一种无线传感器网络覆盖度确定算法

覆盖度能充分反映传感器节点对目标监视区域的覆盖情况,是无线传感器网络QOS标准之一.在实际应用中无线传感器网络节点通常是高密度随机放置的,如何确定覆盖度是提高网络性能和生存期需要解决的关键问题.通过引入节点"覆盖模板"的概念,提出一种覆盖模板扫描 (Coverage Template Scan,CTS)确定传感器节点在目标区域的覆盖度.CTS算法充分考虑可变节点感知半径以及节点覆盖圆边界效应的影响,能更好地满足实际应用需求.仿真表明,CTS算法的性能在时间复杂性上明显优于已有的传统贪婪算法.     

异构无线传感器网络中覆盖度和连通度的研究

覆盖度和连通度研究是无线传感器网络中的关键问题。以往研究背景为同构无线传感器网络,这样可以简化问题,但随着问题的深入,不得不考虑异构节点覆盖。系统地对异构无线传感器网络进行了分类,提出了感知异构和通信异构结合的无线传感器网络下的异构节点感知模型,其次分析了两类异构节点之间的覆盖度的计算,最后分析了异构网络的单连通和重连通。此外实现了大量的仿真实验,得出了节点数量和单连通、重连通的概率曲线。     

半径可调的无线传感器网络三维覆盖算法

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。     

无线传感器网络中覆盖控制技术综述

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。     

无线传感器网络一维区域的覆盖研究*

无线传感器网络覆盖问题的研究应综合考虑感知覆盖、通信覆盖和连通覆盖三个方面,建立适合不同监测空间的节点覆盖模型。讨论了无线传感器网络一维区域的覆盖问题,对无线传感器网络中一维直线区域出现的问题进行分析,讨论了均匀分布情况下的节点覆盖概率和覆盖数的计算方法,仿真实验表明节点感知半径是影响节点覆盖率和覆盖数的主要因素。     

无线传感器网络中基于虚拟力的覆盖算法

在无线传感器网络的很多应用场景中,大量的传感器节点被任意播撒在被监测区域内,形成很多覆盖空洞,对无线传感网络的感知、监测和数据采集能力造成很大影响。为了解决无线传感器网络中的覆盖问题,提出了一种基于虚拟引力的覆盖算法。首先,根据虚拟引力产生的约束条件和引力大小,一种扩大网络覆盖范围的算法被提出,算法分析证明这种算法能够减少覆盖空洞;第二,提出了维持邻居节点连通性的方法;第三,提出一种覆盖感兴趣区域的算法。仿真结果表明,这种算法既能提高网络的覆盖能力,又能减少传感器节点的移动距离。     

WSN中多重目标覆盖度和连通度的研究

覆盖度和连通度是无线传感器网络中密不可分的关键性研究问题。求解覆盖度和连通度问题的传统方法之一为整数规划算法,其研究背景为同构无线传感器网络和单覆盖度。该方法在实际的高精度目标检测中已不能满足要求。建立了一种随机生成的网络模型并对其进行模型抽象。此外实现了大量的仿真实验,得出了多重覆盖感知概率与节点数量的关系和单连通、重连通的概率曲线,可以为节点的布置提供参考价值。     

无线传感器网络概率覆盖控制研究*

在无线传感器网络中进行覆盖控制能有效缓解无线传感器网络中节点能量受限的问题,通常采用的是基于二元感知模型的几何方法计算休眠冗余节点,其算法在实际应用中受到局限,不够精确。针对此问题,将提高能量利用效率作为重要指标,采用概率感知模型,提出一种新的覆盖控制算法(PSMC)。仿真结果表明,PSMC算法在较好地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。     

无线传感器网络中覆盖控制理论与算法

覆盖控制作为无线传感器网络中的一个基本问题,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,分类总结了近年来提出的各种覆盖控制问题的思想和有代表性的研究成果,着重讨论了一些典型的无线传感器网络覆盖控制算法与协议.最后进行了各种算法的比较性总结,深入分析了目前无线传感器网络覆盖控制亟待解决的问题,并展望了其未来的发展方向.     

