无线传感器网络远程监测节点的功能扩展电路

在节点现有功能基础上进行外围电路功能扩展是传感器网络应用开发中的常见问题之一。本文以JN5139系列节点为基础,用测量范围较大的高温采集电路,替换了原有的常温传感器;配备了蓄电池电压检测电路,使得监测中心能及时了解节点能量供应情况;通过纽扣电池为节点时钟芯片提供电源,保证节点时钟计时准确性;采用GPRS开关控制电路,降低了汇聚节点能量损耗;设计的看门狗控制电路,提高了节点工作的可靠性和稳定性。     

Investigation of wireless sensor node power consumption profile powered by heterogeneous hybrid energy harvesters with EPDD management algorithm

Node lifetime is the major challenge in the WSN design, which is directly related to the power consumption optimisation. Therefore, there is a necessity to investigate the node power profile so that the hardware designers will have a full picture about the system demand in an early stage of the design. Likewise, it helps the software designers in developing suitable energy-aware operating/routing protocols. This paper profiles an enhanced wireless sensor node called ‘WSN_{_3_HHEH}’ power consumption powered by heterogeneous hybrid energy harvesting and equipped with an improved energy-aware Event-Priority-Driven Dissemination (EPDD) algorithm. The extensive real-world empirical power profiling measurements for each unit and node system level during active and sleep modes are presented, which it provides data on the wireless sensor node architectural design that is applicable for low-power and IoT applications. The results point out that within the WSN_{_3_HHEH} the RF transceiver consumed the highest power of 24 mW, followed by the MCU with 7.5 mW, and the sensor module with 0.16 mW throughout the active period. During the sleeping period however, the MCU unit consumed a noticeable amount of power of 1.8 mW compared to the other sensor node units.     

Analyzing lifetime of energy harvesting underwater wireless sensor nodes

Underwater Wireless Sensor Networks (UWSNs) are utilized to monitor underwater environments that pose many challenges to researchers. One of the key complications of UWSNs is the difficulty of changing node batteries after their energy is depleted. This study aims to diminish the issues related to battery replacement by improving node lifetime. For this goal, three energy harvesting devices (turbine harvester, piezoelectric harvester, and hydrophone harvester) are analyzed to quantitate their impacts on node lifetime. In addition, two different power management schemes (schedule‐driven and event‐driven power management schemes) are combined with energy harvesters for further lifetime improvement. Performance evaluations via simulations show that energy harvesting methods joined by power management schemes can improve node lifetime substantially when actual conditions of Istanbul Bosporus Strait are considered. In this respect, turbine harvester makes the biggest impact and provides lifetime beyond 2000 days for most cases, while piezoelectric harvester can perform the same only for low duty cycle or event arrival values at short transmission ranges.     

智能电网中无线传感器网络的节能节点定位方法

无线传感器网络在智能电网目标检测、监测和定位中得到到越来越多的应用.在无线传感器网络中,能量是一种临界资源,系统寿命通过节能策略得到延长.提出了一种基于能量感知的节点检测和定位方法.这种方法只需要少量的传感器节点信息,由簇头执行定位程序来确定进一步定位所需的传感器子集.这样减少了能量消耗和通信带宽需求,延长了系统寿命.实验结果显示,这种定位方法可以节省高达32％的能量.     

无线传感节点节能措施的研究

在传统的无线传感网络节能措施的基础上,在项目实施过程中,引入了智能电池管理系统,并在其中实现动态电源管理,对整个传感节点的能量进行有效合理的安排.动态电源管理通过对系统的时钟或电压的动态控制,并设置微处理器的寄存器,有选择地关闭不需要的功能模块,以达到节电的目的.同时动态的关闭一些仍然需要的外设控制器来进一步节省能量.并进一步采用均衡能量的方法来延长单个节点的使用寿命,获得更长时间跨度内的有效数据.     

