无线传感器网络能量收集技术分析

对无线传感器网络节点的能量供应及其管理技术的现状进行了讨论。分析研究了无线传感器网络节点的能量收集原理、技术与方法,认为无线传感器网络节点能量管理应从节能与供能两方面去解决。对环境中存在的各种能源的收集原理与方法进行了分析,这些能源包括太阳能、风能、声能、振动、热电以及电磁场能等。最后提出了传感器节点应该采用尽可能多的方法从环境中吸取能量,以确保传感器节点能够长期、稳定、可靠地工作。     

无线传感器网络能量收集技术分析

对无线传感器网络节点的能量供应及其管理技术的现状进行了讨论.分析研究了无线传感器网络节点的能量收集原理、技术与方法,认为无线传感器网络节点能量管理应从节能与供能两方面去解决.对环境中存在的各种能源的收集原理与方法进行了分析,这些能源包括太阳能、风能、声能、振动、热电以及电磁场能等.最后提出了传感器节点应该采用尽可能多的方法从环境中吸取能量,以确保传感器节点能够长期、稳定、可靠地工作.     

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.     

基于ARM7的无线传感器网络节点能量管理初探

为了研究无线传感器网络能量管理和组网技术，采用ARM基高性能、低功耗微控制器LPC2138为核心制作了一种新型无线传感器网络节点，该节点由两节AA电池供电。说明了该节点的硬件构成及设计方法，介绍了该无线传感器网络节点使用的电池模型，并给出了一组该节点有效工作状态下的功率。     

可充电传感器网络能量管理策略研究

随着电子技术的快速发展,传感器技术逐渐得到了广泛的应用,无线传感器网络具有成本低、功耗低以及可分布计算等特点,因此被应用的较为广泛,随着无线传感器网络的深入研究,逐渐出现了可充电传感器网络,它是指利用能量收集技术将提供能量的传感器节点构成的无线传感器网络。     

无线传感器网络中的分簇算法

分簇算法是无线传感器网络中实施分层路由所采用的重要方法,尤其是传感器节点受到能量和带宽的严重制约。如何合理、有效地利用分簇算法使得网络中节点的能量分布趋于一致,从而延长网络的生命周期,提高系统的整体性能指标,成为当前无线传感器网络研究领域内的热点问题之一。本文从能量有效性的角度出发,对最新的分簇算法进行研究与分析,指出如何根据无线传感器网络不同的分布区域、应用场景和多样的无线环境,生成性能优越的分簇算法。     

无线传感器网络能耗分析与策略研究

无线传感器网络技术得到了广泛应用,但是该技术一直受能量的制约,因此能量始终是无线传感器网络的核心问题。通过对传感器节点结构与网络体系的分析,得出了传感器网络的能耗特性。为了延长无线传感器网络的生命周期,对传感器节点工作能耗与传感网络能耗做了具体研究,再从低功耗节点设计、网络协议及环境中能量补给三个方面总结出了一套有效的节能策略。     

基于ARM7的无线传感器网络节点能量管理初探

为了研究无线传感器网络能量管理和组网技术,采用ARM基高性能、低功耗微控制器LPC2138为核心制作了一种新型无线传感器网络节点,该节点由两节AA电池供电.说明了该节点的硬件构成及设计方法,介绍了该无线传感器网络节点使用的电池模型,并给出了一组该节点有效工作状态下的功率.     

基于ARM7的无线传感器网络节点能量管理初探

为了研究无线传感器网络能量管理和组网技术,采用ARM基高性能、低功耗微控制器LPC2138为核心制作了一种新型无线传感器网络节点,该节点由两节AA电池供电。说明了该节点的硬件构成及设计方法,介绍了该无线传感器网络节点使用的电池模型,并给出了一组该节点有效工作状态下的功率。     

基于最大生存周期的无线传感器网络能量模型研究

在分析了无线传感器网络的应用和特性的基础上,从节点能量计算模型、节点的能量消耗模型和状态转换模型3个方面论述了无线传感器网络的系统能量模型,通过引入Flag标志和长期睡眠状态机制来防止网络中的某些节点因为过早耗尽能量而死亡,从而实现无线传感器络中节点的能量均衡和网络生存周期的最大化,对无线传感器网络的应用和研究有着深远的意义。     

无线传感器网络节点节能管理方式的研究

无线传感器网络节点数量众多、自身携带的能量十分有限。为了延长网络的生命周期,需采用有效的策略降低能耗。在研究无线传感器网络节点组成结构、能量消耗以及节点间传播方式的基础上,提出一种为有效地达到节能目的所采用的节点管理方式。该方案采用动态选择簇头节点的自组织、多跳路由、层次式拓扑组织结构的路由协议、快速的数据融合技术,并在实现硬件的低功耗设计的条件下进行动态功耗管理。     

利用环境电磁波为无线传感器节点供电新方案

采用无线传感器节点的环境电磁波能量获取关键技术,设计了一种可行的供电方案.通过对所处环境的频谱能量分析和采用合适的天线及转换电路,收集到足够能量驱动节点工作.同时设计了带有唤醒机制的低功耗电源管理电路,以适应节点在环境电磁波能量较少地区的工作.通过获取能量稳定性、有效工作范围和传感器节点的性能相关测试和分析,验证了方案...     

无线传感器网络的覆盖优化机制研究

如何实现最优覆盖是无线传感器组网的一个基本问题.文章分析了传感器覆盖问题的背景,给出了节点调度方案的主要方法和技术原理,探讨了基于网络能量高效的覆盖优化与网络连通性之间的关系,重点阐述了实现区域覆盖和点覆盖的机制.对于覆盖薄弱地区,文章提出了采用分簇方式将覆盖地区划分成许多子区域或簇,用动态移动修复机制提供细粒度的网络监测与覆盖控制.文章认为调度传感器节点在休眠和活动模式之间进行切换,是一种重要节能方法;对于资源受限且拓扑动态变化的无线传感器网络,宜采用分布式和局部化的覆盖控制协议和算法.     

