一种基于能量效率的自组织网络节点合作方法

针对移动自组织网络中的节点自私性问题,以无线网络环境中的拓扑控制和数据包转发作为网络节点的策略空间,并结合网络节点的能量效率水平,建立了一个基于严格位势博弈的网络节点合作模型。仿真结果表明,该模型不但满足了自组织网络环境下的网络连通性需求,并且通过节点间的合作机制降低了网络能耗,提高了网络节点的能量效率水平,以及数据传输的可靠性和效率。     

基于博弈理论的访问控制奖惩激励约束机制

基于信任的访问控制问题是面向开放式网络访问控制中研究的热点。该文针对开放式网络环境下网络交互实体不诚信合作的交互访问行为,建立了基于信任的动态访问控制博弈模型,并通过设计的奖惩激励约束机制促使交互实体在自身利益驱动下理性选择系统(设计者)期望的策略,以利益作为驱动力,奖励诚信节点,惩罚约束激励不诚信节点,实现符合目标要求实体间的总体均衡状态。仿真实验和结果分析表明,在网络交互实体的不诚信访问问题上该激励约束机制是有效的。     

基于异构无线网络的多路径传输

针对异构无线网络环境中,大容量业务传输质量不可靠、网络资源利用率低的问题,提出了一种基于异构无线自组织网络的多路径传输路由算法。该算法有效避免了单路通信方式下的传输链路拥塞、吞吐量低等问题,并结合大容量业务的特点,通过一定的法则合理表征网络环境信息,依据表征结果提出发端到终端的多路径策略,使得重要性不同的业务可选择相应链路质量的路径进行并行传输,避免了网络中的每个自组网节点独立寻找路由导致的源节点难以获得中间节点路由信息的现象。仿真结果表明,该算法可实现整个网络负载均衡,缓解网络链路拥塞,有效降低传输中的丢包率,降低传输时延。     

基于多因子的ZigBee安全认证机制

针对ZigBee网络节点入网认证机制中存在认证机制不完善、协调器的负载过大的不足,设计了基于多因子的ZigBee安全认证机制,以特定周期更新的新鲜因子并将其与节点硬件信息绑定,匹配节点上传的密钥信息因子和配置因子完成身份认证以防止非法节点入网对整个网络造成危害。安全性分析及测试结果表明,该机制在保证网络节点入网安全的前提下实现了协调器的负载均衡,改善了其综合性能。     

基于剩余负载率的动态负载均衡研究

为进一步提高集群系统服务的性能,在对静态负载均衡和动态负载均衡的优缺点分析的基础上,提出一种基于剩余负载率的动态均衡机制.该均衡机制采用剩余负载率作为负载状态的评价标准;针对服务器各节点性能的不同,提出采用BP神经网络训练节点;并设计了一种基于流表的静态分配策略和基于负载预测的动态分配策略相结合的任务分配策略来实现任务在集群系统各节点间的动态分配,从而降低了服务器各节点之问任务重新调度的次数,提高了集群系统的服务性能.实验结果表明,该均衡机制是可行的、有效的.     

KAD网络负载均衡技术研究

由于应用环境的特殊性和网络节点的异构性,大多数DHT网络都存在负载不均衡问题。以拥有大量用户群的eMule的KAD网络为研究对象,通过实际测量发现,由于关键词使用频率的不同,文件索引信息在KAD网络中的存储分布是不均匀的,会影响系统正常的资源发布和搜索。针对这一问题,本文提出了一个基于多重目标ID的KAD索引信息发布机制,通过让更多的节点负责拥有高频关键词的文件索引,提高KAD网络文件索引资源的负载均衡,并通过仿真实验证明了该方法的有效性。     

基于博弈论的移动自组织网络的信任管理方法

采用博弈论的思想为节点间的间接信任信息获取建立了博弈模型,提出了惩罚机制并给出了节点的效用函数。此外,建立了信任演化的复制动态方程来研究在不同参数下节点的演化稳定策略。通过实验验证了方法的正确性及有效性,证明该模型可使节点为了获得最大利益而在间接信任评估过程中趋于选择同邻居节点合作,从而提高信任管理系统的可用性与有效性,同时验证了节点在不同前提条件下的演化稳定策略。     

弹性光网络中基于安全性感知的差异化虚拟光网络的映射策略

针对虚拟环境下底层网络中光纤的概率性故障,传统的100%保护至少需要配置一条保护路径,造成资源冗余度高和虚拟网络请求接受率低的问题,该文提出一种基于安全性感知的差异化虚拟光网络的映射(SA-DVNM)策略,在链路发生故障时为差异化虚拟网络请求提供安全保证。在SA-DVNM策略中,设计了一个综合考虑物理节点对之间跳数和相邻带宽大小的节点权重式避免链路映射过长,并提出路径频谱资源使用均衡的链路映射机制,最小化瓶颈链路的数量。当单路径传输失败时,SA-DVNM策略设计允许路径分割的资源分配机制,为保障时延敏感业务的安全性,SA-DVNM策略在路由选择中设计了基于时延差优化的多路径路由频谱分配方法。仿真结果表明该文所提策略在概率故障环境中能够降低带宽阻塞率,提高频谱资源利用率和虚拟光网络接受率。     

