无线传感器节点实时能耗监测

无线传感器网络设计的关键技术环节之一是低功耗。首先要准确地检测到运行时各模块的能量消耗,然后才能够进行控制优化。然而,应用上的需求千差万别,导致硬件平台的多样性。本文选取无线传感器网络领域节点能量消耗检测作为研究方向,提出了一种便携的无线传感器节点能耗数据采集装置,能够实时采集节点的电压、电流信息。针对当前研究集中于仿真模拟,这种装置可用于实际环境的能量消耗检测,检测精度高。在MicaZ节点上的实验结果表明,该系统能以较高精度监测节点的能量效率。实际测量发现,传感器网络中传感器能耗也属能量消耗的一部分,且消耗量不可忽视,为今后的研究改进提供了新的参考。     

An efficient heuristic for selecting active nodes in wireless sensor networks

Energy saving is a paramount concern in wireless sensor networks (WSNs). A strategy for energy saving is to cleverly manage the duty cycle of sensors, by dynamically activating different sets of sensors while non-active nodes are kept in a power save mode. We propose a simple and efficient approach for selecting active nodes in WSNs. Our primary goal is to maximize residual energy and application relevance of selected nodes to extend the network lifetime while meeting application-specific QoS requirements. We formalize the problem of node selection as a knapsack problem and adopt a greedy heuristic for solving it. An environmental monitoring application is chosen to derive some specific requirements. Analyses and simulations were performed and the impact of various parameters on the process of node selection was investigated. Results show that our approach outperforms a naı¨ve scheme for node selection, achieving large energy savings while preserving QoS requirements.     

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.     

无线传感器网络分簇路由节能研究

在大规模传感和环境监测中,节约能源延长传感器节点生命已成为无线传感器网络最重要的研究课题之一。提供合理的能源消耗和改善无线网络生命周期的传感器网络系统,必须设计一种新的有效的节能方案和节能路由体系。方案采用一种聚类算法减少无线传感器网络的能量消耗,创建一种cluster-tree分簇路由结构的传感器网络。该方案主要目标是做一个理想的分簇分配,减少传感器节点之间的数据传输距离,降低传感器节点能源消耗,延长寿命。实验结果表明,该方案有效地降低了能源消耗从而延长无线传感器网络生命。     

一种适用于近海环境监测的WSNs节点设计方法

针对传统近海环境监测无线传感器网络（ WSNs）节点存在开发成本高、可扩展性差、通信距离短等不足,提出了一种基于开源Arduino软硬件平台,设计近海环境监测WSNs节点的方法。方法依据近海环境监测的实际需求,首先对传感器节点的微控制板进行了选型与定制,并给出了节点总的功能模块设计框架;然后对节点软硬件设计中涉及的节点供电优化、多种通信机制的融合、长距离通信等关键问题提出了相应的解决方案。实际应用结果表明：设计的节点所构建的WSNs,能实现连续实时采集监测区域的多种环境要素,并将数据稳定可靠地上传至服务器,传感器网相邻节点的通信距离可长达1000 m以上。所设计的WSNs节点具有开发成本低、接口丰富、可扩展性强、组网简单等特点,节点除满足近海环境监测实时获取数据的功能需求外,还可以应用到淡水的实时环境监测,具有较好的应用前景。     

基于CC2530的水产养殖监控系统的设计

为了解决传统水质监测方案中遇到的布线困难、成本高等问题,并能实现对水质环境因子的准确测量与控制,介绍了一种基于无线传感器网络的智能监控系统在水产养殖中的应用。选用集数据收发和数据处理于一体的低功耗芯片CC2530,设计了以CC2530为射频收发器的低功耗无线传感器网络节点,实现了对水产养殖水质参数的采集、处理和显示。在IAR开发环境下编写和编译传感器节点程序,实现了无线传感器网络节点之间的数据传输功能。结果表明:该系统各项技术性能指标达到设计要求,而且系统结构简单,数据传输速度快,功能易扩展,具有推广和应用价值。     

无线传感器网络节点的低功耗设计

无线传感器网络(WSNs)能够协作地实时监测、感知和采集各种环境对象的信息,并将信息传递给系统用户主机进行分析处理。节点具有感知和路由的功能,在实际的应用中,功耗是影响节点工作寿命的关键因素。设计分析了WSNs系统功率消耗的构成,并从硬件和软件方面提出和总结了WSNs的低功耗设计方法,设计了一种低功耗的WSNs节点,并进行了测试,结果证明:该方法适合WSNs节点的应用,具有易使用、低功耗特点。     

