基于马尔可夫链的无线传感器网络分布式调度方法

能量效率是无线传感器网络(Wireless sensor network, WSN)研究中的核心问题之一. 当节点采用电池供电时, 有限的能量限制了网络的生存周期, 从而对无线传感器网络的大规模应用提出了挑战. 本文基于马尔可夫链, 提出了一种实用的、协作分布式的调度方法, 并从理论上证明了该方法的收敛性. 该方法不仅可对节点的休眠/唤醒进行调度, 还可以对节点数据发送进行调度以减少数据冲突的发生. 仿真实验结果表明, 该方法能够有效地减少节点能量的消耗, 且对其他网络性能的影响较小.     

基于ARM和ZigBee的WSN节点设计与实现

设计一种基于ARM和ZigBee技术的WSN硬件节点,并根据该硬件平台的特性,有裁减地移植实现了Microchip ZigBee协议栈。对节点的性能进行组网测试,结果表明所设计的节点达到了无线传感器网络的设计要求,并具有良好的可扩展性和移植性,可以为工程应用和实验教学提供基础平台。     

FISDR:一种新的故障注入无线传感器网络性能评估系统

在无线传感器网络WSN中,可靠性和容错性是评价WSN稳定性的重要指标。在WSN的实际应用中常会发生很多故障(Fault)和干扰,采用故障注入FI技术可以向WSN人为地注入这些故障和干扰,通过观察注入故障后网络的反应来评价网络的可靠性和容错性,从而对网络机制进行改进来提高网络的可靠性和稳定性。本文提出的FISDR是一种采用故障注入的WSN性能评估系统,基于软件故障注入方法,采用一对一的方式通过特殊接口与WSN节点连接,向WSN节点注入故障命令。该系统一是可以有效地向WSN注入各种实际应用时可能遇到的故障和干扰并观察网络运行的状况;二是可以接收包括WSN节点和其它各种设备通过特殊接口发来的数据,并将其存储;三是配有上位机软件对网络拓扑结构进行监控、对传输成功率进行统计并对存储的大量信息进行分析,从而对WSN网络及其可靠性做出评价。本系统在一栋五层办公楼分别用数十个WSN节点和FISDR节点做实验,实验内容包括使用FISDR向WSN注入大规模的故障并统计网络的反应状况,验证FISDR故障注入的效果,从而对FISDR的性能进行测试和分析。实验结果表明,FISDR可以有效地向WSN注入各种故障以评价其可靠性,在测试WSN及其可靠性评价方面有很高的应用价值。     

无线传感器网络节点分簇与非分簇性能比较

为研究分簇的无线传感器网络（WSN）能否在很大程度上节约传感器节点电池能源,延长网络生存周期,从分簇的网络组织本身、分簇WSN和非分簇WSN能量消耗的对比、不同分簇方式对网络能耗的影响进行研究,得出当满足一定条件时,分簇WSN比非分簇WSN性能更优的结论,并进一步得出WSN的最佳分簇规格应在5跳以内。     

基于WSN节点能量补充的太阳能充电系统

由于传统的电池供电方式满足不了WSN节点能量消耗的要求,设计了一种基于WSN节点能量补充的光伏发电系统.根据四区域光电传感器采集的光照强度信息,STM32最小系统驱动控制水平方向和垂直方向的舵机,使得太阳能电池板适时获得最大光照强度.实验结果表明,采用锂电池和电容混合储能方案时,在测试条件下,可为锂电池提供的0.1A左...     

失真容忍无线传感网络中的最优传感器配置研究

研究了一维和二维无线传感器网络(WSN)在空间信号源相关条件下的最优传感器配置方法。WSN通过分布的传感器节点得到与位置相关的测量数据, 然后恢复出具有空间相关性的信号。WSN重建信号的基本准则是使重建信号和原信号在单位区域能量恒定条件下的均方误差(MSE)最小。研究了在具有有限节点的小网络和具有有限节点密度的大网络中传感器节点密度和空间数据相关性对网络性能的影响, 定量分析了各种不同网络参数间的相互作用及其对网络性能的影响。其结果为实用WSN的设计提供了基础。     

环境监测无线传感器网络节点能源技术

节点能量提供与管理技术是无线传感器网络的关键技术之一。针对环境监测应用对无线传感器网络的特殊要求．提出了节点能源设计的基本原则，在此基础上，对可用的供电电池相关性能进行了比对。研究了适于环境监测的能源补充技术．设计了一套实用的太阳能能源补充系统，与单纯电池供电系统的供电能力进行了比对实验。最后讨论了降低节点能耗的相关技术。     

微型温差电池的无线传感器节点自供电系统

伴随全球性的能源危机,利用环境中的动态能量为无线传感器网络供电已经成为一种趋势.本文设计了一个基于BQ25504芯片的无线传感器节点自供电系统,该系统可以在330mV电压下启动,在工作时以最大功率跟踪方式采集低至80 mV的温差能量,并能够动态地将能量通过能量缓冲器电路供给无线传感器节点使用.该系统有效地解决了基于微型温差电池的无线传感器节点自供电的问题.     

