基于移动代理的无线传感器网络簇内融合算法

在无线传感器网络中采用移动代理技术进行数据融合。根据节点剩余能量、局部融合结果,设计节点分簇算法。优化移动代理在簇内的路由策略,进一步减少无线传感器网络的数据传输总量。通过实验得出,采用移动代理的簇内融合过程中,能在一定程度上减小路径损耗。     

改进的LEACH协议在井下通信系统中的应用

无线传感器网络由能量受限的节点组成,通过部署这些节点以便收集特定监测区域内的有用信息.基于层次的LEACH协议通过将节点分簇以实现数据融合.随机选择的簇头节点接收到本簇成员的数据后进行融合处理,将结果传输到汇聚节点.避免每个节点都与远距离的汇聚节点直接通信,从而节约能耗.将无线传感器网络应用于井下通信系统,能够提高通信的安全性.LEACH的分簇结构与矿井内分坑道工作的情况相类似,把每个坑道作为一个簇,将多数传感器节点安置在坑道内的固定位置,少量节点随矿工位置移动,再将这些节点采集的数据传输至簇头节点.本文主要针对井下通信系统的特点对现有的LEACH协议进行改进,优化了簇头节点的选举方法,并允许部分节点采用多跳方式与汇聚节点通信,使其更符合矿井结构的要求,从而节约了能耗,并且有效地延长了网络的生存时间.     

基于移动机器人的无线传感器网络数据收集方法

稀疏无线传感器网络中各传感器节点距离较远,而传统的静态数据收集方法要求各传感器节点直接通信,导致网络延迟时间长,能耗高。针对该问题,提出一种基于移动机器人的无线传感器数据收集方法。该方法首先由静态节点选择与路径最短的移动机器人作为簇头,移动机器人比较一定周期内检测到的邻居节点的平均剩余能量与整个网络传感器节点平均剩余能量,根据比较结果决定其是否移动,若移动则采用范围可控的随机移动策略;当移动机器人移动到新位置时,传感器节点更新路由,选择新的移动机器人作为簇头。仿真结果表明,与传统的静态无线传感器网络数据收集方法相比,基于移动机器人的无线传感器网络数据收集方法大大降低了数据传输延迟和节点能量消耗。     

WSNs中基于期望网络覆盖和分簇压缩感知的数据收集方案

为提高无线传感器网络数据收集精确度、降低网络能耗和改善数据包丢失情况下数据收集算法的鲁棒性,提出一种基于期望网络覆盖和分簇压缩感知的数据收集方案.首先设计期望网络覆盖优化算法,给出节点调度策略,实现对“特殊”区域重点观测和降低节点能耗的目的;然后通过分析网络分簇与节点部署之间的关系,设计弱相关性观测矩阵,降低数据包丢失对数据收集的影响;最后引入群居蜘蛛优化算法以提高汇聚节点处CS数据重构精度.仿真结果表明,与其他数据收集算法相比,所提出方案数据重构误差降低了约23.5{%     

基于MACAW的分簇轮转调度式水声传感网MAC协议

针对当前水声传感器网络长时延和低信道利用率的特点,改进传统的水声通信网MAC协议MACAW协议,设计出一种新型的分簇轮转调度式MAC协议CRD-MACAW协议。该协议通过网络初始化和网络动态更新对部署在网络中的传感器节点按照一定机制进行分簇,网络中的数据传输则分为簇内传输和簇间传输。簇内传输采用分簇时网络管理节点所分配的轮转顺序进行,节点与节点之间无需发送RTS帧和CTS帧;簇间传输则是通过各个簇首节点之间采用MACAW协议来进行的,最终网络数据汇聚到网络管理节点供分析使用。仿真结果表明,该协议与传统的MACAW协议相比,在网络节点增多、节点整体分布较为分散时,能够有效降低传输时延,提高信道利用率。     

