Analytical framework for adaptive compressive sensing for target detection within wireless visual sensor networks

Multimedia Tools and Applications - Wireless visual sensor networks (WVSNs) are composed of a large number of visual sensor nodes covering a specific geographical region. This paper addresses the...     

无线传感器网络中被捕获节点的检测技术综述

无线传感器网络在许多应用场合都需要采集比较敏感的数据,因此安全问题至关重要。一旦传感器节点被捕获,且没有采取相应的措施,该节点内的所有信息将会泄露。利用被捕获节点,攻击者可在网络内发起内部攻击,导致网络的安全性能急剧下降。如何检测被捕获节点,目前已有多种技术可以解决这个问题。文章对目前的检测技术作了总结,并对未来的研究方向做了展望。     

CCS-MAC: Exploiting the overheard data for compression in wireless sensor networks

Both the overhearing and overhearing avoidance in a densely distributed sensor network may inevitably incur considerable power consumption. In this paper we propose a so-called CCS-MAC (collaborative compression strategy-based MAC) MAC protocol which facilitates to exploit those overheard data that is treated useless in traditional MAC protocols for the purpose of cost and energy savings. Particularly the CCS-MAC enables different sensor nodes to perform data compression cooperatively with regard to those overheard data, so that the redundancy of data prepared for the link layer transmission can be totally eliminated at the earliest. The problem of collaborative compression is analyzed and discussed along with a corresponding linear programming model formulated. Based on it a heuristic node-selection algorithm with a time complexity of (O(N²)) is proposed to the solve the linear programming problem. The node-selection algorithm is implemented in CCS-MAC at each sensor node in a distributed manner. The experiment results verify that the proposed CCS-MAC scheme can achieve a significant energy savings so as to prolong the lifetime of the sensor networks so far.     

Identifying defective nodes in wireless sensor networks

Wireless sensor networks (WSNs) have become ubiquitous, e.g., in logistics, smart manufacturing, smart city infrastructures or vehicular ad-hoc networks. WSNs tend to rely on ad-hoc infrastructures that are prone to a wide range of different defects, e.g., communication failures, faulty sensors or nodes that have been tampered with. Additionally, dealing with defects is challenging, as defects might occur only occasionally. In this paper, we introduce SEDEL, our approach for Sensor nEtwork DEfect Localization. SEDEL helps the WSN operator to pinpoint defective nodes in the routing topology of a WSN. In particular, we let the operator store graph representations of the routing topology, together with information if the WSN has produced errors. Based on this information, SEDEL assigns each WSN node a suspiciousness score that is correlated with the defect probability. Thus, our approach can be used with any kind of defect, and the kind does not have to be known, as long as the operator can decide if a certain processing is correct or not. We have evaluated SEDEL with a real sensor-node deployment. Our evaluation shows that the defective node is assigned a high probability in the vast majority of the experiments.     

Fault-resilient sensing in wireless sensor networks

Research on wireless sensor networks (WSNs) has received tremendous attention in the past few years due to their potential applications and advances in the VLSI design. In WSNs with tiny sensors, mobility of a sink may provide an energy efficient way for data dissemination. Having a mobile sink in WSN, however, creates new challenges to routing and sensor distribution modeling in the network. In this paper, based on clustering and routing optimization algorithms, we propose a new scheme called K-means and TSP-based mobility (KAT mobility). After clustering the sensor nodes, the proposed method navigates the mobile sink to traverse through the cluster centers according to the trajectory of an optimized route. The mobile sink then collects the data from sensors at the visited clusters. Simulation results have demonstrated that the proposed scheme can provide not only better energy efficiency as compared to those obtained by conventional methods which assume random waypoint for the mobile sink, but also fault-resilience in case of malfunctions of some sensors due to attacks.     

无线传感器网络节点调度优化分簇算法研究*

节点调度优化分族算法根据网络节点部署的特点,在不影响网络服务质量的情况下,通过冗余节点调度优化分族的方法能有效减少网络中工作节点的数量,从而节约网络平均每一轮的网络能耗.仿真结果表明,与未考虑冗余节点状态调度的算法相比,节点调度优化分簇算法有效提高了网络能量利用率,延长了网络寿命.     

