无线传感器网络中能量感知目标定位算法

在传感器网络中节点能量有限,因此设计出能量高效的目标定位算法对于延长网络生命期、增强网络健壮性有着非常重要的意义.提出了一种能量高效的目标定位算法,并提出了在节点稀疏情况下保证定位精确性的方法.仿真表明,使用文中提出算法的传感器网络能大大地降低能量损耗.     

有向传感器网络覆盖控制策略

针对当前的有向传感器网络覆盖控制算法中主要存在的节点方向调节受限、优化程度有限、算法适用性单一等问题,提出了一种有向传感器网络覆盖控制策略(CCS,coverage control strategy),该策略经过严格的数学推导,形成一个分布式算法,能够广泛适用于不同网络下的不同节点感知模型。仿真实验表明,传感器节点运行CCS能够有效增强网络覆盖,并相比于现有的几种同类算法,具有一定的优越性。     

Mobile target tracking algorithm for wireless camera sensor networks with adjustable monitoring direction of nodes

Wireless camera sensor networks (WCSNs) possess a powerful physical environment monitoring capability. Camera nodes with adjustable monitoring directions further improve their flexibility. This study focuses on tracking multiple mobile targets to investigate the node scheduling and target location evaluation strategy of WCSNs on the basis of rotating nodes. By referring to existing research, this study improves the camera node monitoring and rotation model and proposes three network performance evaluation indicators. The proposed algorithm schedules nodes and their monitoring directions by using the unutilized energy of the nodes and the number of monitored targets. It also predicts the moving trends of the targets and selects active nodes by using the locations and linear speeds of the targets. Experimental results show that the proposed algorithm has a high target tracking accuracy. Compared with traditional target tracking algorithms, the proposed algorithm can effectively reduce the number of active nodes, balance the energy consumption between nodes, and prolong network lifetime.     

Coverage hole problem under sensing topology in flat wireless sensor networks

In flat wireless sensor networks, one fundamental issue is region coverage, which usually addresses whether the given region is sufficiently covered by sensing disks of sensor nodes or not. Although numerous research works have been carried out on region coverage, it still lacks in‐depth understanding on the relations between region coverage and sensing topology defined with the intersections of sensing areas of sensor nodes. In this paper, we consider the region coverage problem by using the sensing topology proposed in our previous work. Based on the notion of sensing topology, we prove that the given region can be partitioned into a number of the smallest cells, each of which is defined by sensing links among sensor nodes. Then, we investigate the sufficient and necessary conditions for the existence of coverage holes for the specific polygon graph residing in the partitioned cells. Further, two polynomial time algorithms are presented for dividing the given region covered by the whole network and detecting the coverage holes existing in the interior area of the partitioned cells, respectively. The experiment results show that our proposed algorithms are effective for detecting the coverage holes. Copyright © 2014 John Wiley & Sons, Ltd.     

面向资源节省的传感网动态目标自适应获取系统

针对图像传感网动态目标监测问题,搭建了面向资源节省的动态目标自适应获取系统Easi RS。利用存储空间复用技术减少存储资源需求;提出图像完整性自适应实时检测方法,解决由于目标动态性导致的连续图像的实时处理问题;在图像完整性实时检测的基础上,对获取的信息进行选择性传输,以减少传输数据量和传输能耗。通过室内和室外环境对该方法进行实验,结果表明,该系统不仅可以有效保证系统的感知性能,而且降低了存储开销和传输能耗。     

Theoretic analysis of unique localization for wireless sensor networks

Node self-localization has become an essential requirement for realistic applications over wireless sensor networks (WSNs). Although many distributed localization algorithms have been proposed, fundamental theoretic analysis of unique localization is still in its early stage of development. This paper aims at a synthetic and homogeneous survey of the theoretical basis on WSN localization problem carried out thus far. Specifically, subsequent to establishing a technological context of relevant terms, we construct a graph and then a formation for each WSN to present current state-of-the-art by analyzing possible conditions for unique localization, as well as corresponding verification algorithms, by drawing on the powerful results from rigidity theory, distance geometry, geometric constraints in CAD, and combinatorial theory. We show that the unique localization problem is well understood in two-dimension, however, only partial analogous results are available in three-dimension.     

