无线传感器网络的节点功耗研究

近年来,无线传感器网络因其低成本、低功耗、分布式和自组织等特点,得到了广泛的关注。因网络中节点能量受限,因此节点功耗研究是一个关键问题。无线传感器网络中节点的基本任务是数据的采集、处理以及与其它节点间的通信。由于节点在同一时间可能感知到多个节点,而与这些节点通信的数据就会形成一个队列。节点与邻节点进行数据通信的同时,节点能量损耗分配也形成了一个队列。本文中,我们提出了一个数学队列模型,利用最优解来优化传感器节点的能量消耗。仿真结果表明,所提出的模型在能量损耗方面具有良好的性能,能够有效延长网络生命周期。     

区域重叠的无线传感器网络节点定位算法研究

传感器节点的自身定位是无线传感器网络应用的一个重要研究方向。为了确定节点的位置,需应用各种限制条件对其所在区域进行求解,找到解的交集,即找出符合各种条件的重叠区域。以区域的形状为线索,对基于区域重叠的无线传感器网络节点的定位算法进行了研究,分析了几种典型算法的原理与特点,对同一类算法优缺点进行了对比,对部分算法进行了仿真,得出了区域重叠算法的研究重点。最后对无线传感器网络定位的发展趋势进行了展望。     

无线传感器网络节点太阳能电源系统设计

对于无线传感器网络节点而言,电源是系统的关键部分之一。在此提出一种收集环境中太阳能为传感器节点供能的电源系统。该系统采用了高效安全的充电控制技术,独特的电池电压监测电路,以及低功耗的DC—DC转换电路。通过实验验证,基于此太阳能电源的传感器节点功耗动态调整节性能好,生存周期显著增加。该系统可应用于各种户外监测的节点,如环境监测,精细农业,森林防火等。     

无线传感器网络节点的设计

无线传感器网络是一种以无中心节点的全分布系统。通过随机投放的方式,众多传感器节点被密集部署于监控区域。这些传感器节点集成有传感器、数据处理单元和通信模块,它们通过无线信道相连,自组织地构成网络系统。传感器节点借助于其内置的形式多样的传感器,测量所在周边环境中的相关信号,传感器节点间具有良好的协作能力,通过局部的数据交换来完成全局任务。     

无线传感器网络节点定位技术

本文从算法性能、已有的定位算法、定位算法的分类和WSN节点定位机制的评价标准等方面,针对无线传感器的网络定位技术进行详细的分析和探讨。并与经典的APIT算法、凸规划定位算法进行了比较。结论显示出在不同的环境之下不同的算法各有优劣,并不能指出最好的算法。实际操作中应该根据实际的需求来选择算法,并对未来无限传感器网络节点定位技术的发展方向做出了预测。     

无线传感器网络节点定位机制研究

传感器网络中的节点定位问题与很多实际应用直接相关,主要有两类算法,即 rang-free和rang-based,这两类定位算法各有其优势和不足.为了研究算法的发展趋势,比较了几种典型的定位算法,指出了各自的优缺点.     

基于ZigBee的无线传感器网络节点的设计

针对无线传感器网络节点体积小、能耗低、存储和通信能力有限等特点,从ZigBee协议栈的结构特点出发,提出一种基于ZigBee的无线传感器网络节点的设计方案.详细地阐述了构成传感器节点的各个模块的设计,即采用了CC2430芯片作为核心元件,使用温湿度传感器SHT11进行温湿度数据采集,并给出了节点软件设计方案.经过测试证明,该节点运行稳定可靠并具有较高的通信效率.     

无线传感器网络节点的自身定位

无线传感器网络的自身节点的定位对网络来说是非常重要的，传感器节点是随机分布在网络中的，这关系到网络最终的定位精度；节点自身定位的方法从节点的个数主要有单点定位和两个节点的定位，这里提出另一种定位方法，运用三个节点实现传感器网络的节点定位。     

无线传感器网络节点定位技术

无线传感器网络(Wireless Sensor Network,WSN)在许多领域有广泛的应用,无线传感器网络中节点位置对无线传感器网络的应用有重要的影响,没有位置属性的信息是无价值的,定位技术是无线传感器网络的重要研究方向之一。依据测距和非测距的分类方法,介绍节点定位技术的基本原理和方法及当前的发展状况,最后对节点定位技术的发展方向作展望。     