A review on solar forecasting and power management approaches for energy‐harvesting wireless sensor networks

For rechargeable wireless sensor nodes, effective power management is of prime importance because of the stochastic behaviour of the environmental resources. A key issue in integrating solar resources with wireless sensor networks (WSNs) is the need of precise irradiance measurements and power to resource modelling. WSNs are employed in an adhoc manner comprises of numerous sensing nodes and organised as a network for the sake of checking and balancing the environmental factors. Each node has sensing, computation, communication, and locomotion capabilities but operates with limited battery life. Energy harvesting is a way of powering these WSNs by harvesting energy from the environment. By considering harvested energy as an energy source, certain considerations are different from that of battery‐operated networks. Nondeterministic energy availability with respect to time is the reason behind these differences, which put a limit on the maximum rate at which energy can be used. Thus, reliable knowledge of solar radiation is essential for informed design, deployment planning, and optimal management of energy in rechargeable WSNs. Further, power management is essential in self‐powerssed networks to efficiently utilize the available energy. In this paper, a detailed survey on different solar forecasting techniques has been presented for precise energy estimates. A detailed study on energy efficient power management techniques is also proposed to address the feasibility of energy‐harvesting approach in WSNs.     

Reliability modeling and planning of energy harvesting based on uncertainty theory

Energy harvesting network is a new form of computer networks.It can convert the environmental energy into usable electric energy,and supply the electrical energy as a primary or secondary power source to the electronic device for network communication.However,the energy harvesting process has great volatility and uncertainty,the traditional analytical method based on probability distribution function to describe the energy collection process can not accurately simulate the actual situation,resulting in higher depletion probability of nodes,then the reliability cannot be guaranteed as a result.For this,the energy harvesting reliability of energy harvesting nodes was defined,represented with the degree of normal operation,respectively set up the node reliability models with no battery and infinite battery.As an example for maximum node achievable rate,the uncertain multilevel programming model based on node reliability was put forward,then the network efficiency was improved under the premise of ensuring node reliability.An energy average allocation (EAA) algorithm was proposed and the upper bound of competitive ratio of the algorithm was proved theoretically.Finally,the actual wind power data was taken as an example to verify the feasibility and effectiveness of the proposed model and method.     

A distributed,multi‐hop,adaptive, tree‐based energy‐balanced routing approach

To accomplish the primary objective of data sensing and collection of wireless sensor networks (WSN), the design of an energy efficient routing algorithm is very important. However, the energy constrained sensing nodes along with the intrinsic properties of the (WSN) environment makes the routing a challenging task. To overcome this routing dilemma, an improved distributed, multi‐hop, adaptive, tree‐based energy‐balanced (DMATEB) routing scheme is proposed in this paper. In this scheme, a relay node is selected in view of minimum distance and high energy from a current sensing node. Further, the parent node is chosen among the selected relay nodes on the basis of high residual energy and less power consumption with due consideration of its associated child nodes. As each sensing node itself selects its parent among the available alternatives, the proposed scheme offers a distributive and adaptive approach. Moreover, the proposed system does not overload any selected parent of a particular branch as it starts acting as a child whenever its energy lowers among the other available relay nodes. This leads to uniform energy utilization of nodes that offers a better energy balance mechanism and improves the network lifespan by 20% to 30% as compared with its predecessors.     

ROTEE: Remora Optimization and Tunicate swarm algorithm-based Energy-Efficient cluster-based routing for EH-enabled heterogeneous WSNs

Since the development of Wireless Sensor Networks (WSNs), the limited battery of the sensor nodes has been an unavoidable concern. Hence, to keep the WSNs operational for a longer possible duration, the recharging of node's battery through harvesting the ambient energy from surroundings (for an example, solar energy) has been proposed. In this work, we focus not only on utilizing the energy harvesting (EH)-enabled sensor nodes for routing purposes but also introduce a novel hybrid optimization ROATSA that uses Remora Optimization Algorithm (ROA) and Tunicate Swarm Algorithm (TSA) for energy-efficient cluster-based routing. The proposed work is termed as ROA and TSA-based Energy-Efficient Cluster-based Routing for EH-enabled WSN (ROTEE). Hybrid ROATSA is chosen due to enhanced convergence and exploitation capabilities. To reduce the financial burden on the network, we use only four EH-enabled nodes and locate them at each periphery of the network, equidistant to each other and the other nodes are 3-level energy heterogeneous sensor nodes. The selection of cluster head (CH) is optimized through ROATSA by considering profile index of each node by evaluating them at energy, distance, load balancing, node density, the delay involved, and network's average energy. The proposed work ROTEE shows supreme performance against the recently proposed clustering techniques.     

基于新型电源供电的无线传感网络节点设计

基于新型集成式压电能量收集模块LTC3588-1,结合压电自发电单元特性,进行了面向环境监测的无线传感网路节点的设计.实验结果表明,与改进后的电荷捕获电路相比,系统具有能量收集效率高、传输距离较远等优点,有效地解决了无线传感网络节点能源供电的问题,达到了节能环保的目的.     

物联网能量获取节点的研究与实现

物联网应用中,节点的能量是限制节点性能和决定网络寿命的关键因素.环境能量获取技术的使用可以为物联网节点的能量补给提供完美的解决方案.研究并实现了基于太阳能获取技术的3种节点电路方案,并搭建简单网络测试节点的工作特性,对特定区域的物联网应用提供了参考能量获取方案.