概率越小;联合最大能量和最大数据传输链路的中继选择方案在网络中断性能方面优于其他方案,其中断概率随信噪比的增大而减小,特别是当平均信噪比为38dB时,网络中断概率降到10^-5。     

A cooperation strategy based on bargaining solution in wireless sensor networks

This paper presents a symmetric cooperation strategy for wireless sensor networks, aiming to improve the transmission efficiency of the network. The cooperation strategy is implemented by partitioning the nodes into several cooperative groups. Then, in each group, the optimal cooperative bandwidth allocation is obtained based on Raiffa-KalaiSmorodinsky bargaining solution (RBS). Numerical results show that the symmetric cooperation strategy can improve the sensor node’s transmission efficiency dramatically.     

基于博弈论的能量均衡路由算法

针对传感器网络能量不均衡且网络性能易受自私节点影响的问题,利用博弈论的思想,构建了均衡能耗的博弈模型(EBGM)。该算法从激励节点合作行为出发,引入能量关注因子,摒除传统博弈算法以剩余能量作为调整转发意愿的唯一标准,转而根据节点现有能量比例与邻居能量比例的差异程度进行调节。对EBGM模型进行理论分析,证明了纳什均衡点的存在性,且其能够趋于帕累托最优。仿真结果表明,EBGM模型能够促进节点合作行为、均衡能量开销、延长网络的整体生存周期。     

基于信誉度的合作式频谱感知

认知无线电网络中存在阴影和多径衰落效应等问题,从而导致单认知用户感知结果不准确。为此,提出一种基于二重双向信誉度的合作频谱感知算法。每个次用户有自己的自私信誉度,用于判定次用户是否为恶意用户。不同地区的次用户又有不同的位置信誉度,可反映出该地域是否受阴影和多径衰落的影响。基于用户之间的互动反馈,实时更新2种信誉度,并根据不同的信誉度给出不同的权重以用于合作式频谱感知。仿真结果表明,该算法在恶意用户存在的情况下仍能取得较高检测率。