无线传感器网络节点的电压监测

电池供电的无线传感器网络节点在电量不足时,节点上的有源器件不能稳定工作。基于网络节点中的CC2430/31芯片,在Zig Bee协议栈中添加定时功能,使以电池供电的节点能够周期性地采样电池电压并进行判断,当电压低于预先设定的报警低限时,利用LED灯的闪烁进行报警。同时该节点进入非正常工作状态,断开与网络的联系,以保证其他节点交互信息的可靠性。     

基于嵌入式技术的水声传感网和#br# VHF通信网络的互联网关设计

针对水上船舶用户对水下网络监测存在长延时和高费用问题,结合水声传感网特点和水上船舶常用VHF通信设备,采用嵌入式技术,提出一种面向水上船舶用户的水声传感网和水上VHF通信网的无线网关设计方案,对网关的软硬件系统进行设计。仿真结果表明,嵌入式网关实现了水声传感网和VHF通信网的互联互通,具有较高的理论与实际应用价值。     

基于CAN总线和GPRS的车载传感器网络平台的实现

给出了基于CAN总线和通用分组无线业务(GPRS)的车载传感器网络平台的解决方案和软件、硬件的实现。结合汽车轮速传感器,说明了传感器节点的信号处理和数据计算。通过设计CAN通信模块,实现车载传感器数据的网络化传输;采用包含GPRS模块的传感器网关节点,实现车载传感器与远程计算机间的无线数据通信。该车载传感器网络平台具有很强的通用性。     

无线传感器网络中移动传感器的再定位技术

回顾了在传感器网络中引入移动传感器的过程。介绍了移动传感器再定位技术可解决传感器网络中的事件深入感知、传感器失效和非精确投放等问题。详细阐述了现有的移动传感器移动至感兴趣区域深入感知、扩大网络覆盖面积和修补网络覆盖洞三类技术。剖析了现有技术中存在的问题。总结分析了主要解决方法和模型,并对未来研究方向进行了展望。     

基于WSNs的大型楼宇空气质量监测系统设计

针对大型楼宇环境信息监控特点,基于低功耗Zig Bee无线通信技术设计一种空气质量监控系统。运用无线传感器智能信息处理技术,全面提升系统的自动化与监测水平。采用星型拓扑结构组网,通过在监测区域部署网络节点,将监测数据汇集到嵌入式监测系统,实现统一的数据管理和Zig Bee网络的路由监测功能。由无线传感器网络实时采集CO,甲醛,SO2和苯等环境数据,并进行处理,将其发送到接收端,在接收端对数据进行存储和显示,实时监测楼宇环境空气质量。实验证明:该系统性能稳定,数据传输可靠性高,使用灵活,可广泛应用于各领域的环境参数自动监测。     

Receiver-initiated medium access control protocols for wireless sensor networks

One of the fundamental building blocks of a Wireless Sensor Network (WSN) is the Medium Access Control (MAC) protocol, that part of the system governing when and how two independent neighboring nodes activate their respective transceivers to directly interact. Historically, data exchange has always been initiated by the node willing to relay data, i.e. the sender. However, the Receiver-Initiated paradigm introduced by Lin et al. in 2004 with RICER and made popular by Sun et al. in 2008 with RI-MAC, has spawned a whole new stream of research, yielding tens of new MAC protocols. Within such paradigm, the receiver is the one in charge of starting a direct communication with an eligible sender. This allows for new useful properties to be satisfied, novel schemes to be introduced and new challenges to be tackled. In this paper, we present a survey comprising of all the MAC protocols released since the year 2004 that fall under the receiver-initiated category. In particular, keeping in mind the key challenges that receiver-initiated MAC protocols are meant to deal with, we analyze and discuss the different protocols according to common features and design goals. The aim of this paper is to provide a comprehensive and self-contained introduction to the fundamentals of the receiver-initiated paradigm, providing newcomers with a quick-start guide on the state of the art of this field and a palette of options, essential for implementing applications or designing new protocols.     

Deployment of robust wireless sensor networks using gene regulatory networks: An isomorphism-based approach

The communication between nodes in a Wireless Sensor Network (WSN) may fail due to different factors, such as hardware malfunctions, energy depletion, temporal variations of the wireless channel and interference. To maximize efficiency, the sensor network deployment must be robust and resilient to such failures. One effective solution to this problem is to exploit a bio-inspired approach based on Gene Regulatory Networks (GRNs). Owing to million years of evolution, GRNs display intrinsic properties of adaptation and robustness, thus making them suitable for dynamic network environments. In this article, we exploit the genetic structure of real organisms to deploy bio-inspired WSNs that are isomorphic to certain GRN sub-networks. Exhaustive structural analysis, simulations and experimental results on a WSN testbed demonstrate that bio-inspired WSNs are resilient to node and link failures and offer better performance than existing solutions for robust WSNs.     