基于CAN总线的无线传感器网络测试系统设计与实现

为了对无线传感器网络在实际环境下进行综合性能测试,设计了一种无线传感器网络测试系统;各测试模块挂载到CAN总线上,有利于数据的快速传输,增加了可测试节点的数量并提高了数据传输的实时性;提出一种动态优先级方案,解决了静态低优先级节点竞争不到CAN总线造成的数据拥塞;针对无线传感器网络节点数量大、烧录效率低的特点,利用MSP430的Bootstrap Loader特性,实现了对WSN节点的并行程序烧录,提高了烧录效率;此外,还支持对WSN节点的电源控制、能耗测试、程序调试及状态查询。实验数据表明,该测试系统满足无线传感器网络的测试要求。     

基于无线传感器网络的通讯组件和测试平台的设计

该文介绍了无线传感器网络(WSN)和TinyOS操作系统的特点。针对当前无线传感器网络在测试时面临的问题,设计出了一个基于TinyOS操作系统的测试平台。该测试平台通过独立于无线网络的辅助网络,对无线传感器网络中的传感器节点进行实时数据采集。测试平台中内建一个通用组件,用于管理网络中的测试数据流,并为测试者提供友好的数据接口,数据流的帧格式可根据不同应用进行配置,实验表明该测试平台能很好的辅助开发人员对无线传感器网络进行测试。     

Probabilistic fault detector for Wireless Sensor Network

This paper proposed a novel centralized hardware fault detection approach for a structured Wireless Sensor Network (WSN) based on Naïve Bayes framework. For most WSNs, power supply is the main constraint of the network because most applications are in severe situation and the sensors are equipped with battery only. In other words, the battery’s life is the network’s life. To maximize the network’s life, the proposed method, Centralized Naïve Bayes Detector (CNBD) analyzes the end-to-end transmission time collected at the sink. Thus all the computation will not be performed in individual sensor node that poses no additional power burden to the battery of each sensor node. We have conducted thorough performance evaluation. The obtained results showed better performance can be obtained under a network size of 100-node WSN simulations at various network traffic conditions and different number of faulty nodes.     

基于镍氢电池的隔爆型电气设备备用电源系统设计

针对GB 3836.2—2010中规定矿井隔爆型电气设备备用电源系统中的备用电池必须采用镍镉电池、锂电池、镍氢电池的要求,设计了一种基于镍氢电池的隔爆型电气设备备用电源系统;分析了镍氢电池的工作原理及系统的设计要求,详细介绍了系统中充电管理单元、保护单元的设计,并给出了系统测试结果。实际应用表明,该系统运行可靠,保护措施安全有效,完全满足GB 3836.2—2010的要求。     

基于多级多路径控制的无线传感器电源管理方法

无线传感器通常长期在野外工作,其电源能耗一直是受业界关注的技术问题.针对采用低压锂电池供电的无线传感器,提出采用多级多路径控制的电源管理方法,实现超低压降、电源超低功耗和大电流输出.采用本电源管理方法的无线传感器不仅能充分利用电池电能量,还能兼容多种供电电源(如锂电池、锂亚电池、干电池、铅酸电池等)的应用场景.     

基于Nios~ II/s的通用无线传感网络节点设计

无线传感器网络是一项基于无线网络通信、在普适环境下可实现区域性信息采集的网络技术。基于Nios II系列32位RISC嵌入式处理器Nios II,采用创新的三维IP地址分配法,结合传统无线网络技术和MAC协议,设计了一个通用性较强的无线传感器网络模型。同时利用太阳能和节点自身携带微型电池协同供电,太阳能充电的双模式供电法,在无线传感网络的能源问题上作出了改进。     

基于交叉层的无线传感器网络协议

无线传感器网络节点采用电池供电,能量有限。很多情况下电池无法更换,网络中的节点会因能量耗尽而失效。节点的主要能耗是网络通信开销,因此,设计低能耗的网络协议成为无线传感器网络研究的核心问题之一。描述了无线传感器网络的主要能量消耗来源,介绍了Cross-layer设计思想和协议结构,对在Cross-layer框架下开发相关网络协议的能量有效性进行了必要的分析。     

Power management in SMAC-based energy-harvesting wireless sensor networks using queuing analysis

