共查询到18条相似文献,搜索用时 140 毫秒
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由于无线传感器网络节点部署是随机的而且数量巨大,会产生很多冗余的节点,因而对网络进行覆盖控制提高冗余节点的利用率就成为一个亟待解决的问题.针对无线传感器网络中的三维覆盖问题进行了深入的研究,提出了一种分布式能量有效的三维覆盖控制算法,并利用OPNET网络仿真软件对其性能进行了验证. 相似文献
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王樱锦 《数字社区&智能家居》2022,(7):36-37
覆盖控制问题是无线传感器网络研究的基本问题之一.该文根据无线传感器网络中的覆盖控制原理,设计并实现了一个仿真平台,然后选取覆盖控制算法中的一个典型算法作为研究对象,在该平台上实现了该算法,研究其在定位存在误差情况下的性能变化情况. 相似文献
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针对三维无线传感器网络中节点非均匀覆盖需求的问题,提出一种基于虚拟力的三维覆盖算法(3D-CAVF).该算法是将虚拟力应用在无线传感器网络中实现节点布置, 通过虚拟力和拥挤度控制, 使节点能够自动覆盖事件, 并且使节点和事件的密度呈现一种平衡的效果.在Matlab平台上进行仿真实验,将所提算法与基于人工势场的三维部署算法(APFA3D)、基于未知目标精确覆盖的三维部署算法(ECA3D)进行比较,在事件呈T型不均匀部署和线型不均匀部署两种情况下进行实验,所提算法的事件集覆盖效能比APFA3D、ECA3D 算法有3.6%、3.1%的提高.仿真实验结果表明所提算法能够有效处理三维无线传感器网络中节点的布置问题. 相似文献
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针对三维无线传感器网络区域中节点覆盖的问题,提出一种半径可调的无线传感器网络三维覆盖算法(3D-CAAR)。该算法利用虚拟力作用实现无线传感器网络的节点均匀部署,同时结合传感器节点的半径可调覆盖机制,判断节点与被覆盖区域中目标点之间的距离。引入能耗阈值,使得节点根据自身情况调节节点感知半径,从而降低无线传感器网络的整体能耗,提高了节点利用率。最后,通过与传统基于人工势场的三维部署算法(APFA3D)、基于与未知目标精确覆盖的三维算法(ECA3D)仿真实验对比,3D-CAAR的事件集覆盖效能明显较高,能有效解决三维无线传感器网络中对目标节点的覆盖问题。 相似文献
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覆盖作为无线传感器网络中基本问题直接影响着网络的服务质量,在分析传统二维无线传感器网络覆盖增强算法的基础上,建立新的传感器节点三维感知模型,在此基础上提出了一种面向三维空间的无线传感器网络覆盖增强节能算法.该算法通过智能算法优化调节传感器节点位置从而使节点比较均匀分布在监测区域中,在此基础上,采用集合覆盖模型算法计算出... 相似文献
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覆盖控制是无线传感器网络中的基本问题之一,动态覆盖问题又在很多领域有其独到的应用价值。为了更好地实现动态覆盖,基于集中式Voronoi网格细分( CVT)理论,结合Lloyd算法,提出了一种无线传感器网络动态覆盖算法,通过调整目标覆盖区域几何边界,协同调度无线传感器网络节点,从而实现目标区域无线传感器网络动态覆盖。在仿真中,进行了正方形、正方形—圆形障碍静态边界区域覆盖实验和正方形—长方形目标区域、正方形—十字形目标区域、正方形—H形目标区域动态边界覆盖实验,验证了控制算法的有效性,并对不同目标覆盖区域形状、节点数量、覆盖程度、覆盖效率进行了分析。 相似文献
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该文介绍了无线传感网络在智能楼宇中的应用,详细分析了基于无线传感网络的楼宇火灾监测预警系统的系统结构,并从数学角度论证了一种在楼宇环境内应用的无线传感网络节点高效覆盖算法,有效地解决了冗余覆盖问题。 相似文献
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为了提高无线多媒体传感器网络(WMSNs)区域覆盖率,在传感器节点随机部署后,通过调节传感器节点的感知方向,使节点从感知重叠区域向覆盖盲区转动,提高网络覆盖率。针对现有算法中存在覆盖效率和覆盖率不能统一的问题,提出一种改进的虚拟力覆盖算法(VFARCR),该算法利用传感器节点感知扇形区域质心点间的斥力调节感知方向,且通过传感器节点间的覆盖冗余度的决定方向调整的大小,虚拟力和覆盖冗余度共同控制传感器的转动。仿真实验表明:该算法提高了覆盖效率和覆盖效果,提高了虚拟力覆盖算法的性能。 相似文献
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无线传感器网络中覆盖控制技术综述 总被引:7,自引:3,他引:4
覆盖控制是无线传感器网络应用的一个基本问题,反映了网络所能提供的"感知"服务质量,可以使无线传感器网络的空间资源得到优化分配,进而更好地完成环境感知、信息获取和有效传输的任务;立足于无线传感器网络的覆盖控制问题,分析了网络覆盖技术在国内外研究的现状与发展,指出了传感器网络覆盖算法中需要解决的问题,并提出了将多目标进化算法与智能计算技术用于动态覆盖控制技术研究设想。 相似文献
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《Computer Communications》2007,30(14-15):2968-2975