无线传感器网络节点电源系统设计

在影响无线传感器网络的生命周期的众多因素中,节点的能量是其中最为重要的。文中设计了一种基于太阳能电池板和锂电池的节点电源系统,能够为节点数传模块提供电源并为传感器提供5V和12V电源,实现了在有阳光的环境中为无线节点永久性供电与无线传感网络无限使用的目的。     

基于能量和密度的WSNs动态分区成簇路由算法

针对传统的层次型网络存在的分簇不合理和能耗不均衡等问题,提出了一种基于能量和密度的动态非均匀分区成簇路由算法。该算法先根据节点与基站之间的距离将网络合理地进行动态的区域划分,在区域内成簇,使靠近基站的簇规模小于距离基站较远的簇,减少靠近基站的簇首负担和能量消耗;通过综合考虑节点剩余能量和节点密度等因素来优化簇的非均匀划分和簇首的选择,簇首间采取基于数据聚合的多跳传输机制。仿真结果表明,与经典路由算法LEACH相比,该算法能有效均衡节点能耗,延长网络生命周期。     

Efficient flow‐control algorithm cooperating with energy allocation scheme for solar‐powered WSNs

Recently, solar energy emerged as a feasible supplement to battery power for wireless sensor networks (WSNs) which are expected to operate for long periods. Since solar energy can be harvested periodically and permanently, solar‐powered WSNs can use the energy more efficiently for various network‐wide performances than traditional battery‐based WSNs of which aim is mostly to minimize the energy consumption for extending the network lifetime. However, using solar power in WSNs requires a different energy management from battery‐based WSNs since solar power is a highly varying energy supply. Therefore, firstly we describe a time‐slot‐based energy allocation scheme to use the solar energy optimally, based on expectation model for harvested solar energy. Then, we propose a flow‐control algorithm to maximize the amount of data collected by the network, which cooperates with our energy allocation scheme. Our algorithms run on each node in a distributed manner using only local information of its neighbors, which is a suitable approach for scalable WSNs. We implement indoor and outdoor testbeds of solar‐powered WSN and demonstrate the efficiency of our approaches on them. Copyright © 2010 John Wiley & Sons, Ltd.     

IRS: application reconfiguration scheme for wireless sensor networks

Application reconfiguration is essential to achieving flexibility and adaptability of wireless sensor networks (WSNs) used in environment monitoring. In this paper, we present an integrated reconfiguration scheme (IRS) for implementing environment adaptive application reconfiguration (EAAR) in WSNs. In our scheme, application reconfiguration is implemented with the push‐based paradigm for densely distributed nodes and the cluster‐based hybrid reconfiguration (CHR) paradigm for sparsely distributed nodes. We demonstrate the energy‐efficiency and scalability of our scheme by analyzing the energy consumption based on a randomly deployed sensor network. Moreover, we derive the density threshold of reconfiguration nodes (RNs) for determining if the nodes are densely or sparsely distributed, and choose the mode of operation for IRS. We use extensive simulation experiments to demonstrate the effectiveness of our scheme. Copyright © 2009 John Wiley & Sons, Ltd.     

GWO‐C: Grey wolf optimizer‐based clustering scheme for WSNs

A wireless sensor network (WSN) is a prominent technology that could assist in the fourth industrial revolution. Sensor nodes present in the WSNs are functioned by a battery. It is impossible to recharge or replace the battery, hence energy is the most important resource of WSNs. Many techniques have been devised and used over the years to conserve this scarce resource of WSNs. Clustering has turned out to be one of the most efficient methods for this purpose. This paper intends to propose an efficient technique for election of cluster heads in WSNs to increase the network lifespan. For the achievement of this task, grey wolf optimizer (GWO) has been employed. In this paper, the general GWO has been modified to cater to the specific purpose of cluster head selection in WSNs. The objective function for the proposed formulation considers average intra‐cluster distance, sink distance, residual energy, and CH balancing factor. The simulations are carried out in diverse conditions. On comparison of the proposed protocol, ie, GWO‐C protocol with some well‐known clustering protocols, the obtained results prove that the proposed protocol outperforms with respect to the consumption of the energy, throughput, and the lifespan of the network. The proposed protocol forms energy‐efficient and scalable clusters.     