Uncertainty-aware soft sensor using Bayesian recurrent neural networks

Data-driven soft sensors have been widely used to measure key variables for industrial processes. Soft sensors using deep learning models have attracted considerable attention and shown superior predictive performance. However, if a soft sensor encounters an unexpected situation in inferring data or if noisy input data is used, the estimated value derived by a standard soft sensor using deep learning may at best be untrustworthy. This problem can be mitigated by expressing a degree of uncertainty about the trustworthiness of the estimated value produced by the soft sensor. To address this issue of uncertainty, we propose using an uncertainty-aware soft sensor that uses Bayesian recurrent neural networks (RNNs). The proposed soft sensor uses a RNN model as a backbone and is then trained using Bayesian techniques. The experimental results demonstrated that such an uncertainty-aware soft sensor increases the reliability of predictive uncertainty. In comparisons with a standard soft sensor, it shows a capability to use uncertainties for interval prediction without compromising predictive performance.     

Data aggregation in wireless sensor networks using ant colony algorithm

Data aggregation is important in energy constraint wireless sensor networks which exploits correlated sensing data and aggregates at the intermediate nodes to reduce the number of messages exchanged network. This paper considers the problem of constructing data aggregation tree in a wireless sensor network for a group of source nodes to send sensory data to a single sink node. The ant colony system provides a natural and intrinsic way of exploring search space in determining data aggregation. Moreover, we propose an ant colony algorithm for data aggregation in wireless sensor networks. Every ant will explore all possible paths from the source node to the sink node. The data aggregation tree is constructed by the accumulated pheromone. Simulations have shown that our algorithm can reduce significant energy costs.     

一种用于无线传感器网络的模块化设计方法

针对无线传感器网络应用多样化的特点,建立了基于ZigBee技术的无线传感器网络节点与网关节点的模块化软、硬件设计方案。该硬件方案具有模块化与集成度高的特点,软件方案基于嵌入式操作系统进行多种功能的模块化设计,具有良好扩展性以及可维护性。实现了一种基于单芯片平台的传感器节点与ARM平台的网关节点,讨论了当前与未来适用的各种嵌入式设计关键技术。     

无线传感器网络中的被动式红外传感器模型研究

针对公共安全的需要，利用无线传感器网络系统进行区域监控已然成为趋势。通过对系统的物理结构分析提出了一种被动式红外传感器模型。该模型对配备被动式红外传感器的无线传感网络的系统设计具有指导意义。传感器节点的测试以及实时系统的试验验证了模型的可靠性。     

Coverage boundary of unknown environment using mobile sensor networks

In this article, we consider the problem of optimal coverage of unknown environmental boundary using sensor networks. Since the boundary is unknown to all sensors, it is necessary for the sensors to find it first. We give a new distributed estimate policy by tracking a virtual agent using the sensor networks. Then we consider the problem of optimal coverage of the estimate boundary instead of the actual one. Moreover, an algorithm is given to deploy the sensors to the optimal configuration corresponding to the coverage problem considered in this article.     

Distributed linear estimation over sensor networks

We consider a network of sensors in which each node may collect noisy linear measurements of some unknown parameter. In this context, we study a distributed consensus diffusion scheme that relies only on bidirectional communication among neighbour nodes (nodes that can communicate and exchange data), and allows every node to compute an estimate of the unknown parameter that asymptotically converges to the true parameter. At each time iteration, a measurement update and a spatial diffusion phase are performed across the network, and a local least-squares estimate is computed at each node. The proposed scheme allows one to consider networks with dynamically changing communication topology, and it is robust to unreliable communication links and failures in measuring nodes. We show that under suitable hypotheses all the local estimates converge to the true parameter value.     

基于Web服务的传感器网络和Internet集成

随着无线传感器网络的迅速发展和广泛应用,如何把传感器网络和应用系统通过Internet连接在一起就成了一个必须面对的挑战,SOA的软件体系结构是解决这一问题的有效方法.将无线传感器网络的访问封装成Web服务,通过服务注册和服务发现,应用程序可以通过HTTP发现,绑定和调用这些服务.通过定义一些核心服务和辅助服务,传感器网络可以很容易地集成到应用系统中.通过讨论这些核心服务和辅助服务及其实现,典型应用场景的介绍,证明了这种方法的有效性.     