Lifetime optimization of wireless sensor networks with sleep mode energy consumption of sensor nodes

The energy constraint is a major issue in wireless sensor networks since battery cells that supply sensor nodes have a limited amount of energy and are neither replaceable nor rechargeable in most cases. A common assumption in previous work is that the energy consumed by sensors in sleep mode is negligible. With this hypothesis, the usual approach is to iteratively consider subsets of nodes that cover all the targets. These subsets, also called cover sets, are then put in the active mode whereas the others are in the low-power or sleep mode. The scheduling of the appropriate cover sets in order to maximize the network lifetime is a challenging problem known to be NP-hard. The consideration of non-zero energy consumption of sensor nodes in sleep mode is more realistic but significantly increases the complexity of the problem. In this paper, we address this question by proposing a greedy algorithm that gives priority to sensors with lowest energy, and uses a blacklist to limit the number of sensors covering critical targets. Simulations show that this algorithm outperforms the previously published solutions. We then propose for regular arrays, an analytical approach which shows that, for any optimal solution, all sensors’ remaining energies are zero. This theoretical approach sheds a new light on ring connected arrays of odd size, that are known to be rather tricky when non-disjoint cover sets are considered.

     

Uniform thresholding based transmission policy for energy harvesting wireless sensor nodes in fading channel

The work presents a novel computationally efficient transmission policy for throughput maximization over point-to-point sensor links employing harvest-use-store protocol with finite storage capacity battery. In these settings, under finite averaging duration constraint, the stochastic dynamic programming (SDP) technique provides the optimal solution for throughput maximization, but the implementation complexity for SDP is prohibitively large. Thus, there is a need to explore new solutions that can provide near-optimal throughput with lower implementation complexity. The work in this paper presents a adaptive transmission policy based on uniform thresholding that achieves a near-optimal throughput obtainable by SDP. Quantitative comparison with optimal online policies shows that the proposed policy attains performance close to SDP with lower implementation complexity.

     

Energy awareness workflow model for wireless sensor nodes

Before the development of a large‐scale wireless sensor network (WSN) infrastructure, it is necessary to create a model to evaluate the lifespan of the infrastructure, the system performance and the cost so that the best design solution can be obtained. Energy consumption is an important factor that influences the lifespan of WSNs. One of the ways to extend the lifespan of WSNs is to design wireless sensor nodes with low power consumption. This involves component selection and the optimisation of hardware architecture, monitoring software system and protocols to satisfy the requirements of the particular applications. This paper proposes a comprehensive model to describe the workflow of a wireless sensor node. Parameter setup and energy consumption calculation are demonstrated through the model simulation. It provides a mathematical approach to dynamically evaluate the energy consumption of a sensor node. This will benefit the development of wireless sensor nodes based on microprocessors with limited computational capability. Therefore, the model can be applied in dynamic power management systems for wireless sensor nodes or in wireless communication protocols with energy awareness, in particular, for WSNs with self‐organisation. More importantly, the generalisation of the model may be employed as a standard paradigm for the development of wireless sensor node with energy awareness. Copyright © 2012 John Wiley & Sons, Ltd.     

A power management system for energy harvesting and wireless sensor networks application based on a novel charge pump circuit

Energy Harvesting circuits are developed as an alternative solution to supply energy to autonomous sensor nodes in Wireless Sensor Networks. In this context, this paper presents a micro-power management system for multi energy sources based on a novel design of charge pump circuit to allow the total autonomy of self-powered sensors. This work proposes a low-voltage and high performance charge pump (CP) suitable for implementation in standard complementary metal oxide semiconductor (CMOS) technologies. The CP design was implemented using Cadence Virtuoso with AMS 0.35μm CMOS technology parameters. Its active area is 0.112 mm². Consistent results were obtained between the measured findings of the chip testing and the simulation results. The circuit can operate with an 800 mV supply and generate a boosted output voltage of 2.835 V with 1 MHz as frequency.     

Improving communication energy efficiency in wireless networks powered by Renewable energy sources

Energy efficiency is an important issue in wireless networks where the nodes are powered by batteries. In this work, we analyze the energy consumption in one-transmitter-multiple-receiver communication and develop scheduling schemes to improve energy efficiency at the transmitter. Our focus is on systems powered by a renewable energy source such as solar power. We consider an environment where both energy and time to access the wireless channel and transmit data are limited, and data destined for different receivers have different values and incur different energy costs. We present optimal scheduling algorithms that selectively transmit data at calculated rates so that the throughput or the total transmission value is maximized under given time limits and energy constraints.     

