被动式煤矿井下环境安全监测系统设计

介绍了一种基于ZigBee无线网络及传感器检测技术的新型被动式煤矿井下环境安全监测系统设计方案。该系统将带有传感器的移动检测终端设备置于矿工帽子上,通过无线传感网络,实现被动式的环境监测及无线信息传输,大大增加了监测的灵活性,并解决了监测死角的问题。     

无线传感器网络移动簇头节能传输协议

无线传感器网络具有资源的有限性和传感器采集数据的特点,许多在传统网络中运作良好的通信协议,在一些由固定节点和移动节点组成的无线传感器网络中不能很好地管理网络和处理传感器数据。该文提出一种移动簇头的节能通信协议,使用自组织传感器簇来处理和散发数据。通过与LEACH协议的对比,证明该协议具有更好的节能性和更长的网络寿命,更适用于无线传感器网络。     

基于无线传感网络的环境监控系统

为了实现对环境系统的动态远程监控,设计了一种基于Zigbee的无线传感网络监控系统.Zigbee无线数传终端模块通过内置的单片机系统,实现了不同传感器的接口协议,并对传感器数据进行了实时读取、编码与发送;系统中的协调器实现对数据包的接收、解码、验证并将正确的数据转发数据至服务器;无线传感网络中引入了ZStack协议,从而实现了对无线终端与协调器节点的动态增删;监控终端分为桌面与移动端,通过无线网络访问服务器中存储的数据,实现对环境系统的远程实时监控.     

Mires: a publish/subscribe middleware for sensor networks

A wireless sensor network (WSN) consists of a large number of small devices with computational power, wireless communication and sensing capability. These networks have been developed for a wide range of applications, such as habitat monitoring, object tracking, precision agriculture, building monitoring and military systems. Meanwhile, middleware systems have also been proposed in to facilitate both the development of these applications and provide common application services. The development of middleware for sensor networks, however, places new challenges on middleware developers due to the low availability of resources and processing capacity of the sensor nodes. In this context, this paper presents the design and implementation of a middleware for WSN named Mires. Mires incorporates characteristics of message-oriented middleware by allowing applications communicate in a publish/subscribe way. In order to illustrate the proposed middleware, we have also developed an environment-monitoring application and a data aggregation service.

Design and evaluation of lightweight middleware for personal wireless body area network

This paper presents a lightweight middleware to be used for wireless medical body area networks. The middleware is designed to reside in mobile devices, and acts as a gateway to receive sensor data as well as to control a set of sensor devices attached to the wearer. The main essence of the middleware is to simplify and accelerate the development of wireless healthcare applications by providing highly reusable codes. The architecture of the middleware including its main functions such as data acquisition, dynamic plug-and-play capabilities, on-the-fly sensor reconfiguration, and resource management (i.e., sensor sleep/wake-up, critical self-wake) will be discussed. A security feature as a means to protect critical sensor data from malicious/unauthorized parties has also been incorporated in our proposed middleware. The prototype system of the middleware has been built and is presented in this paper together with its performance measurements.     

A Survey of Fault Management in Wireless Sensor Networks

Wireless sensor networks are resource-constrained self-organizing systems that are often deployed in inaccessible and inhospitable environments in order to collect data about some outside world phenomenon. For most sensor network applications, point-to-point reliability is not the main objective; instead, reliable event-of-interest delivery to the server needs to be guaranteed (possibly with a certain probability). The nature of communication in sensor networks is unpredictable and failure-prone, even more so than in regular wireless ad hoc networks. Therefore, it is essential to provide fault tolerant techniques for distributed sensor applications. Many recent studies in this area take drastically different approaches to addressing the fault tolerance issue in routing, transport and/or application layers. In this paper, we summarize and compare existing fault tolerant techniques to support sensor applications. We also discuss several interesting open research directions. Lilia Paradis is currently a graduate student in the Department of Mathematical and Computer Sciences, Colorado School of Mines. She is also part of the Toilers Ad Hoc Networking research group. She is interested in distributed communication protocols for wireless sensor networks. Qi Han received the PhD degree in computer science from the University of California, Irvine in 2005. She is currently an assistant professor in the Department of Mathematical and Computer Sciences, Colorado School of Mines. Her research interests include distributed systems, middleware, mobile and pervasive computing, systems support for sensor applications, and dynamic data management. She is specifically interested in developing adaptive middleware techniques for next generation distributed systems. She is a member of the IEEE and the ACM.     

