无线传感器网络的概述

针对目前无线传感器网络(WSN)在军事、工业、国防等领域的广泛应用,本文就其发展、应用情况一一作了详细阐述,并指出了在无线传感器网络研究过程中面临的难题。     

无线传感器网络

无线传感器网络具有广泛的应用前景．将引起人们越来越多的关注。本文介绍了无线传感器网络的基本组成．网络的特点．并分析了当前无线传感器网络的研究应用现状及一些研究成果。     

用无线传感器组成无线传感器网络

物联网的愿景之一是能够测量以前从未测量过的变量。无论应用是监视基础设施老化(例如桥梁、隧道或电力传输线的老化),还是实时提供停车及交通信息,都需要无线传感器网络(WSN)提供与有线网络类似的性能,而且适合实际部署。传感器网络要能够扩展至包含大量无线节点,而且在很多情况下,需要跨越很长的距离。     

无线磁场传感器网络

无线磁场传感器网络是一种多学科多技术结合的产物,其可以对进入网络的目标进行实时检测。本文采用巨磁阻抗传感器为网络节点组建无线磁场传感器网络,对移动目标进行了测量,并对结果进行了分析。     

无线传感器网络安全性研究

无线传感器网络广泛应用于军事、交通、环境等领域,通信安全问题日渐重要,分析了无线传感器网络的特点,根据无线传感器网络的安全现状,进行了通信安全性研究,提出该领域今后数据安全保护的发展方向。     

无线传感器网络

无线传感器网络(WSN)被认为是21世纪最重要的技术之一,它将会对人类未来的生活方式产生深远影响。本文介绍了传感器网络的概念和特点,探讨了传感器网络与现有的无线通信网络相结合的业务。     

无线传感器网络研究

在信息化时代,信息的接收、处理及分析对用户而言至关重要。特别是信息的接收环节,若收集到的信息不全、有误或者接收不到,后续工作都将无法开展。无线传感器是专门用于接收信息的一类工具,通过网络操作,使人们收集到自己想要的信息。无线传感器网络节点的特点是智能化、功率损耗小、能接收大量信息,传感器的工作运行离不开网络。文章对无线传感器目前的发展现状、技术特点以及应用前景等方面进行了阐述。     

无线认知传感器网络研究

无线认知传感器网络(WCSN)可以定义为无线认知传感器节点的分布式网络,它感知事件信号,机会地使用频谱空洞,并采用多跳方式,完成信息的动态协同通信,最终满足各种应用需求。文章分析了无线认知传感器网络(WCSN)的基本概念和优势,给出了无线认知传感器网络节点硬件结构,研究了Ad Hoc式、分簇式、异构分级式和移动式四种无线认知传感器网络拓扑结构,列举了无线认知传感器网络的应用领域。     

无线传感器网络结构特点及关键问题研究概述

无线传感器网络（Wireless Sensor Network）集中了传感器、计算机和通信技术,通过众多节点自组形成网络,用于实时采集和监测各种信息。因具有广泛的应用前景,成为信息领域新的研究热点。本文基于此介绍了无线传感器网络的概念和特点,讨论了无线传感器网络的关键技术及应用现状,为深入开展研究提供基础指导。     

无线传感器网络结构特点及关键问题研究概述

无线传感器网络(Wireless Sensor Network)集中了传感器、计算机和通信技术,通过众多节点自组形成网络,用于实时采集和监测各种信息。因具有广泛的应用前景,成为信息领域新的研究热点。本文基于此介绍了无线传感器网络的概念和特点,讨论了无线传感器网络的关键技术及应用现状,为深入开展研究提供基础指导。     

无线传感器网络系统综述

介绍了无线传感器网络的概念、几种主要的无线传感器网络协议，尤其是MAC层协议的研究情况，给出了一些比较经典的无线传感器网络MAC协议的思想。     

无线传感器网络LEACH协议分析

在无线传感器网络中,基于簇的层次结构能够优化网络带宽的应用,提高共享信道的利用率,减少路由维护的代价以及提高应用的可扩展性,在路由、安全、网络管理等方面具有广泛的应用。基于此,分析研究了典型的基于簇的LEACH协议,并提出了LEACH协议几个可能的研究方向。     

Directional Controlled Fusion in Wireless Sensor Networks

Though data redundancy can be eliminated at aggregation point to reduce the amount of sensory data transmission, it introduces new challenges due to multiple flows competing for the limited bandwidth in the vicinity of the aggregation point. On the other hand, waiting for multiple flows to arrive at a centralized node for aggregation not only uses precious memory to store these flows but also increases the delays of sensory data delivery. While traditional aggregation schemes can be characterized as “multipath converging,” this paper proposes the notation of “multipath expanding” to solve the above problems by jointly considering data fusion and load balancing. We propose a novel directional-controlled fusion (DCF) scheme, consisting of two key algorithms termed as directional control and multipath fusion. By adjusting a key parameter named multipath fusion factor in DCF, the trade-offs between multipath-converging and multipath-expanding can be easily achieved, in order to satisfy specific QoS requirements from various applications. We present simulations that verify the effectiveness of the proposed scheme.