Collaborative beamforming for wireless sensor networks with Gaussian distributed sensor nodes

Collaborative beamforming has been recently introduced in the context of wireless sensor networks (WSNs) to increase the transmission range of individual sensor nodes. The challenge in using collaborative beamforming in WSNs is the uncertainty regarding the sensor node locations. However, the actual sensor node spatial distribution can be modeled by a properly selected probability density function (pdf). In this paper, we model the spatial distribution of sensor nodes in a cluster of WSN using Gaussian pdf. Gaussian pdf is more suitable in many WSN applications than, for example, uniform pdf which is commonly used for flat ad hoc networks. The average beampattern and its characteristics, the distribution of the beampattern level in the sidelobe region, and the distribution of the maximum sidelobe peak are derived using the theory of random arrays. We show that both the uniform and Gaussian sensor node deployments behave qualitatively in a similar way with respect to the beamwidths and sidelobe levels, while the Gaussian deployment gives wider mainlobe and has lower chance of large sidelobes.     

Power management of autonomous wireless sensor node for structure health monitoring

This paper presents the design concepts of wireless sensor network system constructed with autonomous sensing nodes, which operates at extremely low power levels. At first, conventional, wired civil structure health-monitoring system is reviewed. Then, the monitoring methodology is discussed focusing quantitative measurement accuracy. Issues of node synchronized sampling, multi-layer cluster, node distance and integrated sensor node module are discussed. Also, radio transceiver protocol candidates are reviewed from the point of connection to the Internet gateway. Sensor node consists of microprocessor, sensing analog front end, and radio transceiver. Last two factors are critical for power consumption. Therefore, low duty cycle measurement is essential, in order to accomplish the ultra low power level, which is equivalent to energy harvesting source, such as piezoelectric and solar cells, sensor node power management device circuit design is demonstrated for the high-spec measurement.     

Optimization of energy-constrained wireless powered communication networks with heterogeneous nodes

In this paper, we generalize conventional time division multiple access (TDMA) wireless networks to a new type of wireless networks coined generalized wireless powered communication networks (g-WPCNs). Our prime objective is to optimize the design of g-WPCNs where nodes are equipped with radio frequency (RF) energy harvesting circuitries along with constant energy supplies. This constitutes an important step towards a generalized optimization framework for more realistic systems, beyond prior studies where nodes are solely powered by the inherently limited RF energy harvesting. Towards this objective, we formulate two optimization problems with different objective functions, namely, maximizing the sum throughput and maximizing the minimum throughput (maxmin) to address fairness. First, we study the sum throughput maximization problem, investigate its complexity and solve it efficiently using an algorithm based on alternating optimization approach. Afterwards, we shift our attention to the maxmin optimization problem to improve the fairness limitations associated with the sum throughput maximization problem. The proposed problem is generalized, compared to prior work, as it seemlessly lends itself to prior formulations in the literature as special cases representing extreme scenarios, namely, conventional TDMA wireless networks (no RF energy harvesting) and standard WPCNs, with only RF energy harvesting nodes. In addition, the generalized formulation encompasses a scenario of practical interest we introduce, namely, WPCNs with two types of nodes (with and without RF energy harvesting capability) where legacy nodes without RF energy harvesting can be utilized to enhance the system sum throughput, even beyond WPCNs with all RF energy harvesting nodes studied earlier in the literature. We establish the convexity of all formulated problems which opens room for efficient solution using standard techniques. Our numerical results show that conventional TDMA wireless networks and WPCNs with only RF energy harvesting nodes are considered as lower bounds on the performance of the generalized problem setting in terms of the maximum sum throughput and maxmin throughput. Moreover, the results reveal valuable insights and throughput-fairness trade-offs unique to our new problem setting.