A mobile crowd sensing ecosystem enabled by CUPUS: Cloud-based publish/subscribe middleware for the Internet of Things

Mobile crowd sensing (MCS) is a novel class of mobile Internet of Things (IoT) applications for community sensing where sensors and mobile devices jointly collect and share data of interest to observe phenomena over a large geographic area. The inherent device mobility and high sensing frequency has the capacity to produce dense and rich spatiotemporal information about our environment, but also creates new challenges due to device dynamicity and energy constraints, as well as large volumes of generated raw sensor data which need to be processed and analyzed to extract useful information for end users. The paper presents an ecosystem for mobile crowd sensing which relies on the CloUd-based PUblish/Subscribe middleware (CUPUS) to acquire sensor data from mobile devices in a flexible and energy-efficient manner and to perform near real-time processing of Big Data streams. CUPUS has unique features compared to other MCS platforms: It enables management of mobile sensor resources within the cloud, supports filtering and aggregation of sensor data on mobile devices prior to its transmission into the cloud based on global data requirements, and can push information of interest from the cloud to user devices in near real-time. We present our experience with implementation and deployment of an MCS application for air quality monitoring built on top of the CUPUS middleware. Our experimental evaluation shows that CUPUS offers scalable processing performance, both on mobile devices and within the cloud, while its data propagation delay is mainly affected by transmission delay on wireless links.     

无线传感器网络中间件技术研究综述

无线传感器网络在受到广泛应用与关注的同时,由于网络复杂度及网络应用的增加,普遍存在缺乏统一开放接口的问题。针对无线传感器网络结构及特点,介绍无线传感器网络中间件技术概念,在全面分析中间件面临的问题与挑战的基础上,比较几种不同设计方法,并且通过典型实例在几个重要性能参数方面进行了对比。最后在中间件QoS机制模型方面提出了一种改进方法。     

无线传感器网络中间件研究进展

无线传感器网络作为一种新兴的技术,受到了学术界和工业界的广泛关注.然而随着传感器网络及其应用的发展,系统的复杂性也随之增加,与传统网络相比无限传感器网络又具有其独特的特征,使得无线传感器网络的程序开发变得更加困难.中间件提供了一个编程抽象,方便了应用程序的开发,缩减了应用程序和底层设备的间隙.针对无线传感器网络的特点,分析了无线传感器网络中间件设计面临的问题,对有关设计方法进行了分类评述,并对几种典型中间件进行了比较,最后从通信范式、QoS支持和安全等方面提出了一些改进思路.     

CrimeSPOT: A language and runtime for developing active wireless sensor network applications

Advances in wireless sensing and actuation technology allow embedding significant amounts of application logic inside wireless sensor networks. Such active WSN applications are more autonomous, but are significantly more complex to implement. Event-based middleware lends itself to implementing these applications. It offers developers fine-grained control over how an individual node interacts with the other nodes of the network. However, this control comes at the cost of event handlers which lack composability and violate software engineering principles such as separation of concerns. In this paper, we present CrimeSPOT as a domain-specific language for programming WSN applications on top of event-driven middleware. Its node-centric features enable programming a node’s interactions through declarative rules rather than event handlers. Its network-centric features support reusing code within and among WSN applications. Unique to CrimeSPOT is its support for associating application-specific semantics with events that carry sensor readings. These preclude transposing existing approaches that address the shortcomings of event-based middleware to the domain of wireless sensor networks. We provide a comprehensive overview of the language and the implementation of its accompanying runtime. The latter comprises several extensions to the Rete forward chaining algorithm. We evaluate the expressiveness of the language and the overhead of its runtime using small, but representative active WSN applications.     

无线传感器网络覆盖控制问题

无线传感器网络具有广泛的应用背景,目前已经发展成为一个重要的计算平台。但是,由于无线传感器网络自身的特点,使其也面临许多问题,如何有效地进行覆盖控制,在保证网络覆盖质量的前提下,减少能量消耗,延长网络寿命是其中最重要的问题之一。本文主要讨论无线传感器网络的覆盖控制的问题。     

污水重金属监测与移动预警系统

针对企业污水排放重金属监测分布范围广、环境恶劣的特点,设计了基于无线传感网络、J 2 M E技术的污水重金属监测与移动预警系统。在污染水区部署传感器节点,通过ZigBee无线传感网络传输采集数据,经GPRS网络到达智能手机;同时数据经由无线基站和Internet传送至监测中心,手机客户端既可从GPRS网络获取超限报警数据,也可从监测中心获取重金属污染动态分析数据,实现了实时监测和移动预警。     

Secure lightweight password authenticated key exchange for heterogeneous wireless sensor networks

Several three-party password authenticated key exchange (3-PAKE) protocols have recently been proposed for heterogeneous wireless sensor networks (HWSN). These are efficient and designed to address security concerns in ad-hoc sensor network applications for a global Internet of Things framework, where a user may request access to sensitive information collected by resource-constrained sensors in clusters managed by gateway nodes. In this paper we first analyze three recently proposed 3-PAKE protocols and discuss their vulnerabilities. Then, based on Radio Frequency Identification technologies we propose a novel 3-PAKE protocol for HWSN applications, with two extensions for additional security features, that is provably secure, efficient and flexible.     