Clustering has been well received as one of the effective solutions to enhance energy efficiency and scalability of large-scale wireless sensor networks. The goal of clustering is to identify a subset of nodes in a wireless sensor network, then all the other nodes communicate with the network sink via these selected nodes. However, many current clustering algorithms are tightly coupled with exact sensor locations derived through either triangulation methods or extra hardware such as GPS equipment. However, in practice, it is very difficult to know sensor location coordinates accurately due to various factors such as random deployment and low-power, low-cost sensing devices. Therefore, how to develop an adaptive clustering algorithm without relying on exact sensor location information is a very important yet challenging problem. In this paper, we try to address this problem by proposing a new adaptive clustering algorithm for energy efficiency of wireless sensor networks. Compared with other work having been done in this area, our proposed adaptive clustering algorithm is original because of its capability to infer the location information by mining wireless sensor energy data. Furthermore, based on the inferred location information and the remaining (residual) energy level of each node, the proposed clustering algorithm will dynamically change cluster heads for energy efficacy. Simulation results show that the proposed adaptive clustering algorithm is efficient and effective for energy saving in wireless sensor networks. 相似文献
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Joint routing, scheduling, and power control for multichannel wireless sensor networks with physical interference 总被引:1,自引:0,他引:1
Reliability and real-time requirements bring new challenges to the energy-constrained wireless sensor networks, especially to the industrial wireless sensor networks. Meanwhile, the capacity of wireless sensor networks can be substantially increased by operating on multiple nonoverlapping channels. In this context, new routing, scheduling, and power control algorithms are required to achieve reliable and real-time communications and to fully utilize the increased bandwidth in multichannel wireless sensor networks. In this paper, we develop a distributed and online algorithm that jointly solves multipath routing, link scheduling, and power control problem, which can adapt automatically to the changes in the network topology and offered load. We particularly focus on finding the resource allocation that realizes trade-off among energy consumption, end-to-end delay, and network throughput for multichannel networks with physical interference model. Our algorithm jointly considers 1) delay and energy-aware power control for optimal transmission radius and rate with physical interference model, 2) throughput efficient multipath routing based on the given optimal transmission rate between the given source-destination pairs, and 3) reliable-aware and throughput efficient multichannel maximal link scheduling for time slots and channels based on the designated paths, and the new physical interference model that is updated by the optimal transmission radius. By proving and simulation, we show that our algorithm is provably efficient compared with the optimal centralized and offline algorithm and other comparable algorithms. 相似文献