无线传感器网络中的近似Unit Delaunay功率控制算法

提出一种新几何结构AUDT,将其作为无线传感器网络的底层逻辑拓扑后,每个节点依据最远的逻辑邻居调整到最小发射功率;AUDT从理论上保证网络拓扑的双向连通、平面、逻辑邻居有界及延迟性能的上界等。仿真实验显示,AUDT与其他相似算法相比,在网络延迟相当的情况下,可以获得更小的发射功率和通信干扰,特别是其构造通信开销已经达到最小。     

基于Voronoi的无线传感器网络覆盖控制优化策略

针对无线传感器网络运行状态中存在覆盖空洞的问题,提出了一种基于Voronoi有效覆盖区域的空洞侦测修复策略。该策略以满足一定网络区域覆盖质量为前提,在空洞区域内合理增加工作节点以提高网络覆盖率为优化目标,采用几何图形向量方法对节点感知范围和Voronoi多边形的位置特性进行理论分析,力求较准确地计算出空洞面积,找寻最佳空洞修复位置,部署较少的工作节点保证整个网络的连通性。仿真结果表明,该策略能有效地减少网络总节点个数和感知重叠区域,控制网络中冗余节点的存在,同时其收敛速度较快,能够获得比现有算法更高的目标区域空洞修复率,实现网络覆盖控制优化.     

无线传感器网络分布式概率覆盖保持协议

覆盖配置能有效缓解无线传感器网络中节点能量受限的问题,但现有的研究多是基于物理覆盖,这与实际的信号传播特点不符.针对这一问题,提出了分布式传感器网络概率覆盖保持协议(DPCCP),该协议基于概率探测模型,利用Voronoi划分在节点本地执行概率覆盖判断算法.仿真实验中,将DPCCP嵌入LEACH路由协议,形成LEACHE协议,验证算法效率.仿真结果表明,DPCCP在保持网络覆盖度的同时,可关闭大量冗余节点,有效地延长了网络寿命.     

无线传感器网络基于参数可调增强型覆盖控制算法

覆盖问题是无线传感器网络领域的一个基本问题,也是无线传感器网络特性当中的一个重点问题.如何通过某种算法达到以最少传感器节点对监测区域的有效覆盖已成为目前研究的一项重要课题.因此,提出一种增强型覆盖控制算法(Enhanced Coverage Control Algorithm, ECCA).该算法通过概率理论知识可以有效地求解出对监测区域进行有效覆盖下的最少节点,给出了传感器节点概率的期望值计算方法以及目标节点首次被传感器节点覆盖和多次覆盖后的期望值求解过程,验证随机变量相互之间不独立时的比例函数关系.仿真结果表明,ECCA算法可以使用较少的传感器节点数量完成对监测区域的有效覆盖,提高了对监测区域的覆盖质量.     

基于Voronoi图的无线传感器网络覆盖算法研究

覆盖问题在无线传感器网络研究中具有很重要的地位,用最少的节点获得最大的覆盖面积是研究目标。Voronoi图,又叫泰森多边形或Dirichlet图,它是由一组由连接两邻点直线的垂直平分线组成的连续多边形组成。在一对邻近节点间,垂直平分线上的每个点被感知到的概率最小。文章中,作者提出一种基于Voronoi图的无线传感器网络覆盖算法,算法中先找出最大可能盲点,然后重新部署节点,以达到用最少的节点获得最大的监测面积。仿真实验证明了算法有效性。     

一种无线传感器网络的能耗平衡覆盖模型

针对无线传感器网络节点能量有限、最小覆盖方法能耗不均衡的问题,该文提出了一种能耗平衡的连通覆盖模型,并对模型进行了分析与仿真。模型利用Voronoi划分和Delaunay三角剖分对传感器网络进行分割,判别重复覆盖目标区域的冗余传感器节点,采用节点到sink点的跳数对节点分层,进而提出选择休眠节点的方法。仿真结果表明,由模型建立的非最小连通覆盖集所导出的无线传感器网络,能够平衡节点能耗、使用优化路由、减弱路由关键点的影响。     