嵌入式无线传感器网络节点的设计

介绍了以超低功耗单片机MSP430F149为核心，结合外围传感器和无线收发模块的传感器网络节点的软、硬件设计与实现方案，MSP430F149控制传感器采集环境中的温度、湿度和振动数据，并对原始数据进行初步处理，再由无线收发模块将数据发送给相邻节点，一级级转发最终发送回服务器，实现对环境的监测。     

无线传感网络任务分配的能效性控制策略

无线传感网络包含大量密集分布传感节点,各节点测量产生大量数据给传输、存储、管理和分析带来困难,无线传感网络能源不可更换性限制了网络寿命.本文提出基于熵理论和欧式距离的网络能耗评价指标,采用对等(peer-to-peer,简称P2P)计算方法,利用基于蚁群智能的能效性优化任务分配控制策略,针对中心节点工作状态、传输能耗和网络寿命实现动态实时任务控制分配,完成多中心节点并行计算,提高网络工作效率,节约能耗.实验表明基于蚁群智能的能效性任务分配控制策略能实时有效地缩短无线传感网络计算时间,减少网络能耗,提高网络寿命.     

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.     

基于自组织图算法的水下传感器网络优化部署研究

水下传感器网络部署是开展水下传感器网络相关应用的基础,良好的传感器节点部署方案可以有效提高目标的监测质量;针对水环境中随机事件的突发性和不确定的特点,提出了基于自组织图算法的水下传感器网络优化部署方案;首先,随机部署传感器节点,预设随机事件呈L型不均匀分布,当随机事件发生在传感器覆盖漏洞处时,采用自组织图算法确定传感器节点需要移动到的目标位置;仿真结果表明,基于自组织图算法的水下传感器网络优化部署方案可以显著提高对随机事件的覆盖率,实现对水环境的有效监测。     

Fuzzy rule-based faulty node classification and management scheme for large scale wireless sensor networks

In a wireless sensor network (WSNs), probability of node failure rises with increase in number of sensor nodes within the network. The, quality of service (QoS) of WSNs is highly affected by the faulty sensor nodes. If faulty sensor nodes can be detected and reused for network operation, QoS of WSNs can be improved and will be sustainable throughout the monitoring period. The faulty nodes in the deployed WSN are crucial to detect due to its improvisational nature and invisibility of internal running status. Furthermore, most of the traditional fault detection methods in WSNs do not consider the uncertainties that are inherited in the WSN environment during the fault diagnosis period. Resulting traditional fault detection methods suffer from low detection accuracy and poor performance. To address these issues, we propose a fuzzy rule-based faulty node classification and management scheme for WSNs that can detect and reuse faulty sensor nodes according to their fault status. In order to overcome uncertainties that are inherited in the WSN environment, a fuzzy logic based method is utilized. Fuzzy interface engine categorizes different nodes according to the chosen membership function and the defuzzifier generates a non-fuzzy control to retrieve the various types of nodes. In addition, we employed a routing scheme that reuses the retrieved faulty nodes during the data routing process. We performed extensive experiments on the proposed scheme using various network scenarios. The experimental results are compared with the existing algorithms to demonstrate the effectiveness of the proposed algorithm in terms of various important performance metrics.     

基于Zig Bee技术的大坝安全监测WSNs节点设计

针对无线传感器网络(WSNs)在大坝安全监测中的需求,结合大坝安全监测传感器网络和ZigBee技术的特点,提出一种基于射频芯片CC2430的WSNs大坝安全监测系统解决方案。简要介绍了传感器网络体系结构,重点阐述了其网络节点的硬件设计和软件设计。并在实验室环境下搭建了一个簇-树型传感器网络,对传感器网络进行了测试并对节点进行了标定。实验表明:节点采集传感器数据准确,在实验室环境下数据传输可靠、准确,数据丢失率为0。     

Privacy preserving secure expansive aggregation with malicious node identification in linear wireless sensor networks