无线传感器网络中能量有效的波束成形机制

针对无线传感器网络中单个节点能量和通信距离均受限,以及传统波束成形机制中由于忽略能耗均衡而造成单个节点过早死亡的特点,提出了一种能量有效的波束成形机制。首先分析了节点个数、发射系数、功率受限、相位等因素对网络能耗的影响,给出了对应的设计原则。然后,基于此原则来选择参与发射的节点,并结合节点的剩余能量和相位来调整各自的发射系数。理论分析和仿真结果表明,该机制有效地增加了数据成功传输的次数,均衡了节点间的能耗,延长了网络寿命。     

Systematic energy-balanced cooperative transmission scheme in wireless sensor networks

Energy efficiency is a critical issue in wireless sensor networks(WSNs).In order to minimize energy consumption and balance energy dissipation throughout the whole network,a systematic energy-balanced cooperative transmission scheme in WSNs is proposed in this paper.This scheme studies energy efficiency in systematic view.For three main steps,namely nodes clustering,data aggregation and cooperative transmission,corresponding measures are put forward to save energy.These measures are well designed and tightly coupled to achieve optimal performance.A half-controlled dynamic clustering method is proposed to avoid concentrated distribution of cluster heads caused by selecting cluster heads randomly and to get high spatial correlation between cluster nodes.Based on clusters built,data aggregation,with the adoption of dynamic data compression,is performed by cluster heads to get better use of data correlation.Cooperative multiple input multiple output(CMIMO) with an energy-balanced cooperative cluster heads selection method is proposed to transmit data to sink node.System model of this scheme is also given in this paper.And simulation results show that,compared with other traditional schemes,the proposed scheme can efficiently distribute the energy dissipation evenly throughout the network and achieve higher energy efficiency,which leads to longer network lifetime span.By adopting orthogonal space time block code(STBC),the optimal number of the cooperative transmission nodes varying with the percentage of cluster heads is also concluded,which can help to improve energy efficiency by choosing the optimal number of cooperative nodes and making the most use of CMIMO.     

一种基于树状结构的无线传感网络低功耗算法

针对无线传感器网络（Wireless sensor networks,WSNs）的能耗问题,在保证低延迟率的前提下,通过降低空闲模式下的能量消耗,提出一种适用于大型树簇状无线传感器网络结构的位图辅助式低功耗算法（Bit-map assisted low power algorithm,BALPA）,建立了能量模型。仿真结果表明：此算法和传统TDMA、低功耗TDMA（E-TDMA）算法相比,在相同参数下,最多能减少35%的能耗,显著降低能量开销和数据包延迟速度,延长系统的使用寿命。     

Fuzzy-based techniques for clustering in wireless sensor networks (WSNs): Recent advances,challenges, and future directions

A wireless sensor network (WSN) is a network of tiny sensors deployed to collect data. These sensors are powered with batteries that have limited power. Recharging and/or replacement of these batteries, however, are not always feasible. Over the past few years, WSN applications are being deployed in diverse fields such as military, manufacturing, healthcare, agriculture, and so on. With the ever-increasing applications of WSNs, improving the energy efficiency of the WSNs still remains to be a challenge. Applying fuzzy logic to the problem of clustering exploits the uncertainty associated with the factors that affect the lifetime of these sensors and enables the development of models that would improve their performance in real-world applications. We present a comprehensive review of various fuzzy-based techniques for clustering in WSNs whose main goal is to optimize energy usage in WSNs while simultaneously improving their overall performance.     

无线传感器网络中基于拥塞程度分级的速率调节机制

文中提出一种基于拥塞程度分级的速率调节算法.首先,对缓冲区进行多尺度排队分析,计算出缓冲区的溢出概率.其次,根据溢出概率的值,把节点拥塞程度分成三级.最后,针对每一级拥塞采取相应的速率调节方案来缓解拥塞.实验结果表明,该算法可以有效缓解拥塞,提高无线传感器网络的数据包投递率.     

无线传感器网络时间序列流量预估算法

提出了一种专用于无线传感器网络流量预估的时间序列模型ATFA/WSN。ATFA/WSN可对未来工作周期内的网络流量进行预估,并根据预估值实现对网络路由、占空比、能耗等的自适应控制。对采集的流量数据经过NS2仿真实验进行预估并和原始流量对比,发现该模型预估的流量和原始值偏差很小,将其应用于SMAC协议的自适应占空比控制,取得了较好的节能效果。