基于全局贪心的有向传感器网络覆盖算法

针对分布式贪心算法（DGreedy）以传感器节点的剩余能量为优先级,节点处理顺序没有考虑相邻节点间的关系对网络覆盖率的影响,从而影响覆盖率的不足,在此提出了一种新的有向传感器网络覆盖算法。基于全局贪心的原则,以节点一重覆盖区域面积的大小为优先级,优先确定一重覆盖区域面积最大的传感器节点方向,从而保证传感器网络的一重覆盖区域面积更大,重叠覆盖区域较少。对比实验结果表明,该算法能有效提高覆盖率。     

Polytype target coverage scheme for heterogeneous wireless sensor networks using linear programming

Sensing coverage is one of fundamental problems in wireless sensor networks. In this paper, we investigate the polytype target coverage problem in heterogeneous wireless sensor networks where each sensor is equipped with multiple sensing units and each type of sensing unit can sense an attribute of multiple targets. How to schedule multiple sensing units of a sensor to cover multiple targets becomes a new challenging problem. This problem is formulated as an integer linear programming problem for maximizing the network lifetime. We propose a novel energy‐efficient target coverage algorithm to solve this problem based on clustering architecture. Being aware of the coverage capability and residual energy of sensor nodes, the clusterhead node in each cluster schedules the appropriate sensing units of sensor nodes that are in the active status to cover multiple targets in an optimal way. Extensive simulations have been carried out to validate the effectiveness of the proposed scheme. Copyright © 2012 John Wiley & Sons, Ltd.     

一种基于栅格预置点匹配的无线传感器网络目标定位方法

目标定位是无线传感器网络应用领域中一个重要的问题,是进行目标跟踪的前提和基础.节点呈栅格部署的无线传感器网络由于拓扑结构特殊,在目标定位应用领域具有独特的优势.本文基于栅格部署的无线传感器网络,提出了栅格预置点目标定位方法,通过设定和选择合适的栅格预置点进行目标定位.仿真实验和实际测试实验表明,该方法在定位准确性和实时性方面较先前的单层栅格定位和双层栅格定位都有较大幅度的提高.     

视觉传感器网络中基于RANSAC的顽健定位算法

视觉传感器网络由于节点故障或环境变化将导致节点对目标的观测数据出现错误,而基于最小二乘的多视觉信息融合定位方法将因此造成较大的定位误差。针对此问题提出一种基于集中式RANSAC的顽健定位算法,将错误数据进行筛选剔除,从而提高定位精度,进一步针对集中式 RANSAC 将会导致单个节点的计算复杂度过高而导致网络节点能耗不平衡问题,提出基于分布式 RANSAC 的顽健定位算法,从而将大量的迭代计算平均分布在各个节点中并行处理,在保证定位过程顽健性的同时保证了网络的计算能耗平衡性。最后通过实验对no-RANSAC、cen-RANSAC 和 dis-RANSAC算法的定位性能进行了比较,验证了该算法能够依照预定的概率获得良好的定位结果,并对算法的时间复杂度进行了分析。     

Multi‐target localization in wireless sensor networks: a compressive sampling‐based approach

This paper considers the problem of localizing a group of targets whose number is unknown by wireless sensor networks. At each time slot, to save energy and bandwidth resources, only part of sensor nodes are scheduled to activate to remain continuous monitoring of all the targets. The localization problem is formulated as a sparse vector recovery problem by utilizing the spatial sparsity of targets’ location. Specifically, each activated sensor records the RSS values of the signals received from the targets and sends the measurements to the sink node where a compressive sampling‐based localization algorithm is conducted to recover the number and locations of targets. We decompose the problem into two sub‐problems, namely, which sensor nodes to activate, and how to utilize the measurements. For the first subproblem, to reduce the effect of measurement noise, we propose an iterative activation algorithm to re‐assign the activation probability of each sensor by exploiting the previous estimate. For the second subproblem, to further improve the localization accuracy, a sequential recovery algorithm is proposed, which conducts compressive sampling on the least squares residual of the previous estimate such that all the previous estimate can be utilized. Under some mild assumptions, we provide the analytical performance bound of our algorithm, and the running time of proposed algorithm is given subsequently. Simulation results demonstrate the effectiveness of our algorithms.Copyright © 2013 John Wiley & Sons, Ltd.     