无线传感器网络的WPCS覆盖策略

延长无线传感器网络生存时间的有效方法是让冗余节点进入休眠状态。而现有研究多是基于传感器感知模型为圆形的假设前提。该文集中讨论传感器感知模型非圆时,覆盖与连通性之间的联系,并提出适用性更广的WPCS(Well-Proportioned Coverage Strategy)覆盖策略。WPCS覆盖策略以最小化重叠面积为准则,其目的是最大化网络生存时间。仿真实验表明,WPCS性能优于CCP(Coverage Configuration Protocol),且具有一般性,并能很好地减少工作传感器数目,延长网络寿命。     

无线传感器网络部署及其覆盖问题研究

无线传感器网络是近几年发展起来的一种新兴技术,在条件恶劣和无人坚守的环境监测和事件跟踪中显示了很大的应用价值。节点部署是无线传感器网络工作的基础,对网络的运行情况和寿命有很大的影响。部署问题涉及覆盖、连接和节约能量消耗3个方面。该文重点讨论了网络部署中的覆盖问题,综述了现有的研究成果,总结了今后的热点研究方向,为以后的研究奠定了基础。     

无线多媒体传感器网络部署控制算法

已有的无线多媒体传感器网络（WMSNs）研究针对传感器放置在目标区域内的情况进行,且没有考虑节点通过云台的转动获得的整个可能感知区域对覆盖率的影响。本文首先针对节点放置点高于目标区域的应用进行研究,综合考虑节点感知区域和可能感知区域,建立了延时和无延时感知模型,并针对不同的感知模型提出了传感器网络部署控制算法（IVPDCA）,算法中改进了虚拟势场算法,定义了节点质量的概念来表示节点间覆盖重叠的大小,建立受力模型,使得节点在合力作用下进行重新部署,同时关闭冗余节点,既延长了网络寿命,又提高了区域覆盖率。仿真结果验证了算法的有效性。     

无线传感器网络中覆盖问题的研究

简要介绍了无线传感器网络体系结构、特点和应用领域.针对无线传感器网络节点覆盖问题进行了研究,提出了基于最短路径的覆盖算法,并给出了仿真结果.     

基于概率模型的无线传感器网络优化覆盖算法

为了更好地解决无线传感器网络在覆盖过程中出现大量冗余信息及节点能量消耗不均衡等现象,提出了一种节点能量均衡的最优覆盖算法。该算法利用监测区域内传感器节点与目标节点的从属关系建立网络模型,给出传感器节点与目标节点之间的从属关系;通过从属关系和概率理论,求解传感器节点对目标节点的覆盖期望值,然后计算出覆盖监测区域所需最少传感器节点数量。实验结果表明,该算法不仅可以使用最少传感器节点完成对监测区域的有效覆盖,而且抵制了冗余信息数据的产生,提高了网络生存周期。     

Hybrid algorithm optimization for coverage problem in wireless sensor networks

Telecommunication Systems - With the continuous development of evolutionary computing, many excellent algorithms have emerged, which are applied in all walks of life to solve various practical...     

Location-unaware coverage in wireless sensor networks

In scenarios where sensors are placed randomly, redundant deployment is essential for ensuring adequate field coverage. This redundancy needs to be efficiently exploited by periodically selecting a subset of nodes (referred to as a “cover”) that actively monitor the field, and putting the remaining nodes to sleep. We consider networks in which sensors are not aware of their locations or the relative directions of their neighbors. We develop several geometric and density-based tests that enable a location-unaware sensor to intelligently determine whether it should turn itself off without degrading the quality of field coverage. These tests rely on distance measurements and exchanged two-hop neighborhood information. We design an algorithm (LUC) that exploits these tests for computing covers. Based on this algorithm, we propose two distributed protocols (LUC-I and LUC-P) that periodically select covers and switch between them so as to extend the network lifetime and tolerate unexpected failures. Our protocols are highly efficient in terms of message overhead and processing complexity. We implement LUC-I in TinyOS and evaluate it using the TOSSIM simulator. Experimental results indicate that our approach significantly prolongs the network lifetime and achieves comparable performance to location-aware protocols.     