基于概率模型的无线传感器网络优化覆盖算法

为了更好地解决无线传感器网络在覆盖过程中出现大量冗余信息及节点能量消耗不均衡等现象,提出了一种节点能量均衡的最优覆盖算法。该算法利用监测区域内传感器节点与目标节点的从属关系建立网络模型,给出传感器节点与目标节点之间的从属关系;通过从属关系和概率理论,求解传感器节点对目标节点的覆盖期望值,然后计算出覆盖监测区域所需最少传感器节点数量。实验结果表明,该算法不仅可以使用最少传感器节点完成对监测区域的有效覆盖,而且抵制了冗余信息数据的产生,提高了网络生存周期。     

一种可容错的覆盖网节点合作激励策略

为了促进覆盖网节点之间的合作,以任意相邻的两个节点为博弈参与者,用纯策略博弈建立了问题模型,证明了静止状态下的节点相互转发博弈是典型的囚徒困境,以及在无限重复囚徒困境博弈情况下,基于针锋相对策略的合作均衡是脆弱的,偶然的网络故障会引发惩罚行为,从而导致节点间的不合作.提出一种可容错的针锋相对策略TTFT（Tolerant Tit-for-tat),使节点能够在一定时间内容忍网络故障的发生.证明了使用该策略可以在发生网络故障的情况下,在有限时间内使节点达到稳定的合作状态,并证明了作弊节点的收益增量相对较低,能够有效降低节点作弊的可能性.模拟试验表明,在多个节点交互的环境下,该策略可以容忍一定比率的故障,促进节点合作,显著提高全体节点的收益总额,并可以降低作弊节点的收益,有效防止作弊.     

基于演化博弈机制的物理层安全协作方法

在无线网络中,当利用经典博弈机制研究物理层安全时,能量受限的发送端为了最大化自身安全速率,趋向于选择非协作策略,造成网络的安全速率降低。针对这一问题,该文提出一种基于演化博弈机制的物理层安全协作方法。首先,根据演化博弈机制定义策略(发送人工噪声或信号)和收益(不同策略组合下的安全速率);然后,发送端根据当前网络状态以及协作收益与平均期望收益的差值,不断进行策略调整以最大化收益;最后,通过求解获得使发送端达到协作稳定策略的条件,使网络从不稳定状态向协作稳定状态演化,从而提高了系统的安全速率。仿真和分析结果表明,在高斯信道条件下,相比经典博弈方法,该方法的发送端策略稳定在协作状态,网络安全速率可提高1 bit/(s Hz)。     

ICARUS: hybrId inCentive mechAnism for coopeRation stimUlation in ad hoc networkS

Mobile ad hoc networks rely on the cooperation of nodes for routing and forwarding. However, individual nodes may not always be willing to cooperate. In order thus to stimulate cooperation in ad hoc networks, several incentive mechanisms have been developed. In this paper we propose a new hybrid incentive mechanism, called ICARUS, which is an extension of DARWIN, a well-known reputation-based mechanism, combining advantages of both reputation-based and credit-based mechanisms. The objective of ICARUS is to detect and punish selfish nodes efficiently and at the same time motivate nodes to cooperate by rewarding the packet forwarding. Furthermore, ICARUS ensures fairness for distant nodes and prevents selfish nodes from corrupting the system using false information. The proposed scheme’s performance is tested through extended series of simulations and is compared with DARWIN. We show that ICARUS detects and isolates selfish nodes much faster, while at the same time improves the Quality of Service (QoS) received by non-selfish nodes, including distant ones.     

WSNs中基于数据匹配的分布式故障节点检测算法

针对无线传感网络的节点故障问题,提出一种新的分布式故障节点检测算法(DFDA)。DFDA算法利用节点度信息估计节点对网络的重要性,并尽可能将节点度高的节点保存到网络中。通过比较节点间感测的数据,检测故障节点。为了增强检测的准确性,采用双重测定策略。仿真结果表明,相比于同类算法,DFDA算法提高了检测故障节点的精确度,并降低了虚警率。     

Game‐theoretic modeling and analysis of relay selection in cooperative wireless networks

In this paper, distributed single relay selection in cooperative wireless networks is modeled as a Chinese restaurant game (CRG). Specifically, the CRG is used to model strategic relay selection decisions of source nodes, taking into account negative network externality due to the potential sharing of relay nodes among source nodes. Two cases are studied as follows: (i) perfect relay transmit power (RTP) knowledge and (ii) imperfect RTP knowledge. Under the first case, a distributed relay selection algorithm is proposed and shown to converge to a Nash equilibrium grouping. Under the second case, a reinforcement learning algorithm is proposed and combined with the distributed relay selection algorithm to allow network nodes to select rate‐maximizing relays. Simulation results verify the efficiency of the proposed distributed relay selection algorithm when compared with other relay selection schemes and demonstrate that it yields a network sum‐rate that is comparable with that of centralized relay selection. Copyright © 2014 John Wiley & Sons, Ltd.     