一种无线传感器网络覆盖能耗平衡优化策略

在无线传感器网络中,对目标区域的覆盖程度以及网络能耗是衡量其性能的重要指标,通过对节点的合理配置,有利于保证网络覆盖,平衡网络能耗。针对节点感知距离可调的无线传感器网络,提出了一种无线传感器网络覆盖能耗平衡优化策略,该策略以满足一定的网络区域覆盖质量为前提,以覆盖能耗平衡为优化目标,采用粒子群算法,首先对网络中的节点布局进行动态优化,在此基础上通过合理调整节点感知距离,使得网络覆盖能耗性能最优。仿真结果表明,与传统节能覆盖方案相比,该策略能够有效减少感知重叠区和感知盲区,提高网络区域覆盖质量,降低网络能耗。     

A simple coverage-evaluating approach for wireless sensor networks with arbitrary sensing areas

We present a simple and fast deterministic solution to the area coverage problem in wireless sensor networks. The task is to determine whether all points in a region are covered by a given set of sensors, where each sensor may have any arbitrary sensing shape. We transform the area coverage problem to the intersection points' coverage problem, which is simpler and more suitable for evaluating the area coverage problem than previous approaches in our view.     

基于改进势场的有向传感器网络路径覆盖增强算法

路径覆盖是无线传感器网络目标监控领域的一个热点研究问题,在分析节点主感知方向可调模型的基础上,提出了一种基于改进势场的有向传感器网络路径覆盖增强算法(improved potential field based path coverage-enhancing algorithm,IPFPCA).该算法针对传统虚拟势场可能出现的局部极小导致覆盖增强失败问题设计了一种改进的势场函数,通过将相邻传感器节点对路径轨迹点的共同覆盖率引入到斥力计算中,有效引导节点的主感知方向调整,从而达到路径的高效覆盖.实验结果表明:对比已有的路径覆盖增强算法,IPFPCA可以消除节点的感知重叠区和盲区,最终实现网络路径的高效覆盖.     

混合传感器网络节点布设优化算法

针对无线传感器网络中节点在随机部署环境下执行“休眠”策略出现的区域覆盖“收缩”现象,结合网络中的边界效应问题,对覆盖边界区域进行针对性几何划分,提出一种边界区域部署调整的混合传感网节点布设优化算法。通过对划分的边界区域进行少量移动节点补充,达到节点调度过程中的能耗均衡,实现延长网络生存时间的目的。算法与随机部署、随机补充两种方法进行了优化效果对比,仿真结果表明,该方法对提高网络整体生存时长具有明显的改善作用,适用于随机部署状态下的无线传感器网络环境。     

A learning automata based scheduling solution to the dynamic point coverage problem in wireless sensor networks

The dynamic point coverage problem in wireless sensor networks is to detect some moving target points in the area of the network using as few sensor nodes as possible. One way to deal with this problem is to schedule sensor nodes in such a way that a node is activated only at the times a target point is in its sensing region. In this paper we propose SALA, a scheduling algorithm based on learning automata, to deal with the problem of dynamic point coverage. In SALA each node in the network is equipped with a set of learning automata. The learning automata residing in each node try to learn the maximum sleep duration for the node in such a way that the detection rate of target points by the node does not degrade dramatically. This is done using the information obtained about the movement patterns of target points while passing throughout the sensing region of the nodes. We consider two types of target points; events and moving objects. Events are assumed to occur periodically or based on a Poisson distribution and moving objects are assumed to have a static movement path which is repeated periodically with a randomly selected velocity. In order to show the performance of SALA, some experiments have been conducted. The experimental results show that SALA outperforms the existing methods such as LEACH, GAF, PEAS and PW in terms of energy consumption.     

