PTTC:无线传感网络分簇算法

分簇是延长无线传感网络寿命的有效技术。为此,提出了基于Prim的树簇拓扑的无线传感网络分簇PTTC算法。PTTC算法首先推导最优的簇数,再计算节点被选为簇头的平均概率。然后,结合节点的剩余能量以及被选为簇头的频率数选择簇头,最后利用Prim算法建立树,节点依据树传输数据,进而提高能量利用率,扩延网络寿命。仿真结果表明,提出的PTTC算法平衡了节点间的能量消耗,有效地延长了网络寿命。     

无线传感器网络中分级簇的维护和更新算法

无线传感器网络中对于一次性电池供电的传感器节点,为了减小和均衡每个传感器的耗能,延长全网的寿命,需要精密设计高效能的分簇算法,文中介绍一种利用图论中极大权中继集和根树的概念设计的基于能量的分级簇(EAHC)算法,并给出该分级簇的维护和更新算法.通过仿真表明算法的有效性.     

一种高效的无线传感器网络分簇算法

论文在LEACH-M的基础上提出一种高效的无线传感器网络分簇算法.新算法在保持簇的稳定性的同时,在簇头选择过程中引入稳定性因子对簇的稳定性进行度量,选取稳定性因子最小的节点成为簇头.在簇的组建过程中设置能量阈值作为簇的重建条件,减小簇的重建频率,同时采用单跳与多跳结合的数据传输模型,解决网络中的热点、热区问题.仿真结果表明:新算法能够有效提高在移动环境下的吞吐量,延长网络寿命.     

基于地理信息静态分簇的无线传感器网络路由算法

通过路由算法减少节点的能耗、延长网络的寿命是无线传感器网络的研究重点之一。探讨了能量高效的分层无线传感器网络路由算法,提出一个基于地理位置信息静态分簇,根据节点剩余能量及节点在簇内的位置选择簇头的分层路由算法(GSCH),适用于静态无线传感器网络。仿真实验结果表明该路由算法有效地减少分簇成形及簇首选择的能耗,延长了整个网络的寿命。     

移动传感器网络中能量均衡分簇及移动策略

无线传感器网络各节点能量有限,如果数据收集节点（Sink）能够移动,则可以大大节约节点能量,从而延长网络的寿命。首先提出一种能量均衡的分簇算法,根据节点地理信息进行分簇,使得节点耗费总能量尽可能小的同时,使各簇能量消耗基本平衡;在此基础上提出一种Sink 移动策略,Sink 优先选择能量较充足的簇收集信息。仿真结果表明,与传统的随机移动算法相比,提出的算法能够显著平衡各族之间的能量消耗,并减少总的网络能量消耗,从而提高网络的寿命。     

带速度控制的能量高效的数据收集算法

无线传感网络中, 在保证节点能耗较低, 从而延长网络寿命的基础上, 减小数据收集时延是数据收集的核心问题。为此, 提出了一种带速度控制的能量高效的移动数据收集方法。该方法首先基于节点剩余能量进行动态分簇, 每个簇形成两个簇头来分担簇头能耗; 然后给小车装载双天线, 使得节点能够MIMO数据上传; 最后利用TSP问题找到一条最优路径, 并对移动小车的速度进行控制, 以便小车能够更快地收集数据。仿真实验结果表明, 该方法能够均衡网络流量, 延长网络寿命; 与其他算法相比, 数据收集时延较短。     

无线传感器网络中最大化簇寿命的优化模型

分簇是无线传感器网络中节省节点能量的一种有效方法.研究在传感器节点均具有数据融合能力时,网络的分簇方式以及最大化簇的寿命, 提出用簇与簇头节点的能耗向量来具体刻画每个簇能量消耗的方法,建立了最大化簇寿命的整数线性规划模型,并应用该模型分析了两种基本的分簇机制下簇的寿命,提出了对就近点分簇机制下簇结构的一种调整算法.仿真实验表明,这种调整可在缩短网络时延的同时有效地延长簇的寿命.     

