无线传感器网络节点的自身定位

无线传感器网络的自身节点的定位对网络来说是非常重要的，传感器节点是随机分布在网络中的，这关系到网络最终的定位精度；节点自身定位的方法从节点的个数主要有单点定位和两个节点的定位，这里提出另一种定位方法，运用三个节点实现传感器网络的节点定位。     

Hybrid area exploration–based mobility‐assisted localization with sectored antenna in wireless sensor networks

In common practice, sensor nodes are randomly deployed in wireless sensor network (WSN); hence, location information of sensor node is crucial in WSN applications. Localization of sensor nodes performed using a fast area exploration mechanism facilitates precise location‐based sensing and communication. In the proposed localization scheme, the mobile anchor (MA) nodes integrated with localization and directional antenna modules are employed to assist in localizing the static nodes. The use of directional antennas evades trilateration or multilateration techniques for localizing static nodes thereby resulting in lower communication and computational overhead. To facilitate faster area coverage, in this paper, we propose a hybrid of max‐gain and cost‐utility–based frontier (HMF) area exploration method for MA node's mobility. The simulations for the proposed HMF area exploration–based localization scheme are carried out in the Cooja simulator. The paper also proposes additional enhancements to the Cooja simulator to provide directional and sectored antenna support. This additional support allows the user with the flexibility to feed radiation pattern of any antenna obtained either from simulated data of the antenna design simulator, ie, high frequency structure simulator (HFSS) or measured data of the vector network analyzer (VNA). The simulation results show that the proposed localization scheme exhibits minimal delay, energy consumption, and communication overhead compared with other area exploration–based localization schemes. The proof of concept for the proposed localization scheme is implemented using Berkeley motes and customized MA nodes mounted with indigenously designed radio frequency (RF) switch feed network and sectored antenna.     

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.     

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.     

基于序列的传感器网络节点定位算法

针对MSP算法需要借助额外的外部扫描设备,不适合应用于对野外大规模部署的传感器网络进行定位这一缺点,提出了一种HG-MSP算法。该算法通过锚节点发出扫描信息,不需要额外的外部设备进行辅助定位,提高了算法的可用性。仿真实验表明,在去掉辅助设备的情况下,算法的定位精度并无明显下降。     

改进遗传算法优化无线传感器网络路由算法

为了有效延长无线传感器网络的生存时间,针对传感器节点能耗不均衡难题,提出一种改进遗传算法优化的无线传感器网络路由算法。首先对LEACH算法不足进行分析,然后构建簇头节点选择的目标函数,并将其作为遗传算法的搜索目标,最后通过遗传算法找到下一时刻簇头的候选节点,并针对遗传算法不足进行相应改进。采用仿真实验对算法的性能进行分析,结果表明,相对于其它无线传感器路由算法,本文算法可以保证无线传感器的节点能量均衡,延长了网络的生存时间。     

基于改进DV-Hop的无线传感器网络节点定位算法

针对DV-Hop距算法定位误差大的难题,提出一种改进离估计误差,并利用DV-Hop的传感器节点定位算法。首先修正知节点与信标节DV-Hop算法对节点进行定位;然后对进V-Hop算法定位误差行校正,最后在Matlab 2012平台上对算法性能进行仿真分析。仿真结果表明,本文算法可以较好地克服DV-Hop算法存在的不足,提高了传感器节点的定位精度。     

多Sink动态传感器网络主动式分层定位方法

针对多Sink动态无线传感器网络，提出一种主动式分层定位方法，采用事件驱动的主动式分层定位，不但能减少传感器节点的定位开销、延长网络的寿命，而且能够适应节点动态移动的场景。     

无线传感器网络节点定位技术综述

无线传感器网络在许多领域有着重要的科研和使用价值,网络中传感器节点自身定位可为无线传感器网络的很多应用提供基础信息,是重要研究方向之一.从无线传感器网络节点定位技术的研究意义与应用价值出发,介绍了节点定位技术的基本原理与方法,并讨论了定位算法的评价标准,最后对节点定位技术的发展方向进行了展望.     