Lightweight Deployment-Aware Scheduling for Wireless Sensor Networks

Wireless sensor networks consist of a large number of tiny sensors that have only limited energy supply. One of the major challenges in constructing such networks is to maintain long network lifetime as well as sufficient sensing areas. To achieve this goal, a broadly-used method is to turn off redundant sensors. In this paper, the problem of estimating redundant sensing areas among neighbouring wireless sensors is analysed. We present simple methods to estimate the degree of redundancy without the knowledge of location or directional information. We also provide tight upper and lower bounds on the probability of complete redundancy and on the average partial redundancy. With random sensor deployment, our analysis shows that partial redundancy is more realistic for real applications, as complete redundancy is expensive, requiring up to 11 neighbouring sensors to provide a 90 percent chance of complete redundancy. Based on the analysis, we propose a scalable Lightweight Deployment-Aware Scheduling (LDAS) algorithm, which turns off redundant sensors without using accurate location information. Simulation study demonstrates that the LDAS algorithm can reduce network energy consumption and provide desired QoS requirement effectively. This research was partially supported by Natural Sciences and Engineering Research Council of Canada. Kui Wu received his Ph.D. in Computing Science from the University of Alberta, Canada, in 2002. He joined the Department of Computer Science at the University of Victoria, Canada in the same year and is currently an Assistant Professor there. His research interests include mobile and wireless networks, network performance evaluation, and network security. Yong Gao received his Master's degree and Ph.D. degree in computer science from University of Alberta, Canada, in 2000 and 2005 respectively. He is currently with the Irving K. Barber School of Arts and Sciences, UBC Okanagan, Canada. His research interests include search algorithms and AI, communication networks, and computational biology. Yang Xiao worked at Micro Linear as an MAC (Medium Access Control) architect involving the IEEE 802.11 standard enhancement work before he joined Department of Computer Science at The University of Memphis in 2002. Dr. Xiao is an IEEE Senior member. He was a voting member of IEEE 802.11 Working Group from 2001 to 2004. He currently serves as Editor-in-Chief for International Journal of Security and Networks (IJSN) and for International Journal of Sensor Networks (IJSNet). He serves as an associate editor or on editorial boards for the following refereed journals: (Wiley) International Journal of Communication Systems, (Wiley) Wireless Communications and Mobile Computing (WCMC), EURASIP Journal on Wireless Communications and Networking, and International Journal of Wireless and Mobile Computing. He serves as five lead/sole guest editor for five journal special issues. He serves as a referee/reviewer for many funding agencies, as well as a panelist for NSF. His research interests are Security/ Reliable Communications, Medium Access Control, Mobility/Location/Paging Managements, Cache Access and Replacement Policies, Quality of Service, Energy Efficiency, and Routing in wireless networks and mobile computing.     

压缩感知在传感器网络中的应用研究

无线传感器网络(Wireless Sensor Networks,WSN)被应用在诸多领域,如在工业自动化、环境检测、网络控制、生物及能量管理等方面。主要讨论了压缩感知在传感器网络中的应用,研究了压缩感知在传感器网络中应用所需的数学基础,以及重要参数的描述。     

无线传感器网络休眠MAC协议分析

无线传感器网络中每个传感器节点一般采用电池供电,能量有限,需要有效的可休眠的MAC协议来保持能量的高效利用,因此休眠MAC协议成为研究的重要方向之一。目前已经有很多种为无线传感器网络设计的MAC协议,其中一个重要的分支就是基于局部同步周期休眠／监听排程的S-MAC协议及其各种改进协议。论文首先介绍了无线传感器网络中与MAC协议设计相关的一些特性。其次对S-MAC协议的基本原理以及各种改进协议的原理进行了说明,并分析了它们各自的优缺点。     

无线传感网络中的目标跟踪技术

无线传感器网络由于其自组织性、鲁棒性及节点数量巨大的特点,非常适合于目标跟踪。无线传感器网络目标跟踪大体分为单目标跟踪与面目标跟踪。单目标跟踪主要采用双元检测协作跟踪、信息驱动协作跟踪、传送树跟踪算法等方法。面目标跟踪采用对偶空间转换算法等方法。在无线传感器网络目标跟踪中,跟踪精度、跟踪能量消耗和跟踪可靠性是需要考虑的主要问题。     

无线传感器网络安全性研究综述

本文介绍了无线传感器网络发展现状及其应用情况,分析了无线传感网存在的安全问题及面临的安全威胁,并综合考虑无线传感网存在的自身限制,给出了保障无线传感器网络安全的综合解决方案,为无线传感器网络大范围推广应用提供了技术支撑。     

基于无线传感网络的瓦斯监控报警系统

该文设计了以CC2430为核心的无线传感网络的瓦斯监控报警系统。该系统通过放置大量的无线传感器网络采集节点,实时进行节点处瓦斯浓度的采集和换算,并通过模糊PID控制实现节点附近的瓦斯浓度的智能化控制。     

无线传感器网络的自组织机制研究

无线传感器网络的自组织包含不依赖于固定通信基础设施的有规则联系和运动,本文在特定应用中研究这一过程.在定性分析无线传感器网络的自组织特性之后,提出自组织度和自组织单位能耗的自组织评价方法,在典型应用中以此量化分析无线传感器网络的自组织演化机制.仿真表明,在特定应用中的无线传感器网络表现出孕育、发育、成熟、衰退和死亡的自组织过程,自组织能耗依赖于特定的部署方式和无线模型.