Self-policing mobile ad hoc networks by reputation systems

Node misbehavior due to selfish or malicious reasons or faulty nodes can significantly degrade the performance of mobile ad hoc networks. To cope with misbehavior in such self-organized networks, nodes need to be able to automatically adapt their strategy to changing levels of cooperation. Existing approaches such as economic incentives or secure routing by cryptography alleviate some of the problems, but not all. We describe the use of a self-policing mechanism based on reputation to enable mobile ad hoc networks to keep functioning despite the presence of misbehaving nodes. The reputation system in all nodes makes them detect misbehavior locally by observation and use of second-hand information. Once a misbehaving node is detected it is automatically isolated from the network. We classify the features of such reputation systems and describe possible implementations of each of them. We explain in particular how it is possible to use second-hand information while mitigating contamination by spurious ratings.     

Analytical Model of Cooperation in Ad Hoc Networks

The problem of cooperation among selfish nodes in ad hoc networks has gained recently a considerable attention. In this paper we propose a dynamic game theoretical model of cooperation in ad hoc networks, based on evolutionary game theory. Our model enables us to make predictions about possible equilibrium points of the network composed of the selfish and learning nodes, which can dynamically adjust their strategy in order to maximize their own payoff. In particular, we show that if an ad hoc network implements a reputation mechanism, all long term equilibrium points of the system will include cooperating nodes. In fact, in most of the equilibrium points, the cooperators will constitute a majority of the nodes. We believe that this new approach, borrowing from biological research, can have broader applications for studying dynamics of distributed communication systems.     

Spare node cooperative method for IEEE 802.11 networks

Most of the existing cooperation methods select relay node(s) mainly based on the channel state information, but do not consider whether the selected relay nodes work or not. If the selected relays are invalidated, the performance of cooperative communication will deteriorate. To resolve the above problem, this paper investigates cooperative communication in IEEE 802.11 networks, and proposes a novel Spare Cooperative Method (SCM). SCM chooses a spare cooperation node to enhance the reliability of communication, and uses an enhanced handshaking mechanism to coordinate the access of source nodes and cooperation nodes to the wireless channel. The performance of SCM is comprehensively analyzed in terms of outage probability and saturated throughput. The analysis shows that SCM improves the performance of IEEE 802.11.     

Auction-Based Pricing Schemes for Distributed Partner Selection in Cooperative Wireless Networks

In autonomous wireless networks, distributed and efficient partner selection is critical for fully realizing the benefits of cooperative communications. However, the selfish nodes in the networks bring catastrophe for partner selection when implementing cooperative transmissions. In order to stimulate cooperation and achieve distributed partner selection for such systems, an auction-based pricing scheme that considering efficiency and fairness is proposed in this paper. Two most prevalent auction forms, i.e., the second-price auction and the first-price auction, are both considered and analyzed in the single- and multiple-relay networks. In the single-relay scenario, the Nash equilibrium strategy for each auction is characterized, based on which the expected payoff and revenue for the source and relay are derived, respectively. Conclusions show that the same expected payoff is charged for the source with different auction schemes, and so is the expected revenue for the relay. Nonetheless, things are different in the multi-relay networks. With the linear 0–1 integer programming models, it is concluded that the first-price auction is more efficient than the second-price auction. Numerical results and analysis present that the proposed auction scheme efficiently solve the noncooperation issues of selfish nodes in autonomous wireless networks.     

Research on social network influence maximization algorithm based on time sequential relationship

For the time sequential relationship between nodes in a dynamic social network,social network influence maximization based on time sequential relationship was proved.The problem was to find k nodes on a time sequential social network to maximize the spread of information.Firstly,the propagation probability between nodes was calculated by the improved degree estimation algorithm.Secondly,in order to solve the problem that WCM models based on static social networks could not be applied to time sequential social networks,an IWCM propagation model was proposed and based on this,a two-stage time sequential social network influence maximization algorithm was proposed.The algorithm used the time sequential heuristic phase and the time sequential greedy phase to select the candidate node with the largest influence estimated value inf (u) and the most influential seeds.At last,the efficiency and accuracy of the TIM algorithm were proved by experiments.In addition,the algorithm combines the advantages of the heuristic algorithm and the greedy algorithm,reducing the calculation range of the marginal revenue from all nodes in the network to the candidate nodes,and greatly shortens the running time of the program while ensuring accuracy.