基于移动 Ｓｉｎｋ 的带状无线传感器网络数据汇聚方法研究

无线传感器网络内部能耗不均衡容易导致节点提早死亡,为此大量的能耗均衡路由协议被提出,然而这类方法主要针对环状无线传感器网络。带状无线传感器网络呈长条形分布,传统的能耗均衡路由协议无法发挥节能和能耗均衡的作用。本文提出一种基于移动Sink的带状WSN数据汇聚方法,首先基于节点能耗模型计算簇内节点的平均能耗,然后利用节点平均能耗求取Sink节点的最佳移动速度,最后簇首节点根据它与Sink的距离动态调整数据传输范围,从而实现对带状传感器网络的数据汇聚。实验结果表明该方法具有较好的节能和能耗均衡性,能够有效延长网络的生存周期。     

带有重叠区域的多跳非均匀分簇路由算法

能耗作为衡量无线传感器网络性能的一项重要指标,通常将延长生命周期、均衡能耗作为网络协议重要的设计目标.针对静态、异构、非均匀分布的网络模型,设计带有重叠区域的分簇及簇内单跳、簇间多跳的路由算法 ----- OMU分簇路由算法,该算法中簇头不再作为数据转发节点,而主要用于簇内数据的接收与融合.通过综合考虑节点剩余能量、节点密度及与基站的距离进行簇头选举并进行分簇,形成簇间重叠区域,产生用于数据转发的中继节点.同时,建立簇头与中继节点轮换机制以达到节点能耗均衡的目的,并为每个节点建立能量最省的多跳数据传输路径.仿真结果表明,所设计的分簇路由算法,特别是在大规模部署的无线传感器网络中,能有效减少和均衡能量消耗.     

基于口令应答的协作式WSNs移动复制节点检测方法研究

目前,针对无线传感器网络复制节点攻击研究主要集中在对静态网络中复制节点的检测。WSNs的应用中,节点部署在一定区域形成静态网络并采集信息,为了减少节点间通信量、降低能耗,若干个节点形成一个簇,簇内选举簇头节点作为簇间通信人。静态网络采集的信息通常由汇聚节点回收,为了方便,汇聚节点通常采用移动形式加入网络,收集完后离开。如果这类在移动中收集信息的节点是复制节点,对整个WSNs的威胁比静态网络中的复制节点威胁更大。在借鉴已有的移动网络检测方案的基础上,针对静态网络分簇和移动节点位置经常变换的特点,提出了基于口令应答的协作式WSN移动复制节点检测方法CRCDS（Challenge/Response and Collaborative Detection Scheme）,有效利用静态网络的存储空间,采取静态网络和移动节点相互协作的方式,规避因移动节点位置变化对检测结果的影响,并从理论和实验上分析了该检测方法的安全性和可行性。     

多稀疏基分簇压缩感知的WSN数据融合方法

针对传感器节点采集数据精度与能量消耗的矛盾,提出多稀疏基分簇压缩感知的无线传感器网络WSN（Wireless Sensor Network）数据融合方法。该方法利用改进的阈值对随机部署的传感器节点进行簇首选择继而形成最优簇,簇首采用伯努利随机观测矩阵对簇内节点信号进行线性压缩投影,然后将压缩的信息传送给汇聚节点,减少数据传输即降低通信能耗,从而提高网络的生命周期。根据传感器节点监测信号在有限差分和小波中都具有可压缩特性,汇聚节点在有限差分和小波两个稀疏基的约束下,利用OOMP算法分别对线形压缩投影信息进行重构;并采用最小二乘法融合重构信号,提高数据精度。仿真实验结果表明,多稀疏基分簇压缩感知的WSN数据融合方法在减少数据发送的情况下,能提高整个网络的生命周期,解决采集数据精度与网络生命周期的矛盾。     

基于分簇的无线传感器网络簇内数据融合算法

根据节点剩余能量、通信消耗量和节点IP,设计无线传感器节点分簇算法,减少了无线传感器网络的数据传输总量。分析对以分簇为基础的簇内数据的融合算法误差成因,提出先进行簇内传感器测量修正、再进行簇内传感器数据融合的改进算法。通过TOSSIM仿真平台的实验,改进后的簇内数据融合算法测量误差明显减少。     

基于改进ACO的WSN感知数据传输策略研究

无线传感器网络(WSN)能够利用传感器节点快速准确地获取物理世界的信息从而作为物联网的感知层在监控领域得到了广泛的应用,而能量利用率是能量受限无线传感器网络的一个关键属性,直接影响网络的生命周期.经典的分层路由LEACH(及其变种)算法是无线传感器网络中最常见的节能路由协议.该文提出了一种改进的LEACH算法,由sin...     

