Experimental studies of using wireless energy transmission for powering embedded sensor nodes

A major challenge impeding the deployment of wireless sensor networks for structural health monitoring (SHM) is developing a means to supply power to the sensor nodes in an efficient manner. In this paper, we explore possible solutions to this challenge by using a mobile-host based wireless energy transmission system to provide both power and data interrogation commands to sensor nodes. The mobile host features the capability of wirelessly transmitting energy to sensor nodes on an as-needed basis. In addition, it serves as a central data repository and processing center for the data collected from the sensing network. The wirelessly transmitted microwave energy is captured by a receiving antenna, transformed into DC power by a rectifying circuit, and stored in a storage medium to provide the required energy to the sensor node. The application of wireless energy transmission is targeted toward SHM sensor nodes that have been recently developed by the authors, which can be used to collect peak mechanical displacements or piezoelectric impedance measurements. This paper will describe considerations needed to design such energy transmission systems, experimental procedure and results, method of increasing the efficiency, energy conditioning circuits and storage medium, and target applications. Experimental results from a field test on the Alamosa Canyon Bridge in southern New Mexico will also be presented.     

无线传感器网络中继节点布居算法的研究

本文表述的是在该应用背景下引入多约束条件, 并采用枚举法与贪婪寻优算法相结合的方法, 解决了在可以作为中继节点设置位置的预设中继节点位置集合内, 合理选择中继节点设置位置以及既存网络因添加新传感器节点所引起的中继节点追加的问题. 仿真实验表明, 本文提出的中继节点布居与追加优化算法能够保证多约束条件下网络的容错性. 同时提出的基于最小网络距离因子评价标准, 有效提高了中继节点布居算法的能效性.     

基于嵌入式操作系统的无线电力监测系统设计

为了对各个用电设备或用电用户的电力使用情况进行精细化监测,从而对电力评估、管理起到基础性作用,设计了一种基于Contiki嵌入式操作系统的无线电力监测系统,以6LoWPAN作为无线通信协议;该系统由终端节点、路由节点、接入节点、GPRS模块及计算机数据中心构成;介绍了基于TV3154、TA5212及信号调理滤波网络、ADE7653电力测量、MSP430F1611主控及CC2420射频的终端节点、接入节点硬件设计方法;介绍了基于Contiki,结合6LoWPAN无线协议及I²C、UART等串口通信协议的终端节点、接入节点软件设计方法;实验结果表明,系统对电压、电流、功率的测量误差均保持在2% 以内,能够实现组网,两个节点之间的无线通信距离可达80 m。     

Enhancing network lifespan in wireless sensor networks using deep learning based Graph Neural Network

Inadequate energy of sensors is one of the most significant challenges in the development of a reliable wireless sensor network (WSN) that can withstand the demands of growing WSN applications. Implementing a sleep-wake scheduling scheme while assigning data collection and sensing chores to a dominant group of awake sensors while all other nodes are in a sleep state seems to be a potential way for preserving the energy of these sensor nodes. When the starting energy of the nodes changes from one node to another, this issue becomes more difficult to solve. The notion of a dominant set-in graph has been used in a variety of situations. The search for the smallest dominant set in a big graph might be time-consuming. Specifically, we address two issues: first, identifying the smallest possible dominant set, and second, extending the network lifespan by saving the energy of the sensors. To overcome the first problem, we design and develop a deep learning-based Graph Neural Network (DL-GNN). The GNN training method and back-propagation approach were used to train a GNN consisting of three networks such as transition network, bias network, and output network, to determine the minimal dominant set in the created graph. As a second step, we proposed a hybrid fixed-variant search (HFVS) method that considers minimal dominant sets as input and improves overall network lifespan by swapping nodes of minimal dominating sets. We prepared simulated networks with various network configurations and modeled different WSNs as undirected graphs. To get better convergence, the different values of state vector dimensions of the input vectors are investigated. When the state vector dimension is 3 or 4, minimum dominant set is recognized with high accuracy. The paper also presents comparative analyses between the proposed HFVS algorithm and other existing algorithms for extending network lifespan and discusses the trade-offs that exist between them. Lifespan of wireless sensor network, which is based on the dominant set method, is greatly increased by the techniques we have proposed.     