     

用于无线传感器网络节点的小数分频频率综合器

This paper presents a fractional-N frequency synthesizer for wireless sensor network(WSN) nodes. The proposed frequency synthesizer adopts a phase locked loop(PLL) based structure, which employs an LC voltagecontrolled oscillator(VCO) with small VCO gain(KVCO) and frequency step(fstep) variations, a charge pump(CP)with current changing in proportion with the division ratio and a 20-bit △∑ modulator, etc. To realize constant KVCO and fstep, a novel capacitor sub-bands grouping method is proposed. The VCO sub-groups’ sizes are arranged according to the maximal allowed KVCOvariation of the system. Besides, a current mode logic divide-by-2 circuit with inside-loop buffers ensures the synthesizer generates I/Q quadrature signals robustly. This synthesizer is implemented in a 0.13 m CMOS process. Measurement results show that the frequency synthesizer has a frequency span from 2.07 to 3.11 GHz and the typical phase noise is 86:34 d Bc/Hz at 100 k Hz offset and 114:17 d Bc/Hz at 1 MHz offset with a loop bandwidth of about 200 k Hz, which meet the WSN nodes’ requirements.     

具有能量收集管理的无线传感器节点设计

传感器网络作为物联网的底层核心和感知前端,在实际应用中要求能够长时间连续工作,但是基于电池的有限能源供给严重限制了其灵活设计和长期部署,成为许多领域中影响其应用的重大挑战.能量收集技术使得节点可以从环境获取能量给自身充电,为延长网络寿命提供了一个有效的技术手段.本文设计了一种基于CC2650的无线传感器网络节点,结合基于LTC3331的多源环境能量收集技术,形成了一套完整的带能量补充的微功耗传感器节点.实验通过太阳能板作为能量收集前端进行验证,结果表明其可以实现环境能量的收集和累积存储并驱动节点运行.该节点体积小,自治工作时间长,可以广泛用于环境和结构监测等领域.     

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。     

Prediction-based energy map for wireless sensor networks

A fundamental issue in the design of a wireless sensor network is to devise mechanisms to make efficient use of its energy, and thus, extend its lifetime. The information about the amount of available energy in each part of the network is called the energy map and can be useful to increase the lifetime of the network. In this paper, we address the problem of constructing the energy map of a wireless sensor network using prediction-based approach. Simulation results compare the performance of a prediction-based approach with a naive one in which no prediction is used. Results show that the prediction-based approach outperforms the naive in a variety of parameters. We also investigate the possibility of sampling the energy information in some nodes in the network in order to diminish the number of energy information packets. Results show that the use of sampling techniques produce more constant error curves.     

基于故障节点无线传感网络的数据汇聚算法

核辐射环境的影响和节点能量的有限性,导致无线传感网络(WSNs)节点容易发生故障,如何在基于故障节点WSNs的环境实现有效的数据汇聚已成为研究热点。首先,研究了核辐射对节点射频通信能力的影响,并提出基于核辐射约束下的WSNs的数据汇聚DGP-RA算法。在DGP-RA算法中,节点具有射频和声通信的双通信模式。DGP-RA算法基于奖惩机制,并结合D-S证据理论DST和假设检验理论,识别因核辐射影响而无法通信的故障节点,然后再适应地切换通信模式,抵御辐射影响。仿真结果表明,提出的DGP-RA算法有效地提高了数据传输效率,降低了能量消耗。     

DV-Hop localization methods for displaced sensor nodes in wireless sensor network using PSO

Wireless Networks - Localization of sensor nodes is one of the major challenge in wireless sensor networks. It helps in identifying the geographically area where an event occurred. Most of the...     

无线传感器网络多汇聚节点分簇算法

为解决大规模无线传感器网络的节点通信效率问题,提出无线传感器网络的一种多汇聚节点分簇算法,针对拥有多个汇聚节点的监控区域,对网络进行层次化管理。算法通过对多种参数的综合考虑后产生簇头,并将传感器节点分配到相应的簇,由此可以有效降低节点的非均匀能耗,减少因能耗较大节点的能量过度衰竭而造成网络可用率下降。仿真结果显示,该算法可以延缓首个死亡节点的发生时间,并能有效延长无线传感器网络的整体可用率。