基于改进Prim算法无线传感器网络的动态分簇

基于图论中最小生成树的思想对LEACH协议进行了改进,构建了一种降低能耗的Prim分簇算法。其算法采用将普里姆的思想用到分簇中,将能量大或近似大的传感器节点,根据其在网络中的位置,将一条最小距离的边加入树中。通过多跳结构,减少节点在传输数据中的能量消耗,从而延长网络的寿命。对改进的算法经验证表明能有效降低能量消耗,提高网络的生存期。     

容忍延迟传感器网络中基于分簇的移动Sink动态路由算法

在无线传感器网络中使用移动Sink能有效延长网络寿命。提出一种在容忍延迟传感器网络中基于分簇的移动Sink动态路由算法MSDR（Mobile Sink Dynamic Routing）,移动Sink根据簇头位置构建遍历所有簇头的Hamilton回路,并沿着该路径收集数据。进一步提出基于标记的数据缓存机制,有效解决算法中每一轮之间的数据存储问题。仿真实验结果表明,MSDR算法使网络具有较长的生命周期,能有效平衡网络能耗。     

无人机自组网基于加权的稳定分簇算法

相较于传统移动自组网,无人机自组网具有节点移动速度更快、分布范围更广、网络规模更大的显著特征,而分簇结构能实现网络的有效控制和管理,提高网络的扩展性.为了提高分簇结构的稳定性,提出了一种基于加权的稳定分簇算法,该算法基于现有加权分簇算法,从分簇测度指标的选取、指标权重因子分配、分簇稳定保持策略三个方面进行改进.仿真结果表明,该算法不仅能合理控制分簇数量,有效提高网络的扩展性,而且能够延长簇首保持时间和降低成员节点的簇间切换次数,提高分簇的稳定性.     

一种带有可控阈值参数的分簇路由优化算法

针对传感网中大量冗余数据导致通信频繁中断的问题,提出一种带有可控阈值参数的分簇路由优化算法。引入蚁群算法中的适应度函数和启发式函数,使得下一跳簇首节点的选择更具针对性,实现网络路由树的建立与事件域节点的分布式成簇。利用可控阈值参数和变异系数对网络路由所选最短路径进行优化,保证节点能量消耗较低的同时全网延时最小,并通过全局信息素的更新策略抑制长链路的产生,以均衡全网能量并延长网络生存周期。实验结果表明,该算法与DMOA和MTTA算法在抑制网络能量消耗和延长网络生存周期方面进行对比,其性能指标平均提升了13.72%和12.06%。     

WSN 中基于能量反馈的分簇路由算法EFCA

分簇技术在无线传感器网络中得到广泛的应用.提出了一种基于能量反馈的分簇路由算法(EFCA).该算法以簇为单位构造数据聚合树,解决了单跳传输外沿节点能耗过快和多跳传输时延过大的问题;同时在簇内选择簇头对,令主次节点分别负责簇间信息传递和簇内信息收集,进一步减小了数据传输延迟;提出的能量反馈机制很好的解决了网络"热区"问题.经仿真验证,可以有效的延长网络的生存时间.     

A hierarchical overlay with cluster-based reputation tree for dynamic peer-to-peer systems

Traditional peer-to-peer technologies and systems assume that people operate with desktop computers in fixed broadband networks. When people with modern mobile devices now access Internet and Web services much in the manner they used to on desktop computers, the classical peer-to-peer overlay models can be vulnerable in wireless and mobile networks. This paper proposes a hierarchical overlay architecture based on partially central and semi-structured overlay models for the deployment of peer-to-peer systems in dynamic network environments. To keep up system scalability and efficacy, this architecture design exploits peer locality and network proximity, and contends with several problems of peer churn, peer mobility, search redundancy and traffic overhead that become much stickier in dynamic network environments. This design also integrates the reputation notion to mitigate the free-riding problem in peer-to-peer systems. According to a special cluster-based reputation tree, the hierarchical overlay is adjustable to moderate unfair or imbalanced resource utilization over the system. Furthermore, the cluster hierarchy is resilient to any points of failure at peer clusters in the overlay topology. Therefore, the effort of this study achieves an efficient and robust overlay architecture in dynamic network environments. Simulation results show that the proposed architecture is not only scalable to peer population, but also sustainable to peer- and network-initiated dynamics and influences in peer-to-peer systems.     