数字、模拟无线混合网络视频节点设计

针对无线多媒体传感器网络广泛的应用前景和目前节点平台稀缺的情况,设计并研制了一种小型化的无线多媒体传感器网络节点。节点采用ADI公司的ADSP-BF561微处理器和Helicomm公司的基于Zigbee网络协议的无线收发模块IP-Link研制而成。在输入通道上可分别支持模拟图像传感器和数字图像传感器。输出通道具有多媒体传输通道和数据/命令传输通道,其中多媒体传输通道用于传输实时的模拟视频,数据/命令传输通道用于传输节点处理之后的有效数据以及接收来自上层网络的命令。     

A Resiliency-Connectivity metric in wireless sensor networks with key predistribution schemes and node compromise attacks

Applications for wireless sensor networks require widespread, highly reliable communications even in the face of adversarial influences. Maintaining connectivity and secure communications between entities are vital networking properties towards ensuring the successful and accurate completion of desired sensing tasks. We examine the required communication range for nodes in a wireless sensor network with respect to several parameters. Network properties such as key predistribution schemes and node compromise attacks are modelled with several network parameters and studied in terms of how they influence global network connectivity. These networks are physically vulnerable to malicious behavior by way of node compromise attacks that may affect global connectivity. We introduce a metric that determines the resilience of a network employing a key predistribution scheme with respect to node compromise attacks. In this work,we provide the first study of global network connectivity and its relationship to node compromise attacks. Existing work considers the relationship between the probability of node compromise and the probability of link compromise and the relationship of the probability of secure link establishment and overall network connectivity for the Erdős network model. Here, we present novel work which combines these two relationships to study the relationship between node compromise attacks and global network connectivity. Our analysis is performed with regard to large-scale networks; however, we provide simulation results for both large-scale and small-scale networks. First, we derive a single expression to determine the required communication radius for wireless sensor networks to include the effects of key predistribution schemes. From this, we derive an expression for determining required communication range after an adversary has compromised a fraction of the nodes in the network. The required communication range represents the resource usage of nodes in a network to cope with key distribution schemes and node compromise attacks. We introduce the Resiliency-Connectivity metric, which measures the resilience of a network in expending its resources to provide global connectivity in adverse situations.     

一种无线传感器网络健壮性可调的能量均衡拓扑控制算法

无线传感器网络中, 应用环境的干扰导致节点间距不能被准确度量. 所以利用以节点间距作为权重的闭包图(EG)模型构建的拓扑没有考虑环境的干扰, 忽略了这部分干扰带来的能耗, 缩短了网络生存时间. 针对无线传感器网络拓扑能量不均的特点和EG模型的缺陷, 首先引入节点度调节因子, 建立通信度量模型和节点实际生存时间模型; 其次量化网络节点度, 从而获取满足能量均衡和网络生命期最大化需求的节点度的取值规律; 然后利用该取值规律和函数极值充分条件解析推导出网络最大能量消耗值和最长生存时间, 并获得最优节点度; 最后基于以上模型提出一种健壮性可调的能量均衡拓扑控制算法. 理论证明该拓扑连通且为双向连通. 仿真结果说明网络能利用最优节点度达到较高的健壮性, 保证信息可靠传输, 且算法能有效平衡节点能耗, 提高网络健壮性, 延长网络生命周期.     

Genetic algorithm-support vector regression for high reliability SHM system based on FBG sensor network

Structural Health Monitoring (SHM) based on fiber Bragg grating (FBG) sensor network has attracted considerable attention in recent years. However, FBG sensor network is embedded or glued in the structure simply with series or parallel. In this case, if optic fiber sensors or fiber nodes fail, the fiber sensors cannot be sensed behind the failure point. Therefore, for improving the survivability of the FBG-based sensor system in the SHM, it is necessary to build high reliability FBG sensor network for the SHM engineering application. In this study, a model reconstruction soft computing recognition algorithm based on genetic algorithm-support vector regression (GA-SVR) is proposed to achieve the reliability of the FBG-based sensor system. Furthermore, an 8-point FBG sensor system is experimented in an aircraft wing box. The external loading damage position prediction is an important subject for SHM system; as an example, different failure modes are selected to demonstrate the SHM system's survivability of the FBG-based sensor network. Simultaneously, the results are compared with the non-reconstruct model based on GA-SVR in each failure mode. Results show that the proposed model reconstruction algorithm based on GA-SVR can still keep the predicting precision when partial sensors failure in the SHM system; thus a highly reliable sensor network for the SHM system is facilitated without introducing extra component and noise.     