Energy-efficient target detection in sensor networks using line proxies

One of the fundamental and important operations in sensor networks is sink–source matching, i.e. target detection. Target detection is about how a sink finds the location of source nodes observing the event of interest (i.e. target activity). This operation is very important in many sensor network applications such as military battlefield and environment habitats. The mobility of both targets and sinks brings significant challenge to target detection in sensor networks. Most existing approaches are either energy inefficient or lack of fault tolerance in the environment of mobile targets and mobile sinks. Motivated by these, we propose an energy-efficient line proxy target detection (LPTD) approach in this paper. The basic idea of LPTD is to use designated line proxies as rendezvous points (or agents) to coordinate mobile sinks and mobile targets. Instead of having rendezvous nodes for each target type as used by most existing approaches, we adopt the temporal-based hash function to determine the line in the given time. Then the lines are alternated over time in the entire sensor network. This simple temporal-based line rotation idea allows all sensor nodes in the network to serve as rendezvous points and achieves overall load balancing. Furthermore, instead of network-wide flooding, interests from sinks will be flooded only to designated line proxies within limited area. The interest flooding can further decrease if the interest has geographical constraints. We have conducted extensive analysis and simulations to evaluate the performance of our proposed approach. Our results show that the proposed approach can significantly reduce overall energy consumption and target detection delay. Copyright © 2007 John Wiley & Sons, Ltd.     

QoS‐aware target coverage in wireless sensor networks

Wireless sensor networks have emerged recently as an effective way of monitoring remote or inhospitable physical targets, which usually have different quality of service (QoS) constraints, i.e., different targets may need different sensing quality in terms of the number of transducers, sampling rate, etc. In this paper, we address the problem of optimizing network lifetime while capturing those diversified QoS coverage constraints in such surveillance sensor networks. We show that this problem belongs to NP‐complete class. We define a subset of sensors meeting QoS requirements as a coverage pattern, and if the full set of coverage patterns is given, we can mathematically formulate the problem. Directly solving this formulation however is difficult since number of coverage patterns may be exponential to number of sensors and targets. Hence, a column generation (CG)‐based approach is proposed to decompose the original formulation into two subproblems and solve them iteratively. Here a column corresponds to a feasible coverage pattern, and the idea is to find a column with steepest ascent in lifetime, based on which we iteratively search for the maximum lifetime solution. An initial feasible set of patterns is generated through a novel random selection algorithm (RSA), in order to launch our approach. Experimental data demonstrate that the proposed CG‐based approach is an efficient solution, even in a harsh environment. Simulation results also reveal the impact of different network parameters on network lifetime, giving certain guidance on designing and maintaining such surveillance sensor networks. Copyright © 2009 John Wiley & Sons, Ltd.     

无线多媒体传感器网络部署控制算法

已有的无线多媒体传感器网络（WMSNs）研究针对传感器放置在目标区域内的情况进行,且没有考虑节点通过云台的转动获得的整个可能感知区域对覆盖率的影响。本文首先针对节点放置点高于目标区域的应用进行研究,综合考虑节点感知区域和可能感知区域,建立了延时和无延时感知模型,并针对不同的感知模型提出了传感器网络部署控制算法（IVPDCA）,算法中改进了虚拟势场算法,定义了节点质量的概念来表示节点间覆盖重叠的大小,建立受力模型,使得节点在合力作用下进行重新部署,同时关闭冗余节点,既延长了网络寿命,又提高了区域覆盖率。仿真结果验证了算法的有效性。     

Efficient closed-form solution for target localization using TDOA measurements in the presence of sensor position errors

An efficient solution for locating a target was proposed, which by using time difference of arrival (TDOA) measurements in the presence of random sensor position errors to increase the accuracy of estimation. The cause of position estimation errors in two-stage weighted least squares (TSWLS) method is analyzed to develop a simple and effective method for improving the localization performance. Specifically, the reference sensor is selected again and the coordinate system is rotated according to preliminary estimated target position by using TSWLS method, and the final position estimation of the target is obtained by using weighted least squares (WLS). The proposed approach exhibits a closed-form and is as efficient as TSWLS method. Simulation results show that the proposed approach yields low estimation bias and improved robustness with increasing sensor position errors and thus can easily achieve the Cramer-Rao lower bound (CRLB) easily and effectively improve the localization accuracy.     