Jamming detection approach based on fuzzy assisted multicriteria decision‐making system for wireless sensor networks

The jamming detection approach based on fuzzy assisted multicriteria decision‐making system (JDA) is proposed to detect the presence of jamming in downstream communication for Cluster based Wireless Sensor Network (CWSN). The proposed approach is deployed in cluster head (CH). The JDA functions in two aspects: First, the CH periodically measures the jamming detection metrics namely Packet Delivery Ratio (PDR) and Received Signal Strength Indicator (RSSI) of every node in the cluster to determine the behavior of the sensor nodes. In order to determine the behavior of members in the cluster, the CH compares the measured PDR with the PDR threshold. If the measured PDR is lesser than the PDR threshold, then CH applies the TOPSIS method on the PDR and RSSI metrics to determine the presence of jamming. These metrics are considered as the criteria and the nodes or the members are considered to be the alternatives. Next, the fuzzy logic is applied on the results obtained from the TOPSIS method to optimize the jamming detection metrics and identify the presence of jamming accurately. The proposed jamming detection approach detects well and arrives at 99.6% jamming detection rate as shown in simulation.     

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.     

无线传感器网络SL-n迭代定位算法

无线传感器网络迭代多边定位算法在迭代定位过程中使用全局最小均方估计(MMSE)方法估计盲节点的位置,导致算法定位误差很大,缺乏稳健性。针对此问题,提出了SL-n估计方法,该方法首先把某盲节点的所有参考节点进行分组,通过三边法或局部MMSE方法求出的每组相应样本值,并用这些样本值估计出此盲节点的位置。仿真实验表明,当部分参考节点的参考误差较大时,该方法优于全局MMSE处理方法,可以有效降低定位误差。     

利用移动内点来修复传感器网络空洞的算法

针对目标区域中存在感知空洞问题,提出了一种空洞修复准则。在此基础上,设计了基于移动节点无需地理信息的修复算法SOI,该算法通过计算空洞边缘可移动的最佳内点,使该边缘节点到达新的位置,实现减少目标区域中空洞面积的目的。分析与仿真实验表明,与VHR算法相比,SOI算法在部署密集的传感网络中需要移动的总距离更少。     

A cluster‐based fault‐tolerant routing protocol for wireless sensor networks

Energy conservation and fault tolerance are two critical issues in the deployment of wireless sensor networks (WSNs). Many cluster‐based fault‐tolerant routing protocols have been proposed for energy conservation and network lifetime maximization in WSNs. However, these protocols suffer from high frequency of re‐clustering as well as extra energy consumption to tolerate failures and consider only some very normal parameters to form clusters without any verification of the energy sufficiency for data routing. Therefore, this paper proposes a cluster‐based fault‐tolerant routing protocol referred as CFTR. This protocol allows higher energy nodes to become Cluster Heads (CHs) and operate multiple rounds to diminish the frequency of re‐clustering. Additionally, for the sake to get better energy efficiency and balancing, we introduce a cost function that considers during cluster formation energy cost from sensor node to CH, energy cost from CH to sink, and another significant parameter, namely, number of cluster members in previous round. Further, the proposed CFTR takes care of nodes, which have no CH in their communication range. Also, it introduces a routing algorithm in which the decision of next hop CH selection is based on a cost function conceived to select routes with sufficient energy for data transfer and distribute uniformly the overall data‐relaying load among the CHs. As well, a low‐overhead algorithm to tolerate the sudden failure of CHs is proposed. We perform extensive simulations on CFTR and compare their results with those of two recent existing protocols to demonstrate its superiority in terms of different metrics.     

针对虫洞攻击的无线传感器网络安全定位方法

节点定位技术是无线传感器网络的关键技术之一,是很多基于无线传感器网络的应用的基础。然而,无线传感器网络通常部署在无人值守的敌对环境中,攻击节点能够很容易地破坏网络中节点的定位过程。本文针对无线传感器网络中距离无关的定位技术,分析了虫洞攻击对DV-Hop定位过程的影响,提出了一种无线传感器网络中抵御虫洞攻击的DV-Hop安全定位方法。仿真结果表明所提出的安全定位方法能够有效降低虫洞攻击对DV-Hop定位过程的影响,验证了该方法的有效性。     

Performance analysis of channel estimation in amplify‐and‐forward multi‐hop direct forwarding wireless networks