异构传感器网络能量空洞分析与避免研究

在无线传感器网络中,由于sink附近的节点承担远方节点数据的转发,故能量消耗较高,容易在sink附近形成能量空洞而使网络提前死亡.针对由初始能量较大节点充当簇头节点与初始能量较小的节点作为普通节点组成的异构分簇无线传感器网络,提出了不等簇半径工作能量空洞避免策略.策略的核心是让近sink的簇半径较小,而远sink的簇半径较大,这样,近sink部署的初始能量较大的簇头节点较多,因而能够减弱能量空洞的影响,以达到能量消耗均衡的目的.将能量空洞避免问题转化为在保证网络寿命满足应用需求约束前提下如何使部署的节点最小的优化问题,并详细给出了不等簇半径的取值与优化方法.理论分析与实验结果表明,所提出的策略对网络寿命与性能有较大的改善,对于异构传感器网络建设有较好的指导意义.     

基于单向多汇聚节点的WSN分层路由协议

针对分层无线传感器网络的簇首节点容易成为网络瓶颈制约网络性能的不足,提出一种低能耗的路由协议。采用多汇聚（Sink）节点模式来构建网络,利用RSSI（接收信号强度指示）测出各传感器节点与各Sink节点之间的距离,并依据距离的远近为Sink节点划分作用域。通过传感器节点单向与所属Sink节点通信来降低簇首节点的负担。仿真实验结果表明提出的路由协议能有效克服簇首节点网络瓶颈问题,从而降低网络能耗,提高网络生存时间,对于无线传感器网络应用于大范围数据收集的网络具有重要的价值。     

A two-hop clustered image transmission scheme for maximizing network lifetime in wireless multimedia sensor networks

In traditional wireless sensor networks, normal sensor nodes which measure scalar physical phenomena like temperature, pressure and humidity usually compress the data before sending them out to minimize the communication energy consumption. However, this strategy may not be suitable for image transmission in wireless multimedia sensor networks. In the traditional clustering structure, when the camera-equipped node or the cluster head compresses the images, an energy hole will appear. This is a key factor that affects the lifetime of the network. To avoid the energy hole problem, a two-hop clustered image transmission scheme is proposed in this paper. In the proposed scheme, many redirectors are used to compress and forward the images for the purpose of reducing energy consumption of the camera-equipped node and the cluster head. With adaptive adjustment of the transmission radius in the camera cluster and tasks allocation based on the residual energy of the normal sensor nodes by the camera-equipped node, the energy consumption of the nodes in the network is balanced. The experimental results show that the proposed scheme can prolong the network lifetime dramatically in the case of the sensor nodes deployed densely.     

Particle swarm optimization based clustering algorithm with mobile sink for WSNs

Wireless sensor networks with fixed sink node often suffer from hot spots problem since sensor nodes close to the sink usually have more traffic burden to forward during transmission process. Utilizing mobile sink has been shown as an effective technique to enhance the network performance such as energy efficiency, network lifetime, and latency, etc. In this paper, we propose a particle swarm optimization based clustering algorithm with mobile sink for wireless sensor network. In this algorithm, the virtual clustering technique is performed during routing process which makes use of the particle swarm optimization algorithm. The residual energy and position of the nodes are the primary parameters to select cluster head. The control strategy for mobile sink to collect data from cluster head is well designed. Extensive simulation results show that the energy consumption is much reduced, the network lifetime is prolonged, and the transmission delay is reduced in our proposed routing algorithm than some other popular routing algorithms.     