基于视觉传感器网络的飞机识别系统

利用3D-MAX建立了三种飞机模型, 设计了三维飞机目标图像库。在该图像库中按不同的飞机模型分为三个大类, 每个大类中按不同的飞行姿态分为24个组。论述了三类飞机图片的纹理特征的提取方法, 并通过基于贴近度的多传感器一致性融合方法计算每类飞机图像的对比度融合值、熵融合值、逆差距特征融合值, 通过最小距离法对测试对象的归类进行预判断。介绍了K-L变换、降维特征矩阵空间与投影系数向量, 计算了图库中每张图像在降维特征矩阵空间投影的系数向量, 以及测试图像在降维特征矩阵空间投影的系数向量。然后介绍了Fisher最佳鉴别向量与判别规则, 以图像在特征子空间投影的系数向量作为对象, 通过对每组图像正样本与负样本的训练得出最佳鉴别向量, 通过Fisher判别规则判断测试目标的类别与飞行姿态。通过实验证明了识别系统的高识别率, 以及可以对飞机复杂飞行姿态进行判断。     

视频传感器网络覆盖问题

视频监控已经被广泛应用于各种场景,为安全防卫提供了有效信息。综述视频传感器网络中覆盖问题的相关研究。视频传感器网络具有有向传感器网络的一般特征。考虑到监测对象通常有面部朝向属性,视频传感器网络的感知模型又不同于一般的有向传感器网络的感知模型。根据感知模型是否考虑监测目标的朝向,分别介绍视频传感器网络中的点覆盖、区域覆盖和栅栏覆盖问题的典型算法。此外,讨论了目前研究存在的问题以及未来可能的研究方向。     

无线传感器网络中的簇头节点能耗平衡策略

无线传感器网络（WSNs）具有集中式数据收集和多对一数据通信等特点,使得越靠近汇聚节点的簇头节点能耗越大,最终导致网络中心出现能量空洞。提出一种基于簇内节点分配的簇头节点能耗平衡策略,根据WSNs的分簇汇聚拓扑结构,分析了其中簇头节点的能量消耗情况;在此基础上,通过在各簇内分配一定数量的基本节点,并成比例地增加附加节点的方式,使网络中各簇头节点的能量消耗相等。仿真结果表明：该策略能够适应网络规模和负载的动态变化,最终达到平衡簇头节点能耗的目的。     

无线传感网络节点非视距定位方法的改进

在无线传感器网络定位中,节点精确定位面临的一个主要问题是信号的非视距传播,非视距误差是节点定位误差的主要来源。在分析基于位置残差检测的非视距误差抑制技术的基础上,提出了基于近似最大似然估计技术和残差检测技术的非视距定位算法。算法通过逐步减少视距信号个数的组合方式,在每一步选取残差最小的组合,利用改进的距离残差定位方法进行节点定位。通过理论分析与仿真比较,均表明改进算法的性能接近于PRT算法的性能,但能大大降低PRT算法的计算复杂度,验证了改进方法的优越性。     

无线传感器网络节点近点加权质心定位方法

节点定位技术是无线传感器网络（WSNs）的基础技术,具有重要的研究意义。质心算法与基于RSSI的质心算法是目前常用的定位方法,但前者定位误差大,后者对每个信标节点进行加权定位,这在提高精度的同时也增加计算量和干扰因素（如路径衰减因子等）。基于此,提出一种利用距未知节点最近的若干个信标节点的位置修正其他信标节点的位置的近点加权质心算法,以提高初次定位的精度。进而,可以通过改变最近点、次近点、所有点位置之和三者的权值对初次定位进行校正。仿真结果表明了所提算法的有效性。     

无线传感器网络节点的低功耗设计

无线传感器网络(WSNs)能够协作地实时监测、感知和采集各种环境对象的信息,并将信息传递给系统用户主机进行分析处理。节点具有感知和路由的功能,在实际的应用中,功耗是影响节点工作寿命的关键因素。设计分析了WSNs系统功率消耗的构成,并从硬件和软件方面提出和总结了WSNs的低功耗设计方法,设计了一种低功耗的WSNs节点,并进行了测试,结果证明:该方法适合WSNs节点的应用,具有易使用、低功耗特点。     

一种线性无线传感器网络的节点布置方案

线型无线传感器网络在应用中比较常见，其监控区域接近于线条。在基站收集感应数据的过程中，离基站越近的区域需要转发的数据越多，数据流量越大。如果采用通常的均匀布置传感器节点方案，则基站附近的节点将很快消耗完能量，基站也就无法收集数据。通过研究线型无线传感器网络中的能量消耗，得到了布置传感器节点的密度公式。按照此密度公式布置传感器节点，可使得各区域的总能量与能量消耗速度之比达到平衡，从而延长系统生命期。理论分析和仿真实验表明，在监控区域较大时，以此方案布置传感器节点，可将系统生命期提高到均匀布置方案的2倍。     

