水下无线传感器网络

水下无线传感器网络是一种包括声、磁场、静电场等的物理网络,它在海洋数据采集、污染预测、远洋开采、海洋监测等方面取得了广泛的应用,将在未来的海军作战中发挥重要的优势。描述了水下无线传感器网络的研究现状,给出了几种典型的水下无线传感器网络的体系结构,并针对水下应用的特点,分析了水下无线传感器网络设计中面临的节点定位、传感器网络能量、目标定位等诸多难题,最后根据应用需求提出了水下无线传感器网络研究的重点。     

一种无线传感器网络被动定位方法设计与实现

从无线传感器网络节点自定位出发,分析比较了无线传感器自定位的几种常见定位算法,并给出现有算法存在的问题;在嵌入GPS模块的无线传感器网络汇聚节点上提出一种新的被动定位方法,并在软硬件上得到了实现．与传统的定位方法比较,它避免了无线传感器网络必须在每个节点嵌入GPS模块的同时,能在不增加体积、成本、通信功耗的情况下提供精确的定位位置．     

IEEE 802.15.4无线传感器网络中的能耗研究

低速率、低功耗的无线传感器网络日益发展,传统网络协议并不适用。IEEE 802.15.4通信协议是短距离无线通信的IEEE标准,包含了MAC层和物理层的规范,规定了在个域网(PAN)中设备之间的无线通信协议和接口。该标准也可用于无线传感器网络,尤其是活动时段(CAP)中采用的CSMA/CA算法对节省网络中的能耗有很大作用,本文分析了其中BO、SO以及数据传输间隔对无线传感器网络中的设备及协调器功耗的影响。     

基于混合信息增量矩阵的传感器网络故障自检测算法

针对无线传感器网络(WSNs,wireless sensor networks)故障检测过程中邻居协作导致额外的通信和计算负载的问题,提出一种用于无线传感器网络中的混合信息增量矩阵的故障自检测算法。该算法不需要邻居协作,通过对现有的基于局部信息增量矩阵的故障检测方法进行改进,以实现更好的故障检测能力。仿真结果表明,与局部信息增量矩阵算法相比,本算法具有更好的故障检测性能和鲁棒性,更适合于无线传感器网络的应用环境。     

基于位置信息的水声传感器网络路由协议

由于水下环境与地面环境不同,无线传感器网络中的协议不能直接应用于水下传感器网络中。针对水下环境的特点,提出了一种适用于水下传感器网络的路由协议。它是一种可扩展的、能量高效的路由协议。仿真结果显示:网络节点的移动速率不是很大时,该协议具有能量利用率高、数据传输成功率高和传输延时低等优点。     

无线传感器网络分簇算法研究综述

由于无线传感器网络存在能量约束问题,因此如何利用现有能量资源,延长网络的生命周期是无线传感器网络技术迫切需要解决的问题。分簇算法(ClusterAlgorith m)是无线传感器网络在分层路由中的重要算法。本文在简单介绍当前几个典型分簇算法的基础上,重点分析了簇首的形成过程,最后给出了结论和展望。     

基于微机电系统与径向基函数的水下航行器姿态检测

为实现水下航行器自主运动控制,准确掌握水下航行器的运动姿态至关重要。微机电系统惯性传感器因具有体积小、成本低和功耗低等特点,被广泛应用于姿态检测系统当中。由于海底的工作环境复杂,故水下航行器在实验过程中设定有一定的非合作性;因此设计采用径向基函数神经网络算法对采集数据进行训练与分类。实验结果表明,微机电系统惯性传感器结合径向基函数神经网络算法对水下航行器的基本行为识别的平均召回率可达94%。     

基于ZigBee的风光互补发电监测系统无线传感器的研究1009-914X

针对气象环境对风光互补发电系统影响重大及传统传感器测量物理量单一等原因,提出了一种基于ZigBee的无线传感器网络的设计方案。该传感器集风速、风向、光照强度、温度、湿度为一体,网络容量大、功耗低、易于扩充并且支持自组网。根据监测系统的技术要求,设计了无线传感器结构和硬件电路,井给出了软件流程。     