能耗均衡的移动传感器节点派遣算法

在混合无线传感器网络中,移动传感器节点最耗能的操作是移动,如何减少移动传感器节点的移动距离同时能让其完成任务是一个富有挑战性的研究课题。本文提出了一个移动传感器节点的派遣算法,旨在均衡各个移动传感器节点的移动负载,并且能按优先级响应事件地点,适用于任意数量的移动传感器节点和事件地点的情况。当移动传感器节点数量大于事件地点数量时,将其转化为一个带权完全二分图上的最大匹配问题。当事件地点数量大于移动传感器节点的数量时,本文提出的算法先将事件地点聚类分簇,然后派遣移动传感器节点到各个簇中分别完成访问任务。为了减少传感器节点之间的消息传输量,本文在集中式算法的基础上又提出了一个分布式算法。仿真实验结果表明本文提出的分布式算法能有效降低传感器节点之间的消息传输量,算法能够使得整个混合无线传感器网络的生存寿命延长20%左右。     

Energy-aware weighted graph based dynamic topology control algorithm

In this paper a new energy-aware weighted dynamic topology control (WDTC) algorithm is proposed to extend the lifetime of wireless network and balance the nodes’ energy consumption. The idea is that each node builds its local minimum spanning tree (MST) based on the energy-aware weighted graph and the network topology is adjusted accordingly. It was proved theoretically that the topology under WDTC algorithm could preserve the network connectivity and a sufficient condition for the degree of no more than 6 was also given. Simulation shows that WDTC algorithm can effectively prolong the network lifetime and has good topological features.     

Energy-efficient clustering in lossy wireless sensor networks

Recent experimental studies have revealed that a large percentage of wireless links are lossy and unreliable for data delivery in wireless sensor networks (WSNs). Such findings raise new challenges for the design of clustering algorithms in WSNs in terms of data reliability and energy efficiency. In this paper, we propose distributed clustering algorithms for lossy WSNs with a mobile collector, where the mobile collector moves close to each cluster head to receive data directly and then uploads collected data to the base station. We first consider constructing one-hop clusters in lossy WSNs where all cluster members are within the direct communication range of their cluster heads. We formulate the problem into an integer program, aiming at maximizing the network lifetime, which is defined as the number of rounds of data collection until the first node dies. We then prove that the problem is NP-hard. After that, we propose a metric-based distributed clustering algorithm to solve the problem. We adopt a metric called selection weight for each sensor node that indicates both link qualities around the node and its capability of being a cluster head. We further extend the algorithm to multi-hop clustering to achieve better scalability. We have found out that the performance of the one-hop clustering algorithm in small WSNs is very close to the optimal results obtained by mathematical tools. We have conducted extensive simulations for large WSNs and the results demonstrate that the proposed clustering algorithms can significantly improve the data reception ratio, reduce the total energy consumption in the network and prolong network lifetime compared to a typical distributed clustering algorithm, HEED, that does not consider lossy links.     

无线传感器网络的链路稳定成簇与功率控制算法

在能量有限条件下通过降低能耗来延长网络生存时间是无线传感器网络面临的重要挑战之一。在层次体系结构中,MAC层和网络层的能耗是影响系统能量有效性的关键,因此可以将这两层结合起来考虑,从网络跨层优化的角度来分析其能耗。针对现有典型成簇算法理论前提条件多、无法适应网络动态变化、不易在实际环境中实现的不足,结合功率控制理论及算法,基于跨层优化的策略提出了一种易于实现、能动态适应网络变化、能量有效的链路稳定成簇算法。该算法能在降低能耗的同时扩大网络的吞吐量。实验仿真结果表明,与现有的几种典型方案相比,新算法在保证网络稳定性的同时使网络具有了更大的有效吞吐量及更长的生存时间。