无线传感器网络密度控制研究

无线传感器网络节点能量受限,部署环境恶劣、复杂。在监测区域内部署大量节点,通过节点之间的状态轮换与合作策略延长网络寿命是非常重要的方法。本文论述了设计密度控制算法状态转移条件需要解决的两个基本问题：区域覆盖问题和节点连通性优化问题,并分别以ILP的形式给出了一个集中式算法解决方案。通过节点的覆盖效用范围与连通性效用范围的几何分析,提出了传感器网络密度控制算法中解决两个基本问题的一致性策略。     

A grid-based coverage approach for target tracking in hybrid sensor networks

Most existing work on the coverage problem of wireless sensor networks focuses on improving the coverage of the whole sensing field. In target tracking, the interested coverage area is the emerging region of a motorized target, not the whole sensing field. As the motorized target moves, the emerging region is also dynamically changed. In this paper, we propose a grid-based and distributed approach for providing large coverage for a motorized target in a hybrid sensor network. The large coverage is achieved by moving mobile sensor nodes in the network. To minimize total movement cost, the proposed approach needs to solve the following problems: the minimum number of mobile sensor nodes used for healing coverage holes and the best matching between mobile sensor nodes and coverage holes. In the proposed approach, the above two problems are first transformed into the modified circle covering and minimum cost flow problems, respectively. Then, two polynomial-time algorithms are presented to efficiently solve these two modified graph problems, respectively. Finally, we perform simulation experiments to show the effectiveness of proposed approach in providing the coverage for a motorized target in a hybrid sensor network.     

Coverage area enhancement in wireless sensor network

In the wireless sensor network, coverage area may be enhanced after an initial deployment of sensors. Though, some research works propose how to decrease the coverage hole by increasing sensing range or movement assisted sensor deployment, these are not suitable for energy constraint wireless sensor network, as longer mobility distance or higher power level consume more energy. In this paper, we address the increasing coverage area through smaller mobility of nodes. We find out the coverage hole in the monitoring region, which is not covering by any sensing disk of sensor. Then, we address the new position of mobility nodes to increase the coverage area. The simulation result shows the mobile nodes can recover the coverage hole perfectly. The coverage holes is recovered by mobility on the existing recovery area, which cannot be lost. Moreover, hole detection time in our proposed protocol is better than existing algorithm.

     

A novel knowledge-guided evolutionary scheduling strategy for energy-efficient connected coverage optimization in WSNs

One of the most important challenges in designing wireless sensor network is how to construct full-connected network containing least active sensor nodes with satisfied quality of services, such as the coverage rate and energy consumption. This energy-efficiency full-connected coverage optimization problem is modeled as a single-objective optimization problem with constraint. To solve this problem, a knowledge-guided evolutionary scheduling strategy is proposed. Three highlights of this strategy are: (1) Knowledge is defined as the importance of sensor node, which depends on the distance between sensor node and sink node. (2) The genes of an individual correspond to senor nodes in descending order of their importance. (3) Considering sensor nodes’ importance and redundancy rate, knowledge-guided mutation operator and repair strategy are present. Simulation results show that the proposed method can find the optimal full-connected wireless sensor network containing least sensor nodes and consuming less energy for communication by less computation time. Though the coverage rate of the optimum is larger, it still satisfies the coverage constraint. Moreover, this strategy fits for the problems that the communication radius of sensor node is less than two times of its sensing radius.     

综合覆盖调度的无线传感器网络跨层路由研究

无线传感器网络由大量微小的传感器节点构成,各节点协作完成环境现象的分布式感知。覆盖控制作为无线传感器网络中的一个基本问题,反映了网络所能提供的"感知"服务质量。基于现有的集中式计算覆盖集合算法MLMC,通过改变计算覆盖集合条件,结合能量不均衡消耗的I-RDDD协议,观察了网络生存期的变化。仿真结果和分析表明,基于能量考虑和单组覆盖集合轮询的工作方式能获得更长的网络生存期。