基于PSO的无线多媒体传感器网络覆盖增强算法

在无线多媒体传感器网络(Wireless Multimedia Sensor Networks,WMSNs)中,由于节点部署的不合理,往往存在较多的监控盲区,影响了网络的服务质量。为了提高网络的覆盖率,在有向感知模型基础的基础上,提出了一种基于粒子群算法的WMSNs覆盖增强算法PSOCE。PSOCE算法以网络覆盖率为优化目标,以粒子群算法为计算工具,同时对节点的位置与主感知方向进行调整。仿真试验表明,PSOCE算法能够有效地改进WMSNs的覆盖质量,网络的覆盖率能提高6%～12%。     

Maximal coverage hybrid search algorithm for deployment in wireless sensor networks

A vital design aspect in the setting up of a wireless sensor network is the deployment of sensors. One of the key metrics of the quality of deployment is the coverage as it reflects the monitoring capability of the network. Random deployment is a sub-optimal method as it causes unbalanced deployment and requires sensors in excess of the planned deployment to achieve the same level of coverage. To achieve maximum coverage with a limited number of sensors, planned deployment is a preferred choice. Maximizing the coverage of the region of interest with a given number and type of sensors is an optimization problem. A novel maximal coverage hybrid search algorithm (MCHSA) is proposed in this paper to solve this problem. The MCHSA is a hybrid search algorithm that achieves the balance between exploration and exploitation by applying the particle swarm optimization as a global search technique and using the Hooke–Jeeves pattern search method to improve the local search. The algorithm starts with a good initial population. The proposed MCHSA has low computational complexity and fast convergence. The performance of the MCHSA is analyzed by performing a comparison with the existing algorithms in the literature, in terms of coverage achieved and number of fitness function evaluations. The paper also discusses the tuning of parameters of the proposed algorithm.

     

Information coverage for wireless sensor networks

Coverage is a very important issue in wireless sensor networks. Current literature defines a point to be covered if it is within the sensing radius of at least one sensor. In this paper we argue that this is a conservative definition of coverage. This definition implicitly assumes that each sensor makes a decision independent of other sensors in the field. However, sensors can cooperate to make an accurate estimation, even if any single sensor is unable to do so. We then propose a new notion of information coverage and investigate its implications for sensor deployment. Numerical and simulation results show that significant savings in terms of sensor density for complete coverage can be achieved by using our definition of information coverage compared to that by using the existing definition.     

Distributed learning in wireless sensor networks

This paper discusses nonparametric distributed learning. After reviewing the classical learning model and highlighting the success of machine learning in centralized settings, the challenges that wireless sensor networks (WSN) pose for distributed learning are discussed, and research aimed at addressing these challenges is surveyed.     

高精确度与高覆盖率的传感器网络定位算法

为了对无线传感器网络中随机分布的节点实施有效定位,针对典型Bounding Box算法的定位准确性与覆盖率较低的不足,提出了一种基于三跳通信环带概念的定位算法C3HR(concentric triple-hop of node communication range).理论分析及仿真结果均表明,该算法优化了对待测节点位置的约束,对于锚节点分布稀疏和不均匀的网络,显著提高了定位的准确性及覆盖率,并能够有效降低节点能耗.     

无线传感器网络的分布式能量有效非均匀成簇算法

研究了现有成簇路由算法,提出了分布式能量有效成簇路由算法,该算法主要包括3部分内容:一是选择候选簇头时通过引入平均能量因子来平衡全网节点的剩余能量情况;二是构造了基于能量和距离的能量消耗率函数以平衡节点的能量效率;三是首次提出了基于同构单跳网络的分布式能量有效非均匀成簇路由算法.理论和仿真结果均说明该算法优于EECS,生命周期比EECS延长达到约30%.