基于物联网的设施温室监控系统中无线传感器节点设计

设计具有低成本、低功耗、易扩展的设施温室监控设备,深入研究无线网络构成,优化网络结构、降低组网难度、提高组网效率。采用 MSP430F149为核心的处理器;采用CC2530射频芯片实现无线传输;提供多种协议接口方便传感器的扩展,给出了土壤温湿度、空气温湿度、光照传感器的选型和指标参数;由本设计的无线传感器节点作为WSN中的全功能设备同时充当路由节点,搭建了MESH型的无线传感器网络结构。经测试,通过硬件设计及网络结构搭建,系统具有结构简单、组网快捷、数据传输可靠性高等优点,能较好的满足无线传感器节点在设施温室监控中的应用。     

基于质心迭代估计的无线传感器网络节点定位算法

针对无线传感器网络非测距定位方法的应用,提出了基于质心迭代估计的节点定位算法.该算法首先计算当前连通信标节点所围成的平面质心的坐标及其与未知节点间的接收信号强度,然后用计算所得质心节点替代距离未知节点最远的连通信标节点,缩小连通信标节点所围成的平面,并通过多次迭代的方法提高节点定位精度.仿真实验结果表明,该算法的各项指标均为良好,适用于无线传感器网络的节点定位.     

交换节点基于电磁波全向辐射特性的M维空时纠错码理论

电磁波在自由空间中的全向辐射特性在无线通信领域一直被认为是一个巨大缺点,但在网络环境下该特性可被用来提高无线通信系统的性能.考虑在一个无线网络中, M 个节点通过一个交换节点来相互交换各自信息.不同于传统传输方式,交换节点将对自己接收到的这 M 份独立信息进行联合编码,再利用电磁波全向辐射特性向所有节点同时发送相同码字.对于这种新型网络编码方式,本文给出了它对应的 M 维空时纠错码的数学定义,并证明了一些关于码本性能的基本定理,为构造性能较好的码本奠定了基础.这种同时引入空域和时域冗余的纠错码本有效地提高 关键词： 全向辐射 无线通信网络 交换节点 M 维空时纠错码     

基于强化学习和蚁群算法的WSN节点故障诊断

为了克服现有的WSN节点故障诊断方法所具有的难以实现在线诊断和诊断精度仍然不够高的缺点,设计了一种基于Sarsa算法和改进蚁群算法的WSN节点在线故障诊断方法。首先,建立了监测区域的网络模型和WSN节点故障诊断模型,然后,采用主成分分析法对节点故障样本数据进行降维,从而提高诊断效率,将样本数据作为层次,将故障诊断类作为各层节点建立层次树,采用改进的Sarsa算法求取各层节点的Q值,并将其用于初始化蚁群算法中路径的信息素,最后,提出了一种改进的蚁群算法求取从第一层出发的蚁群到各层节点之间的路径,将各层中信息素最大的节点作为最终的故障诊断类别。在Matlab环境下进行仿真实验,结果证明文中方法能有效实现WSN节点故障诊断,且与其它方法相比,具有故障诊断精确度高且能在线故障的优点,是一种有效的节点故障诊断方法。     

多尺度传感网络失效节点检测系统设计

对多尺度传感网络中的失效节点进行准确检测与定位,实现故障节点的高效检测,保障传感网络的可靠运行。提出一种基于多传感器量化融合跟踪滤波检测的失效节点检测算法,并进行检测系统优化设计。构建多尺度传感网络的节点分布实体对象模型,进行失效节点检测系统总体设计和技术指标分析。设计基于多传感器量化融合跟踪滤波检测的失效节点检测算法。进行系统的硬件设计,包括A/D模块设计、时钟电路设计、程序加载电路设计、传感器通信模块设计和系统电源模块设计。在ARM Cortex?-M0平台上进行检测系统软件开发。系统仿真结果表明,该系统进行多尺度传感网络失效节点检测的准确度较高,提高了传感器网络的寿命周期。     

Local adaptive sampling for wireless sensor network powered by energy harvesting

For a sensor network, energy limitation is always a key factor to affect the continuous work of a sensor node. A good idea is harvesting energy from the environment to support the node to work continuously. However, energy from environment is varied with time, weather and season. So in order to use the varied environment energy, it is necessary to find a way to achieve real-time monitoring and adaptive working. In this paper, an algorithm called “Adaptive Sampling” was proposed to adapt the sample mode to the present energy condition. Simulation proves that the algorithm can make the CO₂ sensor flexibly achieve adaptive sampling under different energy condition with the least MSE 2.7767. This algorithm can be widely used in wireless sensor network power by energy harvesting for local adaptive sampling.     