基于遗传算法的三维无线传感器网络定位新算法

针对三维无线传感器网络节点自身定位问题,提出了一种基于遗传算法的新定位算法。该算法通过分析未知节点与它的无线射程范围内的已知节点之间的通讯约束和距离测量,对未知节点建立数学模型;针对此数学模型利用遗传算法求解,把该解作为未知节点的估计位置。理论分析和试验结果表明,该算法具有很强的健壮性,未知节点的失效和新节点的加入不会影响算法的性能,并且算法定位精度高,条件简单,适合各种规模的无线传感器网络的节点定位。     

基于无线传感器网络的节点定位研究

无线传感器网络是对信息获取和处理的技术,通过通信技术使大量微小节点组成自组织网络,传感器网络包括数据的采集、传输、融合分析等。许多应用场所需要精确定位,使得无线传感器网络定位技术得到广泛应用和发展。本文通过对几种典型的定位算法研究,分析传感器网络节点定位算法的原理,得出的几种节点定位算法,并进行比较分析。     

事件驱动型传感器网络能量有效数据融合算法

从降低网络能耗和平衡网络负载的角度,提出了网络的一种能量有效的数据融合算法EFDAA,可应用于节点数量及覆盖度均较大的事件驱动型无线传感器网络.该算法采用正六边形网格划分方法,基于全网能量消耗模型计算所需的融合节点数,解决由于无规则选取融合节点数量而造成的网络能耗增加问题,并且能够优化融合节点的分布;为平衡网格内节点负载,以节点剩余能量、邻节点度和移动性作为选取融合节点的权重因子,基于距离信息自适应调整网格内节点间的单跳通信级别.仿真实验结果表明,融合节点数量的优选,降低了网络总的能量消耗;相比较于HEED算法,EFDAA有效延长了网络生命期.     

低时延能耗均衡的水声传感器网络簇间路由算法

针对水声传感器网络的簇间路由选择问题,提出了一种基于前向网关的低时延能耗均衡路由算法,该算法采用最优方向角原则和能耗均衡原则选择中继簇头和中继网关,以减小长延迟和高能耗对水声通信的影响。仿真结果表明该算法在网络平均能耗、端到端时延和网络生命周期等方面具有较好的性能。     

Efficient Routing Protocol with Localization Based Priority & Congestion Control for UWSN

The nodes in the sensor network have a wide range of uses, particularly on under-sea links that are skilled for detecting, handling as well as management. The underwater wireless sensor networks support collecting pollution data, mine survey, oceanographic information collection, aided navigation, strategic surveillance, and collection of ocean samples using detectors that are submerged in water. Localization, congestion routing, and prioritizing the traffic is the major issue in an underwater sensor network. Our scheme differentiates the different types of traffic and gives every type of traffic its requirements which is considered regarding network resource. Minimization of localization error using the proposed angle-based forwarding scheme is explained in this paper. We choose the shortest path to the destination using the fitness function which is calculated based on fault ratio, dispatching of packets, power, and distance among the nodes. This work contemplates congestion conscious forwarding using hard stage and soft stage schemes which reduce the congestion by monitoring the status of the energy and buffer of the nodes and controlling the traffic. The study with the use of the ns3 simulator demonstrated that a given algorithm accomplishes superior performance for loss of packet, delay of latency, and power utilization than the existing algorithms.     

Three-Dimensional Distance-Error-Correction-Based Hop Localization Algorithm for IoT Devices

The Internet of Things (IoT) is envisioned as a network of various wireless sensor nodes communicating with each other to offer state-of-the-art solutions to real-time problems. These networks of wireless sensors monitor the physical environment and report the collected data to the base station, allowing for smarter decisions. Localization in wireless sensor networks is to localize a sensor node in a two-dimensional plane. However, in some application areas, such as various surveillances, underwater monitoring systems, and various environmental monitoring applications, wireless sensors are deployed in a three-dimensional plane. Recently, localization-based applications have emerged as one of the most promising services related to IoT. In this paper, we propose a novel distributed range-free algorithm for node localization in wireless sensor networks. The proposed three-dimensional hop localization algorithm is based on the distance error correction factor. In this algorithm, the error decreases with the localization process. The distance correction factor is used at various stages of the localization process, which ultimately mitigates the error. We simulated the proposed algorithm using MATLAB and verified the accuracy of the algorithm. The simulation results are compared with some of the well-known existing algorithms in the literature. The results show that the proposed three-dimensional error-correction-based algorithm performs better than existing algorithms.     