Information extraction from sensor networks using the Watershed transform algorithm

Wireless sensor networks are an effective tool to provide fine resolution monitoring of the physical environment. Sensors generate continuous streams of data, which leads to several computational challenges. As sensor nodes become increasingly active devices, with more processing and communication resources, various methods of distributed data processing and sharing become feasible. The challenge is to extract information from the gathered sensory data with a specified level of accuracy in a timely and power-efficient approach. This paper presents a new solution to distributed information extraction that makes use of the morphological Watershed algorithm. The Watershed algorithm dynamically groups sensor nodes into homogeneous network segments with respect to their topological relationships and their sensing-states. This setting allows network programmers to manipulate groups of spatially distributed data streams instead of individual nodes. This is achieved by using network segments as programming abstractions on which various query processes can be executed. Aiming at this purpose, we present a reformulation of the global Watershed algorithm. The modified Watershed algorithm is fully asynchronous, where sensor nodes can autonomously process their local data in parallel and in collaboration with neighbouring nodes. Experimental evaluation shows that the presented solution is able to considerably reduce query resolution cost without scarifying the quality of the returned results. When compared to similar purpose schemes, such as “Logical Neighborhood”, the proposed approach reduces the total query resolution overhead by up to 57.5%, reduces the number of nodes involved in query resolution by up to 59%, and reduces the setup convergence time by up to 65.1%.     

无线传感器网络中节点选择机制综述*

节点选择是保证无线传感器网络满足系统QoS需求的最重要问题之一,一种性能较好的节点选择机制可以在保证数据精度的前提下延长网络生命周期。针对WSN节点选择问题进行了描述及分类,着重研究了几类当前具有代表性的节点选择机制,并分析比较了各自的性能及缺点;最后对节点选择的进一步研究方向进行了展望。     

传感器网络中的安全性和保密性

为了缓解传感器网络在安全性和保密性方面的困境,对传感器节点、窃听、监测数据、拒绝服务攻击等易被攻击环节的安全性问题进行了探讨,并从硬件和软件两个方面,提出了改进协议、数据加密、访问控制、多路发送、分布式询问等多种抵御攻击的办法。     

无线传感器网络的模糊功率控制技术

无线传感器网络节点通过撒播造成节点分布不均,分簇后导致分簇疏密不均,影响了网络性能,需要对簇头进行功率控制使网络结构更加优化.但这是一个难以确定其准确数学模型的过程,因此提出了一种采用模糊技术调整簇头功率以改变拓扑结构的方案.最后进行了仿真,实验结果证明通过分簇大小控制以后,网络的生存时间和通信量都有增加.     

使用部署知识的异构传感器网络有效成簇算法

成簇算法是传感器网络中减少能量消耗的一种关键技术,它能够增强网络的扩展性和延长网络的生存时间。异构传感网络在能量节约方面的性能更好。提出一种适应异构无线传感器网络的分布式能量有效的成簇方案DEECUDK。该方案首先利用部署知识部署节点,使能量在整个监测区域分布比较均匀,然后以节点的剩余能量与传感半径之内的节点的剩余覆盖能量为主参数,其相邻节点个数为辅参数来选举簇头节点。较高初始能量、剩余能量和相邻节点数多的节点比其他节点拥有更多的机会成为簇头节点,并引入活动节点判别式,不需要增加任何开销来减少簇内冗余数据量,从而使网络能量均匀消耗,延长网络的生存时间。通过模拟实验结果,与现有的异构传感网络成簇算法相比,新的算法在网络生存时间与网络吞吐量方面有着更好的性能。     

利用本地信噪比实现无线传感器网络的能量有效性

提出了利用本地信噪比来选择部分传感器节点发送数据从而达到实现无线传感器网络能量有效性的方法。在无线传感器网络中节点分布的密度很大,节点采集的数据具有很强的相关性,这样让每一个节点都发送它们采集的数据是非必要的。采用的方法是选择那些本地信噪比较高（即对恢复目标原始状态贡献大）的那些节点传送它们采集的数据。仿真结果表明该方法可以节约30%50%的能量消耗,并且对目标节点状态的估计几乎没有造成不良的影响。