基于无线传感器网络及GPRS的水质监测系统设计

提出了一种基于ZigBee无线传感器网络和GPRS技术的多参数远程实时水质监测系统。无线传感器网络以CC2430通信模块为核心。传感器节点采集到的数据经路由节点汇总至协调器节点,通过GPRS模块及时远传至监控中心。设计信号调理电路,将传感器电极输出的微弱电信号进行放大、滤波。采用时间同步机制实现网络节点的同步唤醒,大幅提高网络的稳定性。对系统进行了多天连续测试。通信距离为100米时,网络的平均丢包率低于1%。pH值、溶氧度的平均相对偏差低于1%。测试结果表明,系统具有灵活、实时性好、准确性高、稳定可靠等优点,具有很强的实用价值。     

分立式与分布式光纤传感关键技术研究进展

光纤传感技术已广泛应用于航空航天、石油化工、电子电力、土木工程、生物医药等领域,其技术形式主要体现为分立式和分布式.分立式光纤传感技术利用光纤敏感器件作为传感器来感知被测参量的变化,光纤作为光信号的传输通道连接光纤传感器及后端的解调装置;分布式光纤传感系统基于光纤瑞利散射、拉曼散射或布里渊散射等光学效应,利用光纤本身作为传感器,可对沿途的光信号进行大范围、长距离传感.本文介绍了分立式与分布式光纤传感中主要关键技术的研究进展,并对未来的研究和发展方向进行了探讨.     

微小型无线光电传感网络的实验系统设计

基于nRF905低功耗、高灵敏度无线收发的一体芯片实现了一种微小型无线光电传感网络实验系统。讨论了实验系统的硬件节点、网络通信协议及软件的设计。实验结果表明,在19.2kbit/s速率下,系统中任意两节点可实现30m(室内)至150m(室外空旷地带)范围内的无线通信。该系统具有硬件设计简单、软件及其协议编程方便等优点,可微型化、低成本的应用于无线光电传感器网络系统。     

基于动态最小生成树路由协议的数据聚融算法

大规模的地理环境监测,以及用来传输与处理数据的物理基础设施无法和监测区域的规模保持同样的增速,使得不可靠链路下的数据采集与处理呈现出一种饱和流状态,无线传感器网络的能力看似难以稳定.另一方面,尽管理想网络模型的计算结果足够精确,然而,由于与实际应用偏差甚大,使得网络用户无法充分地分析和利用从工业现场所获得到的网络感知数据,并且没有针对网络规模和性能对数据聚融的影响进行分析.为此,本文提出以"过渡区"作为工业现场仿真的假设条件,并在此基础上提出了一种面向实际应用的数据聚融算法,即基于可信度的数据聚融算法(R算法).在具体设计R算法过程中,选用聚集和操作符SUM为例,通过对网络提供出的近似聚集和加以自动分析、综合,针对相对误差界限ε,计算出近似聚集和的可信度的下限η;并将近似聚集和、参数η一同提供给用户,在为用户提供网络概要信息的同时,还提供了参数η作为对信息可信度的判断,以便指导用户对数据聚集结果进行深度处理和提高网络的感知性能.仿真实验描述了过渡区内由于信噪比导致的链路不可靠所引起的η的变化规律;讨论了网络性能和规模对η的影响,随着网络运行周期的增加和网络规模的增大,η的值将逐渐靠近0;从而为WSNs从理论模型投入实际工业应用提供了理论依据和经验公式.     

A novel block encryption scheme based on chaos and an S-box for wireless sensor networks

The wireless sensor network (WSN) has been widely used in various fields, but it still remains in the preliminary discovery and research phase with a lack of various related mature technologies. Traditional encryption schemes are not suitable for wireless sensor networks due to intrinsic features of the nodes such as low energy, limited computation capability, and lack of storage resources. In this paper, we present a novel block encryption scheme based on the integer discretization of a chaotic map, the Feistel network structure, and an S-box. The novel scheme is fast, secure, has low resource consumption and is suitable for wireless sensor network node encryption schemes. The experimental tests are carried out with detailed analysis, showing that the novel block algorithm has a large key space, very good diffusion and disruptive performances, a strict avalanche effect, excellent statistical balance, and fast encryption speed. These features enable the encryption scheme to pass the SP800-22 test. Meanwhile, the analysis and the testing of speed, time, and storage space on the simulator platform show that this new encryption scheme is well able to hide data information in wireless sensor networks.     

基于ZigBee的温室环境无线测控系统

为了实现温室大棚环境的无线、远程实时监控,提出了一种以CC2430芯片为核心的ZigBee温室环境无线测控系统。描述了终端节点、路由节点和协调器节点的硬件组成和软件流程,并应用改进的Cluster-Tree路由算法组成ZigBee无线传感网络,实现数据的无线传输。利用串口通信技术实现无线传感网络与Yeelink物联网平台的通信,管理者可远程登陆Yeelink平台和手机APP查看温室环境信息以及控制节点状态。经实验测试,大棚内无线节点间的通信距离约80米,并且实现了光强、空气温湿度及土壤湿度的监控。测试表明系统构建简单,稳定可靠,为智能农业的设计提供了参考。