保持覆盖的无线传感器网络簇内节点调度方法

为了延长无线传感器网络的生命周期,提高节点能量利用效率,将簇与节点调度相结合,提出了保持覆盖的无线传感器网络簇内节点调度。首先将网络分簇,然后每个簇内的节点,按节点号自小到大的顺序依次计算每个节点与簇内邻居节点的距离,并判断所有距离小于监测半径的邻居节点能否对自己实现圆周覆盖,从而判断自己是否是冗余节点。利用Matlab仿真表明,一方面该算法可以有效减少网络的能量消耗,延长网络生命周期;另一方面该算法的调度效率与网络节点密度以及节点监测半径都有密切关系。     

农田环境信息监测的无线传感器网络节点设计

针对电子信号干扰、能耗大等因素对通信能力造成的影响,设计了基于低功耗微处理器MSP430的无线传感器网络节点.通过使用MCU的不同工作模式和对无线射频模块的不同状态等节能措施,增强了节点通信能力,大幅度降低了节点的能耗.经过背景项目实际农田环境的测试证明:节点不仅能够完成对农田环境要求信息进行准备采集,网络通信效率也得...     

基于VWMC的传感器网络移动节点定位算法

为了解决无线传感器网络移动节点定位精度低、计算方法复杂以及响应时间长的问题,提出了一种基于VWMC的传感器网络移动节点定位算法(VWMCL).该算法利用Monte Carlo算法作为移动节点的基本定位算法,并在预测阶段加入航位推算方法,通过减少预测角度的误差来提高粒子位置预测的精度;并把Voronoi图和权值融合在MCL算法的粒子过滤阶段,采用Voronoi图和权值的双重筛选的机制,提高粒子过滤的准确性.仿真结果表明,该算法可以显著改善定位精度,减少算法的计算量,从而提高定位的效率.     

无线传感器网络节点定位问题研究

节点定位技术是无线传感器网络信息采集、传输和处理能力的基础技术之一。研究和分析了各类无线传感器节点定位技术,从定位精度、健壮性等方面分析总结当前无线传感器网络定位技术存在的问题,展望未来的研究前景与应用发展趋势。     

Existence of dumb nodes in stationary wireless sensor networks

Wireless sensor networks (WSNs), which are typically autonomous and unattended, require energy-efficient and fault-tolerant protocols to maximize the network lifetime and operations. In this work, we consider a previously unexplored aspect of the sensing nodes – dumb behavior. A sensor node is termed as “dumb”, when it can sense its surroundings, but cannot communicate with its neighbors due to shrinkage in communication range attributed to adverse environmental effects and can behave normally in the presence of favorable environment. As a result of this temporary behavior, a node may get isolated from the network when adverse environmental effects are present, but re-connects with the network with the resumption of favorable environmental conditions. We consider the effects of dumb nodes on the, otherwise, energy-efficient stationary WSNs having complete network coverage achieved using sufficient number of activated sensor nodes. While the presence of redundancy in the deployment of nodes, or the number of active nodes can guarantee communication opportunities, such deployment is not necessarily energy-efficient and cost-effective. The dumb behavior of nodes results in wastage of power, thereby reducing the lifetime of a network. Such effects can be detrimental to the performance of WSN applications. The simulation results exhibit that the network performance degrades in the presence of dumb nodes in stationary WSNs.     

无线传感器网络中的协作节点个数优化

为了提高无线传感器网络的能量效率,传感器节点采用空时编码协作和收端分集协作来传输信息.通过分析传感器节点的电路能耗和传输能耗,分别给出了两种协作方式下的网络总能耗.研究表明,对于每种协作方式,传输距离一定时,通过优化接收端协作节点的个数,可以使总能耗降低,传输距离不同时.最优的协作节点个数也不同.仿真结果显示,优化的收端分集协作总比传统的无协作方式能耗低,而当传输距离大于一个门限值时,优化后的空时编码协作优于收端分集协作.     

Using central nodes for efficient data collection in wireless sensor networks

We study the problem of data collection in Wireless Sensor Networks (WSN). A typical WSN is composed of wireless sensor nodes that periodically sense data and forward it to the base station in a multi-hop fashion. We are interested in designing an efficient data collection tree routing, focusing on three optimization objectives: energy efficiency, transport capacity, and hop-diameter (delay).In this paper we develop single- and multi-hop data collection, which are based on the definition of node centrality: centroid nodes. We provide theoretical performance analysis for our approach, present its distributed implementation and discuss the different aspects of using it. Most of our results are for two-dimensional WSNs, however we also show that the centroid-based approach is asymptotically optimal in three-dimensional random node deployments. In addition, we present new construction for arbitrary network deployment based on central nodes selection. We also present extensive simulation results that support our theoretical findings.