Scheduling sensor activity for information coverage of discrete targets in sensor networks

In this paper, we study the problem of scheduling sensor activity to cover a set of targets with known locations such that all targets can be monitored all the time and the network can operate as long as possible. A solution to this scheduling problem is to partition all sensors into some sensor covers such that each cover can monitor all targets and the covers are activated sequentially. In this paper, we propose to provide information coverage instead of the conventional sensing disk coverage for target. The notion of information coverage is based on estimation theory to exploit the collaborative nature of geographically distributed sensors. Due to the use of information coverage, a target that is not within the sensing disk of any single sensor can still be considered to be monitored (information covered) by the cooperation of more than one sensor. This change of the problem settings complicates the solutions compared to that by using a disk coverage model. We first define the target information coverage (TIC) problem and prove its NP‐completeness. We then propose a heuristic to approximately solve our problem. Simulation results show that our heuristic is better than an existing algorithm and is close to the upper bound when only the sensing disk coverage model is used. Furthermore, simulation results also show that the network lifetime can be significantly improved by using the notion of information coverage compared with that by using the conventional definition of sensing disk coverage. Copyright © 2008 John Wiley & Sons, Ltd.     

信标节点漂移情况下的无线传感器网络节点定位机制

针对信标节点漂移情况下的节点定位问题,提出了一种分布式的信标节点漂移检测方法,采用节点自评分和协商机制,自动寻找可能发生了漂移的信标节点,同时针对大量信标节点发生漂移后的定位覆盖率下降问题,构建普通节点的定位可信度模型,并在定位盲区内使用一些较为可靠的普通节点作为临时信标节点进行定位。仿真实验表明,该算法在误检测、定位误差方面性能优于传统算法,具有较低的通信开销、较高的实用性和灵活性。     

动态热释电传感器网络目标跟踪技术研究

提出了一种动态热释电红外辐射传感器网络的目 标 跟踪方法,使热释电传感器在运动状态下进行目标探测,通过采集、分析 动态热释电传感器输出的信号特征可得到目标的角度信息;使用传感器网络目标定位数 学模型, 对多个节点的信息进行融合即可实现运动目标的定位及跟踪,并有效解决了热释电 探测距离及探测角度的矛盾问题。实验表明,所提方法可在大范围对目标进行定时监控及自 主跟踪,在探测范围及灵敏度、定位精度 等方面具有很大优势。     

无线传感器网络中检测女巫攻击的节点定位方法

为了有效抵制女巫攻击,在攻击存在的情况下提高无线传感器网络节点的定位精度,分析、总结了女巫攻击所固有的薄弱环节,提出了基于接收功率验证的检测女巫攻击的节点安全定位方法。检测机制分为两步,首先检测节点通过比较接收功率,从所接收的全部信标节点中选择出距其距离相同的信标节点,列为可疑Sybil节点,然后通过邻居节点间的信息交互和距离验证,最终检测出攻击节点,利用去除了Sybil节点的信标节点集合实现定位。仿真实验显示,当存在攻击时,检测成功概率能达到95%以上,定位精度提高了9～11.64 m,表明该方法能有效检测女巫攻击,实现节点安全定位。     

Monte Carlo localization for mobile wireless sensor networks

Localization is crucial to many applications in wireless sensor networks. In this article, we propose a range-free anchor-based localization algorithm for mobile wireless sensor networks that builds upon the Monte Carlo localization algorithm. We concentrate on improving the localization accuracy and efficiency by making better use of the information a sensor node gathers and by drawing the necessary location samples faster. To do so, we constrain the area from which samples are drawn by building a box that covers the region where anchors’ radio ranges overlap. This box is the region of the deployment area where the sensor node is localized. Simulation results show that localization accuracy is improved by a minimum of 4% and by a maximum of 73% (average 30%), for varying node speeds when considering nodes with knowledge of at least three anchors. The coverage is also strongly affected by speed and its improvement ranges from 3% to 55% (average 22%). Finally, the processing time is reduced by 93% for a similar localization accuracy.