EEHC: Energy efficient heterogeneous clustered scheme for wireless sensor networks

In recent years, there has been a growing interest in wireless sensor networks. One of the major issues in wireless sensor network is developing an energy-efficient clustering protocol. Hierarchical clustering algorithms are very important in increasing the network’s life time. Each clustering algorithm is composed of two phases, the setup phase and steady state phase. The hot point in these algorithms is the cluster head selection. In this paper, we study the impact of heterogeneity of nodes in terms of their energy in wireless sensor networks that are hierarchically clustered. We assume that a percentage of the population of sensor nodes is equipped with the additional energy resources. We also assume that the sensor nodes are randomly distributed and are not mobile, the coordinates of the sink and the dimensions of the sensor field are known. Homogeneous clustering protocols assume that all the sensor nodes are equipped with the same amount of energy and as a result, they cannot take the advantage of the presence of node heterogeneity. Adapting this approach, we introduce an energy efficient heterogeneous clustered scheme for wireless sensor networks based on weighted election probabilities of each node to become a cluster head according to the residual energy in each node. Finally, the simulation results demonstrate that our proposed heterogeneous clustering approach is more effective in prolonging the network lifetime compared with LEACH.     

WSN数据收集中移动sink的路径规划和蔟头节点选取问题的综合研究

针对较大规模的无线传感器网络通过多跳传输进行数据收集而引起的能量空洞问题,本文提出了一种基于移动sink的簇头节点数据收集算法（MSRDG）,该算法基于图论原理,在满足时延性的条件下,综合考虑了普通节点到簇头节点路由和移动sink遍历路经选取的问题,构建了一条通过的簇头节点尽可能多的移动轨迹。通过NS-2仿真软件对算法的性能进行评估,结果显示出该算法能减少数据的多跳传输,降低无线传感器网络节点的能量消耗,延长网络寿命。     

响应式簇结构的无线传感器网络路由算法

在无线传感器网络路由协议中利用分簇技术可以提高网络的存活时间。提出了一种基于响应式的簇结构路由算法（RCSA）。该算法的思想是应用节点间局部信息快速选举簇头,簇头之间以多跳的通信方式传输数据到汇聚节点,且不需要预先得知节点自身及其他节点的位置信息,大大节约了节点的能量消耗。仿真结果表明该路由算法有效地平衡了节点间的能量消耗,延长了网络的生存周期。     

基于压缩感知的传感器网络中概率负载均衡的数据路由协议

基于混合压缩感知(CS)理论,提出一种负载有效的路由协议.考虑分簇网络结构,簇内节点传输原始数据到簇头,簇头对数据进行压缩再通过最小生成树发送到sink.为防止簇头节点负载不均衡造成网络不能正常通信,提出负载度的概念并设计基于CS的负载均衡策略;然后,研究概率负载均衡策略以均衡所有节点的负载流量;最后,提出分布式补偿算法构建分簇网络并实现数据汇聚功能.仿真结果表明,所提出方法在提高网络生存时间及能耗均衡方面均优于传统方法.     

An energy-saving routing architecture with a uniform clustering algorithm for wireless body sensor networks

Wireless body sensor networks are expected to extend human-centered applications in large-scale sensing and detecting environments. Energy savings has become one of the most important features of the sensor nodes to prolong their lifetime in such networks. To provide reasonable energy consumption and to improve the network lifetime of wireless body sensor network systems, new and efficient energy-saving schemes must be developed. An energy-saving routing architecture with a uniform clustering algorithm is proposed in this paper to reduce the energy consumption in wireless body sensor networks. We adopted centralized and cluster-based techniques to create a cluster-tree routing structure for the sensor nodes. The main goal of this scheme is to reduce the data transmission distances of the sensor nodes by using the uniform cluster structure concepts. To make an ideal cluster distribution, the distances between the sensor nodes are calculated, and the residual energy of each sensor node is accounted for when selecting the appropriate cluster head nodes. On the basis of the uniform cluster location, the data transmission distances between the sensor nodes can be reduced by employing an adaptive multi-hop approach. The energy consumption is reduced, and the lifetime is extended for the sensor nodes by balancing the network load among the clusters. Simulation results show that the proposed scheme outperforms the previously known schemes in terms of the energy consumption and the network lifetime for the wireless body sensor networks.