The Wireless Sensor Networks (WSNs) used for the monitoring applications like pipelines carrying oil, water, and gas; perimeter surveillance; border monitoring; and subway tunnel monitoring form linearWSNs. Here, the infrastructure being monitored inherently forms linearity (straight line through the placement of sensor nodes). Therefore, suchWSNs are called linear WSNs. These applications are security critical because the data being communicated can be used for malicious purposes. The contemporary research of WSNs data security cannot fit in directly to linear WSN as only by capturing few nodes, the adversary can disrupt the entire service of linear WSN. Therefore, we propose a data aggregation scheme that takes care of privacy, confidentiality, and integrity of data. In addition, the scheme is resilient against node capture attack and collusion attacks. There are several schemes detecting the malicious nodes. However, the proposed scheme also provides an identification of malicious nodes with lesser key storage requirements. Moreover, we provide an analysis of communication cost regarding the number of messages being communicated. To the best of our knowledge, the proposed data aggregation scheme is the first lightweight scheme that achieves privacy and verification of data, resistance against node capture and collusion attacks, and malicious node identification in linear WSNs.     

一种异构传感器网络时间同步的安全性研究

分布式时间同步技术是无线传感器网络（WSNs）应用中的一项重要支撑技术,保证时间同步的安全性至关重要。针对敌对异构网络环境,通过利用存储有高能量的高级传感器,提出了一种高效的异构WSNs时间同步安全方案。Tmote传感器节点实验表明：该方案比现有的同步方案更能有效提高同步精度,减少通信开销和抵御网络的多种攻击。     

基于WSNs的部分覆盖应用的节点唤醒机制

无线传感网络WSNs(Wireless Sensor Networks)已广泛应用于各类领域.然而,由于能量有限,提高传感节点能效是一项挑战工作.休眠调度策略是保存能量、延长网络寿命的有效策略.此外,多数WSNs应用并不要求100％的覆盖.为此,提出面向部分覆盖应用的节点唤醒机制,且标记为PCLA.PCLA机制引用学习自动机去合理地唤醒节点,而其他节点休眠,进而延长网络寿命.首先,唤醒部分节点构成主干网,然后,再利用这些节点的邻居去满足网络覆盖要求.实验数据表明,与同类机制相比,提出的PCLA机制能够有效地满足部分覆盖要求,并且在活动节点数和网络寿命方面也具有较好的性能.     

基于WSNs的医院环境监测系统设计

针对传统医院环境监测系统现场布线难、设备移动性差、测量精度不高的问题,提出了一种基于无线传感器网络( WSNs)技术的医院环境监测系统,并详细介绍了该系统的结构、通信机制及软件实现流程.系统由无线传感器节点依据无线通信机制形成WSNs.在分析影响WSNs能耗的主要因素和现有节能技术基础上,提出了一种基于能量均衡的数据可靠传输算法,即动态能量管理分簇算法( DPMCA),该算法把DPM技术和CA有效结合,有效解决了传统医院环境监测系统中存在的问题.     

Distributed estimation for adaptive sensor selection in wireless sensor networks

Wireless sensor networks (WSNs) are usually deployed for monitoring systems with the distributed detection and estimation of sensors. Sensor selection in WSNs is considered for target tracking. A distributed estimation scenario is considered based on the extended information filter. A cost function using the geometrical dilution of precision measure is derived for active sensor selection. A consensus-based estimation method is proposed in this paper for heterogeneous WSNs with two types of sensors. The convergence properties of the proposed estimators are analyzed under time-varying inputs. Accordingly, a new adaptive sensor selection (ASS) algorithm is presented in which the number of active sensors is adaptively determined based on the absolute local innovations vector. Simulation results show that the tracking accuracy of the ASS is comparable to that of the other algorithms.     

无线传感器网络簇内多传感器数据融合算法

在无线传感器网络(WSNs)中,一般采用电池供电,节能是WSNs设计的研究重点。为了提高测量结果的准确度和降低网络的能耗,提出了一种两层模式数据融合方案。在传感器节点上用格林贝斯准则和顺序加权算法进行低层次数据融合,在簇头节点上用神经网络算法进行高层次数据融合。仿真实验结果表明:两层模式数据融合方案有效减少了网络中的数据传输量,提高了融合数据的精度,降低传感器节点的能耗。     

Using a dynamic backbone for efficient data delivery in solar-powered WSNs

The periodic nature of solar power requires a different approach to energy consumption in wireless sensor networks (WSNs) from battery-based WSNs. Based on the energy model of a solar-powered node, we develop efficient energy-aware topology-control and routing schemes which utilize a backbone network consisting of energy-rich nodes within the WSN. This backbone handles most of the traffic with low latency, while reconfiguring itself dynamically in response to changes in the availability of energy at each node. Simulation results demonstrate that our schemes can achieve a balance between latency and energy consumption.