面向无人机协助的WSNs的数据收集策略

射频能量捕获(Radio Frequency Energy Harvesting,RF-EH)技术为解决无线传感网络(Wireless Sensor Networks,WSNs)能量有限问题提供了新的方法。为此,针对无人机(Unmanned Aerial Vehicle,UAV)协助的WSNs网络,提出时隙优化的数据收集(Time Slot Optimizing data-gathering,TODG)策略。在TODG策略中,节点先接收来自电力包(Power Beacon,PBs)的无线电能传输(Wireless Power Transfer,WPT)进行充电;再构建最小化中断概率的时隙分配的目标函数,借助于CVX工具求解,获取最优的时隙分配。仿真结果表明,通过优化时隙,TODG策略能够降低中断概率,提升吞吐量。     

ZigBee2006协议栈的无线传感执行网络构建

无线传感执行网络是智能空间的重要组成部分。本文应用TI/Chipcon公司免费提供的ZigBee2006协议栈,以CC2430无线单片机为控制器,构建家庭无线传感执行网络,为执行器操作传送温度、湿度、光照等环境数据。实验结果表明,该系统能够达到检测环境的任务要求,且成本低,性能可靠稳定,在智能空间、智能家居等领域具有良好的应用前景。     

家庭自动化无线传感器／执行器网络路由协议的设计

家庭自动化无线传感器／执行器网络有着自己的特点,如节点间供电能力、计算能力、移动性具有显著 差异,本文在分析这些差异的基础上提出一种基于地理位置的按需路由协议．该路由协议利用静态节点位置限定路 由请求包,并且利用静态邻居节点作为辅助节点完成动态节点的路由发现,避免了对移动节点定位技术的依赖性． 利用NS2 比较了该路由协议和AODV 路由协议的性能．仿真结果显示本文的路由协议能降低路由开销从而提高稳 定性．     

MPC-based Co-design of Control and Routing for Wireless Sensor and Actuator Networks

A wireless sensor and actuator network (WSAN) is a class of networked control systems. In WSANs, sensors and actuators are located in a distributed way, and communicate to controllers through a wireless communication network such as a multi-hop network. In this paper, we propose a model predictive control (MPC) method for co-design of control and routing of WSANs. MPC is an optimal control strategy based on numerical optimization. The control input is calculated by solving the finite-time optimal control problem at each discrete time. In the proposed method, a WSAN is modeled by a switched linear system. In the finite-time optimal control problem, a control input and a mode corresponding to a communication path are optimized simultaneously. The proposed method is demonstrated by a numerical example.     

一种基于执行器控制域的分布式数据收集协议

针对无线传感器/执行器网络(Wireless Sensor and Actuator Networks,WSANs)中执行器控制域的数据收集问题,提出了一种基于执行器控制域的分布式数据收集协议(DG-ACD协议).DG-ACD协议从能量有效性和数据融合的角度,提出了执行器控制域内传感器节点的中继代价函数,并以执行器节点为中心,采用发射功率分级递进的路由建立方式,为控制域内的每个传感器节点寻找其到达执行器节点的中继节点,从而实现对执行器控制域内传感器节点的聚集和数据收集.实验仿真结果表明,网络中节点(包括执行器节点)部署完成后,DG-ACD协议能有效地将网络中的传感器节点聚集到相应的执行器节点,并在数据收集的能量有效性、实时性和稳定性上均有良好表现.     

基于ZigBee无线传感网络的车辆定位系统

介绍一种基于ZigBee无线传感器网络的车辆定位系统设计,通过在监控区放置的参考节点,实现对网络中的移动节点（车辆）的跟踪定位,并将车辆位置信息传输给服务器,实现计算机终端的远程访问和控制。     

基于无线传感器网络的移动目标导航方法

为降低导航方法对移动目标配置的要求,并为移动目标提供在线式导航,提出一种基于无线传感器网络的移动目标导航方法.该方法使用无线传感器网络信息进行导航环境描述,建立影响移动目标前进的多种环境因素的势场模型,结合最短路径与最安全路径,提出一种基于代价的导航决策方法,根据导航代价最小的原则,进行移动目标的导航.分析表明,该导航算法能够满足在线导航的要求,实现移动目标的高精度导航.     

无线传感器网络

无线传感器网络被誉为21世纪四大高新技术之一。文章对无线传感器网络与传统网络的区别、技术特点和体系结构进行了探讨,重点针对无线传感器网络的现有各层协议进行了分析比较,最后,针对无线传感器网络发展所需的关键技术,提出来来我们重点研究的几个亟待解决的技术问题。     

无线传感器网络

集成了传感器、微机电系统和网络三大技术而形成的传感器网络是一种全新的信息获取和处理技术.在简要介绍传感器网络体系结构的基础上,分析和展望了一些有价值的应用领域.结合已有研究,总结并详细阐述了包括低功耗路由技术和介质访问控制方法等在内的热点研究问题.最后,针对应用需求,提出了几点研究设想.     