无线传感器网络便携式用户接口的设计与实现

重点考察无线传感器网络的人机交互问题,设计并实现了一种基于手持移动设备的无线传感器网络用户接口,以方便人们对传感器网络节点的灵活访问与控制。该用户接口搭建于Pocket PC平台,通过蓝牙与汇聚节点进行双向通信,从而实现对整个无线传感器网络系统的监控。用户可以通过便携式接口现场采集与处理传感器网络节点的数据,同时也可以发送指令对汇聚节点和普通节点进行各种设置。演示实验结果验证了该接口系统的可行性与有效性。     

基于GPRS的数据采集系统的研究

本文研究开发了一套基于GPRS技术的无线数据采集系统,远端数据采集模块将传感器的输出信号进行模数转换,通过串行接口驱动无线modem经GPRS网络将数据发送到Internet上的远程监控中心,并完成数据的存储和显示。本文从硬件和软件两方面描述了系统的设计及实现方法。这种新型的无线数据采集系统非常适合于在边远地区或可移动系统中实现无线的数据采集和监控。     

Reliable and energy-efficient data collection in sparse sensor networks with mobile elements

Sparse wireless sensor networks (WSNs) are emerging as an effective solution for a wide range of applications, especially for environmental monitoring. In many scenarios, a moderate number of sparsely deployed nodes can be sufficient to get the required information about the sensed phenomenon. To this end, special mobile elements, i.e. mobile data collectors (MDCs), can be used to get data sampled by sensor nodes. In this paper we present an analytical evaluation of the data collection performance in sparse WSNs with MDCs. Our main contribution is the definition of a flexible model which can derive the total energy consumption for each message correctly transferred by sensors to the MDC. The obtained energy expenditure for data transfer also accounts for the overhead due to the MDC detection when sensor nodes operate with a low duty cycle. The results show that a low duty cycle is convenient and allows a significant amount of correctly received messages, especially when the MDC moves with a low speed. When the MDC moves fast, depending on its mobility pattern, a low duty cycle may not always be the most energy efficient option.     

无线传感器网络的网络管理

无线传感器网络是由许多能量和处理能力有限的传感器节点组成.传感器网络主要用来监测环境、建筑和结构和动物习性的监测.网络管理是任何网络,包括传感器网络的重要功能.而由于无线传感器网络的特点,对其管理要比传统网络都要困难,而其中网络管理的最主要方面是网络拓扑结构的管理.开发节能并且能够维护网络连接的拓扑的算法是非常必要的.本文介绍了网络管理的基本知识,以及如何应用在无线传感器网络中.文中主要描述了网络的拓扑结构,并且对现在主要的网络拓扑结构算法进行描述和比较.     

中间件在无线传感器网络节点设计中的应用

在无线传感器网络(W SNs)节点设计和应用软件开发中引入中间件技术,提出了一种基于中间件的W SNs节点软件、硬件体系结构。一定程度上简化了异构的传感器网络的应用开发,并使得不同应用实例之间实现跨网络的协同工作。     

面向无线传感器网络节点定位的移动锚节点路径规划

节点定位是无线传感器网络技术研究的一个基本问题,大多数无线传感器网络的应用和中间件技术都需要节点的位置信息.目前比较实用的定位方法是利用一些移动锚节点(如安装有GPS)根据有效的规划路径移动,通过发送包含其自身坐标的信息来定位其他节点,该方法不过多地增加无线传感器网络成本,还可以获得较高的定位精度.在该方法中,移动锚节点的路径规划问题是需要解决的基本问题.主要研究移动锚节点的路径规划问题,把图论引入到无线传感器网络节点定位系统.把无线传感器网络看成一个连通的节点无向图,路径规划问题转化为图的生成树及遍历问题,提出了宽度优先和回溯式贪婪算法.仿真实验和真实系统实验结果表明,该方法能够很好地适应无线传感器网络节点随机分布的节点定位,可以取得较高的定位精度.     

基于线性回归的无线传感器网络分布式数据采集优化策略

事件监测是无线传感器网络中最重要的应用之一,部署在监测区域内的传感器节点通过对感知数据信息的采集、处理和传输等基本操作完成具体的监测任务,在各种操作中,节点之间的数据传输是最消耗能量的.为了减少节点之间的通信数据量,达到降低网络能耗和延长网络生命周期的目的,该文提出了一种能量高效的基于线性回归的无线传感器网络分布式数据采集优化策略,通过应用线性回归分析方法构建感知数据模型,保持感知数据的特征,使节点仅传输回归模型的参数信息,代替传输实际监测的感知数据信息.仿真实验结果表明,文中提出的数据采集优化策略能通过较小的通信量有效地实现事件监测区域感知数据的预测和估计,降低网络的总能量消耗,延长网络的生命周期.