传感器网络数据库并行计算设计与应用

本文深入了解了国内外无线传感器网络领域目前的发展现状和发展动态,并对现有的无线传感器网络操作系统进行了大量的钻研,为研究无线传感器网络数据库打下了夯实的理论基础。论文从现有的无线传感器网络数据库分析入手,并着重设计和实现了基于TaraxOS无线传感器网络操作系统的数据库TaraxDB。然后基于对无线传感器网络数据库的分析,设计和实现了无线传感器网络数据库TaraxDB,设计实现了客户端查询的接收、解析和表示,数据库客户端与传感器网络之间发送查询和接收结果,数据库客户端与用户之间接收查询和提交结果。     

基于SOC的血沉仪时钟及温度检测系统

本文设计了一种应用于血沉自动检测,基于SOC的C8051F单片机,结合SMBus总线技术和一线总线技术的实时时钟、温度检测系统。系统采用I2C总线的智能日历时钟芯片PCF8563提供时钟信息,应用一线总线数字温度传感器DS18B20检测温度,利用液晶屏实时显示。该系统具有结构简单、功耗低、可靠性好、可移植性强等特点。     

一种无线传感器网络入侵检测模型

针对无线传感器网络安全问题的研究现状构建了无线传感器网络安全体系结构,并为此提供了一个满足无线传感器网络需求的全分布式入侵检测模型,较好的解决了安全性和有限的网络资源之间的矛盾,实现了安全性和节能性的统一。     

Zigbee无线传感器网络安全研究及改进

无线传感器网络综合了传感器技术、嵌入式计算技术、分布式信息处理技术和无线通信技术,本文针对ZigBee技术在组网方式、安全结构等安全方面进行了全面的分析,提出多冗余路径安全机制,从而更适合无线传感器网络的应用。     

oDect: an RFID‐based object detection API to support applications development on mobile devices

The RFID technology is becoming ever more popular in the development of ubiquitous computing applications. A full exploitation of the RFID potential requires the study and implementation of human–computer interaction (HCI) modalities to be able to support wide usability by the target audience. This implies the need for programming methodologies specifically dedicated to support the easy and efficient prototyping of applications to have feedback from early tests with users. On the basis of our field‐working experience, we have designed oDect, a high‐level language and platform‐independent application programming interface (API), ad hoc designed to meet the needs of typical applications for mobile devices (smart phones and PDAs). oDect aims at allowing application developers to create their prototypes focusing on the needs of the final users, without having to care about the low‐level software that interacts with the RFID hardware. Further, in an end‐user developing (EUD) approach, oDect provides specific support for the application end‐user herself to cope with typical problems of RFID applications in detecting objects. We describe in detail the features of the API and discuss the findings of a test with four programmers, where we analyse and evaluate the use of the API in four sample applications. We also present results of an end‐user test, which investigated strengths and weaknesses of the territorial agenda (TA) concept. The TA is an RFID‐based citizen guide that aids—through time‐ and location‐based reminders—users in their daily activities in a city. The TA directly exploits EUD features of oDect, in particular concerning the possibility of linking detected objects with custom actions. Copyright © 2008 John Wiley & Sons, Ltd.     

An adaptive in-network aggregation operator for query processing in wireless sensor networks

A wireless sensor network (WSN) is composed of tens or hundreds of spatially distributed autonomous nodes, called sensors. Sensors are devices used to collect data from the environment related to the detection or measurement of physical phenomena. In fact, a WSN consists of groups of sensors where each group is responsible for providing information about one or more physical phenomena (e.g., group for collecting temperature data). Sensors are limited in power, computational capacity, and memory. Therefore, a query engine and query operators for processing queries in WSNs should be able to handle resource limitations such as memory and battery life. Adaptability has been explored as an alternative approach when dealing with these conditions. Adaptive query operators (algorithms) can adjust their behavior in response to specific events that take place during data processing. In this paper, we propose an adaptive in-network aggregation operator for query processing in sensor nodes of a WSN, called ADAGA (ADaptive AGgregation Algorithm for sensor networks). The ADAGA adapts its behavior according to memory and energy usage by dynamically adjusting data-collection and data-sending time intervals. ADAGA can correctly aggregate data in WSNs with packet replication. Moreover, ADAGA is able to predict non-performed detection values by analyzing collected values. Thus, ADAGA is able to produce results as close as possible to real results (obtained when no resource constraint is faced). The results obtained through experiments prove the efficiency of ADAGA.     

无线传感器网络中一种新的分布式定位方案研究

Node localization in wireless sensor networks (WSN) is treated as a functional dual of target tracking from a novel perspective in the paper. Different from the traditional tracking problem in WSN, using the static location-ware node to estimate the moving target, the mobile node is used to help unknown nodes to accurately discover their positions. A new node localization scheme virtual beacons-energy ratios localization (VB-ERL) and its refinements for the WSN are presented. In the scheme, the mobile node moves in the surveillant field based on the Gauss-Markov mobility model and periodically broadcasts the information packets. Each static unknown node receives the virtual beacons and energy in its sensing range, and estimates its location by finding the intersection of a set of hyper-spheres. Simulation results show the proposed scheme is efficient.     

一类不确定Lur'e奇异系统的可靠鲁棒H_∞跟踪控制(英文)

The problem of reliable robust H_∞tracking control for a class of uncertain Lur'e singular systems is studied.A practical and general failure model of actuator and sensor is considered by using convex polytopic uncertainties to describe control surface impairment.Some sufficient conditions are presented for the case of actuator,sensor and control surface failures in terms of linear matrix inequalities (LMIs).The resultant control systems are reliable in that they guarantee closed-loop system robust stability with H_∞performance and the output tracking the reference signal without steady-state error when all control components are operational as well as when some control components experience failures.Finally,a numerical example is given to show the effectiveness of the proposed methods.     

基于LS-SVM的非线性多功能传感器信号重构方法研究

提出了基于最小二乘支持向量机(Least squares support vector machine, LS-SVM)的非线性多功能传感器信号重构方法. 不同于通常采用的经验风险最小化重构方法, 支持向量机(Support vector machine, SVM)是基于结构风险最小化准则的新型机器学习方法, 适用于小样本标定数据情况, 可有效抑制过拟合问题并改善泛化性能. 在SVM基础上, LS-SVM将不等式约束转化为等式约束, 极大地简化了二次规划问题的求解. 研究中通过L-折交叉验证实现调整参数优化, 在两种非线性情况下对多功能传感器的输入信号进行了重构, 实验结果显示重构精度分别达到0.154\%和1.146\%, 表明提出的LS-SVM重构方法具有高可靠性和稳定性, 验证了方法的有效性.     

面向无线传感器网络的复杂适应系统分析方法

从复杂适应系统理论角度出发对无线传感器网路的自组织、自适应、主体性等特征进行了分析,认为随着传感技术、通信技术和计算机技术的飞速发展以及 MEMS 技术的日益成熟与完善,无线传感器网络将引领未来信息技术迅猛发展。而 WSN 是一个复杂的系统,依据管理科学研究方法思想,即必须把复杂系统当作复杂系统来处理,复杂适应系统理论在方法论上为研究无线传感器网问题提供了可能的思路。