In this paper, we study the performance of a training‐based least square (LS) and linear minimum mean‐square‐error (LMMSE) channel estimation for both hop‐by‐hop and multi‐hop direct forwarding wireless sensor networks over frequency‐selective fading channels. Specifically, to investigate the properties of the channel estimation, we accomplish a theoretical analysis of MSE in terms of various link parameters. From the performance evaluation, we analytically present the effects of the number of hops on the MSE performance for channel estimations in both multi‐hop networks. Interesting observations of MSE behaviors under various conditions are discussed, and the receiver complexity and channel equalization performance are also analyzed. Finally, through the computer simulations, the analytical results and detection performance are demonstrated. Copyright © 2014 John Wiley & Sons, Ltd.     

基于云计算的矿井无线传感网络火情远程监控系统

针对矿井实际需求情况,提出了一种基于云计算的无线传感网络火情远程监控系统,此系统包括通讯基站、无线传感器网络和云计算平台,其中,无线传感器网络通过通讯基站与云计算平台相连接。它包括用于采集煤矿安全数据的无线传感器、执行器和用于传输煤矿安全数据的无线网关。该系统具备低成本、自组织、低功耗、信息交互方便的特点,具有很好的应用前景。     

Prediction‐based cluster management for target tracking in wireless sensor networks

The key impediments to a successful wireless sensor network (WSN) application are the energy and the longevity constraints of sensor nodes. Therefore, two signal processing oriented cluster management strategies, the proactive and the reactive cluster management, are proposed to efficiently deal with these constraints. The former strategy is designed for heterogeneous WSNs, where sensors are organized in a static clustering architecture. A non‐myopic cluster activation rule is realized to reduce the number of hand‐off operations between clusters, while maintaining desired estimation accuracy. The proactive strategy minimizes the hardware expenditure and the total energy consumption. On the other hand, the main concern of the reactive strategy is to maximize the network longevity of homogeneous WSNs. A Dijkstra‐like algorithm is proposed to dynamically form active cluster based on the relation between the predictive target distribution and the candidate sensors, considering both the energy efficiency and the data relevance. By evenly distributing the energy expenditure over the whole network, the objective of maximizing the network longevity is achieved. The simulations evaluate and compare the two proposed strategies in terms of tracking accuracy, energy consumption and execution time. Copyright © 2010 John Wiley & Sons, Ltd.     

PRDA: polynomial regression‐based privacy‐preserving data aggregation for wireless sensor networks

In wireless sensor networks, data aggregation protocols are used to prolong the network lifetime. However, the problem of how to perform data aggregation while preserving data privacy is challenging. This paper presents a polynomial regression‐based data aggregation protocol that preserves the privacy of sensor data. In the proposed protocol, sensor nodes represent their data as polynomial functions to reduce the amount of data transmission. In order to protect data privacy, sensor nodes secretly send coefficients of the polynomial functions to data aggregators instead of their original data. Data aggregation is performed on the basis of the concealed polynomial coefficients, and the base station is able to extract a good approximation of the network data from the aggregation result. The security analysis and simulation results show that the proposed scheme is able to reduce the amount of data transmission in the network while preserving data privacy. Copyright © 2013 John Wiley & Sons, Ltd.     

Position‐based adaptive quantization for target location estimation in wireless sensor networks using one‐bit data

The problem of target location estimation in a wireless sensor network is considered, where due to the bandwidth and power constraints, each sensor only transmits one‐bit information to its fusion center. To improve the performance of estimation, a position‐based adaptive quantization scheme for target location estimation in wireless sensor networks is proposed to make a good choice of quantizer' thresholds. By the proposed scheme, each sensor node dynamically adjusts its quantization threshold according to a kind of position‐based information sequences and then sends its one‐bit quantized version of the original observation to a fusion center. The signal intensity received at local sensors is modeled as an isotropic signal intensity attenuation model. The position‐based maximum likelihood estimator as well as its corresponding position‐based Cramér–Rao lower bound are derived. Numerical results show that the position‐based maximum likelihood estimator is more accurate than the classical fixed‐quantization maximum likelihood estimator and the position‐based Cramér–Rao lower bound is less than its fixed‐quantization Cramér‐Rao lower bound. Copyright © 2015 John Wiley & Sons, Ltd.