基于无线传感器网络车速监测算法

为了构建基于无线传感器网络的大规模、低成本、低功耗的交通信息采集系统,本文提出了一种车辆速度检测 算法。将一跳通信范围内的路由节点和多个传感器节点看成是一个子网,路由节点实现子网内的时间同步和车速计算。 通过实验验证了该车速检测算法的精度可达到 95% 左右。     

基于IEEE 802.11e的无线传感器/执行器网络丢包判器设计

在目前的无线传感器/执行器网络(Wireless Sensor and Actuator Networks,WSANs)中,无线传感器及其所传输信息的业务类型趋于多样化;同时,在实时性要求较高的工业系统中,无线网络环境下的丢包将给整个系统带来严重的危害。为提高WSANs的可靠性,提出了一种基于IEEE 802.11e的WSANs丢包判决器的优化设计方法。该方法采用提供服务质量(Quality of Service,QoS)的IEEE 802.11e作为WSANs的数据通信协议,推导出该协议下的WSANs丢包概率矩阵,并将基于该丢包概率矩阵的龙伯格状态观测器的输出作为丢包的判决阈值,把网络中的丢包现象作为一种故障信号,从而设计出WSANs的丢包判决器。该丢包判决器不仅能有效判断网络中是否出现了丢包,而且还能通过判决器输出的故障信号波形判断丢包原因,即传感器节点故障,或是由于信道环境不稳定造成的随机丢包。最后,通过MATLAB/OMNET++的混合仿真验证了该设计的有效性。     

无线传感器网络中传感器节点的布置

在无线传感器网络中，传感器节点收集本地数据，通常通过其它节点将数据转发给基站，因而离基站越近的节点，消耗的能量越多．如果采用通常的方法，即均匀布置传感器节点，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．本文通过研究无线传感器网络中的能量消耗，得到了一个布置传感器节点的密度函数，按此函数布置传感器节点可以有效地延长系统的生命期．理论分析和模拟结果表明，本文的布置方案将系统生命期提高到均匀布置方案的3R/2t倍，这里t为传感器节点的通信距离，R为传感器节点的分布区域半径．     

无线传感器网络的管理

无线传感器网络是一个资源受限、应用相关的任务性网络,与现有网络特性显著不同,传统的网络管理不再适用于无线传感器网络。本文在简要说明无线传感器网络基本特性和面临挑战的基础上,给出了一个通用的无线传感器网络管理框架,并详细说明了各部分的内容和研究进展,最后探讨了无线传感器网络管理进一步的发展方向。     

无线传感反应网络综述

从传感器网络衍生出来的传感反应网络是一种全新的信息获取和处理技术.本文先简要介绍了传感反应网络体系结构和特点,再结合已有研究,在设计和开发传感反应网络协议方面,讨论传感节点-反应节点和反应节点-反应节点协调中存在的问题,并探讨反应节点给通信协议带来的问题与挑战.     

Scalable security in Wireless Sensor and Actuator Networks (WSANs): Integration re-keying with routing

Our research aims to address the challenging security issues in Wireless Sensor and Actuator Networks (WSANs), a special type of Wireless Sensor Networks (WSNs). Since WSANs have specific network constraints and data transmission requirements compared to general ad hoc networks and other wireless/wired networks, we propose to seamlessly integrate WASN security with a ripple-zone (RZ)-based routing architecture that is scalable and energy-efficient. In this research, we will also develop a two-level re-keying/re-routing schemes that cannot only adapt to a dynamic network topology but also securely update keys for each data transmission session. Moreover, to provide the security for the in-networking processing such as data aggregation in WSANs, we define a multiple-key management scheme in conjunction with our proposed Ripple-Zone routing architecture. Extensive simulations and hardware experiments have been conducted to verify the energy-efficiency and security performance of our security scheme for WSANs.     

无线传感器与执行器网络基于邻居信息的割点检测算法

无线传感器与执行器网络（WSANs）中通信关键节点（割点）对网络的连通性和通信性能有着重要影响,迅速准确的割点检测以及在此基础上的拓扑修复是提高鲁棒性、保证网络通信性能的重要前提。提出了一种分布式割点检测算法（DCVN）,该算法中每个节点通过至多与其两跳邻居节点进行信息交换来建立局部的网络拓扑信息,再根据预设的判断准则来实现对WSANs中的割点的快速检测。实验模拟显示该算法能够很好的满足割点的检测需求,在检测准确率方面要优于现有的几种有代表性的割点检测算法。     

A Framework for Using Unmanned Aerial Vehicles for Data Collection in Linear Wireless Sensor Networks

The wireless sensor network (WSN) technology have been evolving very quickly in recent years. Sensors are constantly increasing in sensing, processing, storage, and communication capabilities. In many WSNs that are used in environmental, commercial and military applications, the sensors are lined linearly due to the linear nature of the structure or area that is being monitored making a special class of these networks; We defined these in a previous paper as Linear Sensor Networks (LSNs), and provided a classification of the different types of LSNs. A pure multihop approach to route the data all the way along the linear network (e.g. oil, gas and water pipeline monitoring, border monitoring, road-side monitoring, etc.), which can extend for hundreds or even thousands of kilometers can be very costly from an energy dissipation point of view. In order to significantly reduce the energy consumption used in data transmission and extend the network lifetime, we present a framework for monitoring linear infrastructures using LSNs where data collection and transmission is done using Unmanned Aerial Vehicles (UAVs). The system defines four types of nodes, which include: sensor nodes (SNs), relay nodes (RNs), UAVs, and sinks. The SNs use a classic WSN multihop routing approach to transmit their data to the nearest RN, which acts as a cluster head for its surrounding SNs. Then, a UAV moves back and forth along the linear network and transport the data that is collected by the RNs to the sinks located at both ends of the LSN. We name this network architecture a UAV-based LSNs (ULSNs). This approach leads to considerable savings in node energy consumption, due to a significant reduction of the transmission ranges of the SN and RN nodes and the use of a one-hop transmission to communicate the data from the RNs to the UAV. Furthermore, the strategy provides for reduced interference between the RNs that can be caused by hidden terminal and collision problems, that would be expected if a pure multihop approach is used at the RN level. In addition, three different UAV movement approaches are presented, simulated, and analyzed in order to measure system performance under various network conditions.