One of the most important constraints in traditional wireless sensor networks is the limited amount of energy available at each sensor node. The energy consumption is mainly determined by the choice of media access mechanism. SMAC is a typical access mechanism that has drawn much attention in recent years. In WSNs, sensors are usually equipped with capacity-limited battery sources that can sustain longer or shorter period, depending on the energy usage pattern and the activeness level of sensor nodes. To extend the lifetime of the sensor networks, ambient energy resources have been recently exploited in WSNs. Even though solar radiation is known as the superior candidate, its density varies over time depending on many factors such as solar intensity and cloud states, which makes it difficult to predict and utilize the energy efficiently. As a result, how to design an efficient MAC in a solar energy harvesting based WSN becomes a challenging problem. In this paper, we first incorporate a solar energy-harvesting model into SMAC and conduct its performance analysis from a theoretical aspect. Our research works provide a fundamental guideline to design efficient MAC for energy harvesting based WSNs. Our major contribution includes three folders: firstly, we model solar energy harvesting in a photovoltaic cell and then derive the throughput of SMAC in the energy-harvesting based WSNs. Second, we develop a new model based on queuing theory to calculate the average number of energy packets in battery in terms of both duty cycle and throughput. Finally, we form an optimization problem to find a suitable range for the duty cycle to satisfy both quality of service (QoS) and network lifetime requirements.     

采用自供电无线传感网络的电线安全监测系统

电线故障会引起火灾,对电线温度、电流进行在线监测能预防事故发生。设计了采用自供电无线传感网络的电线安全监测系统,系统由传感节点、中继节点、路由节点、服务器和客户端组成。采用自供电技术解决无线传感网络监测系统中传感节点不能持续供能的问题,对传感节点工作状态进行控制以降低传感节点能耗,传感节点具有体积小、能耗低、不用更换电池等特点。分析自供电条件下,无线传感网络的网络结构,引入中继节点,延伸通信距离。将系统用于电线安全监测,该系统通信可靠、工作时间长、数据实时、人机操作方便,为电线安全的监测提供了技术支持。     

A Novel Fault Tolerance Energy-Aware Clustering Method via Social Spider Optimization (SSO) and Fuzzy Logic and Mobile Sink in Wireless Sensor Networks (WSNs)

In recent years, the application of WSNs has been remarkably increased and notable developments and advances have been achieved in this regard. In particular, thanks to smart, cheaper and smaller nodes, different types of information can be detected and gathered in different environments and under different conditions. As the popularity of WSNs has increased, the problems and issues related to networks are examined and investigated. As a case in point, routing issue is one of the main challenges in this regard which has a direct impact on the performance of sensor networks. In WSN routing, sensor nodes send and receive great amounts of information. As a result, such a system may use lots of energy which may reduce network lifetime. Given the limited power of a battery, certain method and approaches are needed for optimizing power consumption. One such approach is to cluster sensor nodes; however, improper clustering increases the load imposed on the clusters around the sink. Hence, for proper clustering, smart algorithms need to be used. Accordingly, in this paper, a novel algorithm, namely social spider optimization (SSO) algorithm is proposed for clustering sensor network. It is based on the simulation of the social cooperative behavior of spiders. In the proposed algorithm, nodes imitate a group of spiders who interact with each other according to biological rules of colony. Furthermore, fuzzy logic based on the two criteria of battery level and distance to sink is used for determining the fitness of nodes. On the other hand in WSNs with a fixed sink, since the nodes near the sink share multi-hop routes and data and integrated towards the sink, these nodes are more likely to deplete their battery energy than other nodes of the network. Also In this paper, mobile sink was suggested for dealing with this problem. For investigating and demonstrating the performance of the proposed method, we compared it with DCRRP and NODIC protocol. The results of simulation indicated better performance of the proposed method in terms of power consumption, throughput rate, end-to-end delay and signal to noise ratio and has higher failure tolerance especially in terms of sensor nodes’ failure.     

Curracurrong: a stream programming environment for wireless sensor networks

The technological advances in wireless sensor network (WSN) enable the development of complex applications including health monitoring, environmental sampling, and disaster area monitoring. WSN applications deploy battery‐powered sensors at remote locations for long periods. The development of energy‐efficient and complex WSN applications therefore requires in‐depth embedded systems programming skills that are normally not found in domain experts. So that this challenge can be overcome, programming environments for WSN need to offer a high degree of productivity, flexibility, and efficiency at the same time. In this work, we present Curracurrong, a development environment for WSNs that is based on expressing queries with stream programming. A query is represented as a stream graph consisting of stream operators and communication channels. Curracurrong provides an extensible stream operator library that adapts to a wide range of applications. It uses a novel placement algorithm that optimizes the energy consumption on sensor nodes. Through a case study, we demonstrate the productivity and flexibility of our system. We conduct experiments that evaluate the energy efficiency of our optimized operator placement algorithm. Copyright © 2012 John Wiley & Sons, Ltd.