A scheduling scheme for wireless sensor networks based on social insect colonies

Sensor networks employ a large amount of wireless sensor nodes to provide sensing power with high redundancy. Such redundancy makes sensor networks robust under changing environments. However, without proper scheduling, the surplus sensing power will cost tremendous energy consumption to the wireless sensor nodes. A scheduling scheme based on social insect colonies is proposed here. The proposed scheme is a kind of adaptive 'periodic on-off' scheduling scheme that uses only local information for making scheduling decisions. The scheme is evaluated in terms of averaged detection delay, target 3-coverage hit-rate and energy consumption per successful target detection. Simulation results show that, when comparing with other generic scheduling schemes, the proposed scheme can reduce energy consumption from a minimum of 7.49% to a maximum of 90.81% and improve the target hit-rate from a minimum of 15.7% to a maximum of 58.9%. Optimisation of the network lifetime and other performances is possible by adjusting some parameters.     

A power scheme of a wireless sensor network node for debris flow monitoring with move-triggered wake-up

In countries threatened by debris flow disasters, using wireless sensor networks (WSN) for debris flow monitoring and warning has become an important research topic. To detect the initial movement and subsequent moving status of monitored debris or rocks, a two-phase power scheme for a self-developed wireless inertial sensor has been proposed, implemented, and analyzed in this study. During the first phase, the power of the sensor node is disconnected to ensure that the sensor remains stationary. In the second phase, a hybrid scheme with periodic and move-triggered wake-up is actuated if the sensor is moved by debris or hit by rocks. A simple move detection algorithm is used to determine whether the node should enter sleep mode. The power models of the components of the proposed sensor node have also been discussed. Based on those models, the power consumption of the proposed power scheme has been determined and verified according to measurements. Analysis of the proposed hybrid power scheme can be easily generalized for WSN applications with sensor-triggered schemes. The relationship between the moving rate of monitored objects and the wake-up period in the moving detection algorithm was found to be nearly inversely proportional. The results can be employed to estimate and design sensor node power schemes for other similar applications, such as value asset monitoring and tracking.     

A Nonuniform Clustering Routing Algorithm Based on an Improved K-Means Algorithm

In a large-scale wireless sensor network (WSN), densely distributed sensor nodes process a large amount of data. The aggregation of data in a network can consume a great amount of energy. To balance and reduce the energy consumption of nodes in a WSN and extend the network life, this paper proposes a nonuniform clustering routing algorithm based on the improved K-means algorithm. The algorithm uses a clustering method to form and optimize clusters, and it selects appropriate cluster heads to balance network energy consumption and extend the life cycle of the WSN. To ensure that the cluster head (CH) selection in the network is fair and that the location of the selected CH is not concentrated within a certain range, we chose the appropriate CH competition radius. Simulation results show that, compared with LEACH, LEACH-C, and the DEEC clustering algorithm, this algorithm can effectively balance the energy consumption of the CH and extend the network life.     

An Integrated Sensing/Communication Architecture for Structural Health Monitoring

In this paper, a novel sensor network architecture for structural health monitoring is presented. The system is based on the adoption of purposely developed contactless sensors that make use of near-field coupling to both sense the structure displacements and deploy a local communication network. The key features of the adopted technology are the low-realization costs and the lower power consumption that nodes feature as compared to traditional wireless communication. In addition, the use of a fully decentralized positioning algorithm, running on each node, is demonstrated as a viable mean for the local mapping of extended structures, thus crediting the architecture for the evaluation of structural in-plane deformations.     

基于能量优化模型的无线传感器网络分簇算法

考虑到无线传感器分簇网络中簇的规模、簇头数量和节点剩余能量是能量有效型分簇路由算法关注的重要指标,提出了一种基于能量优化模型(EOM)的分布式分簇算法——EOMC,该算法通过建立网络能耗优化模型,以最优簇头数构建分簇通信规模,并结合功率控制将候选簇头限制在一定宽度的选举环带,使得簇头分布均衡,同时兼顾到节点剩余能量进行分簇,以达到均衡节点能耗,延长网络生存期的目的。与低能耗自适应分簇分层(LEACH)协议的对比仿真的结果表明,该算法能够达到预期指标,算法的开销相对较小。