基于局部信息的移动感知网覆盖方法*

移动感知网是一个由许多带有传感器的自主移动机器人组成的分布式传感器网络。为了更好地部署这些移动机器人节点,形成最大化覆盖感知区域,提出了一种基于机器人局部信息的分布式感知网覆盖方法。每个节点利用与邻居节点之间的虚拟人工势场产生的虚拟作用力来控制移动节点的运动和节点间的避碰,使移动节点能够在允许的时间内,以较少的能量消耗移动到各自理想的位置。采用李亚普诺夫函数进行了感知网节点势场梯度的理论分析,用计算机仿真实验验证了该方法的有效性,并与模拟退火算法进行了性能比较。     

概率模型下异构传感器网络部署算法的研究

目前采用虚拟力方法解决传感器节点部署问题的算法均基于同构传感器网络,面向异构传感器网络的部署需求,提出扩展的虚拟力算法.该算法采用概率感知模型,部署时根据感知半径的悬殊采用静态部署与动态部署相结合的策略,根据节点感知半径差异度决定最佳距离的取值,节点移动时采用接替移动法.仿真结果表明该算法能够根据应用需要将异构传感器节点合理地部署于目标区域内,同时能有效地均衡网络节点的能耗,延长网络的生存时间.     

基于感知概率的无线传感器网络节点部署算法

研究无线传感器网络节点部署优化问题,传感器节点的部署在一定程度上决定了无线传感器网络的性能和使用寿命;针对随机部署的无线传感器节点,提出一种基于感知概率模型的节点部署方案;使用证据理论通过计算对节点周围区域的综合感知概率,将虚拟力算法进行改造,使传感器节点向感知概率低的区域移动,实现对监测区域的最大覆盖;仿真结果表明,该部署算法实现节点合理分布,提高网络的覆盖率,减少节点的移动距离,达到延长网络使用寿命的目的。     

基于蜂窝网格锚点的虚拟力导向节点部署算法

为满足覆盖需求,提出了一种基于蜂窝网格锚点的虚拟力导向节点再部署覆盖增强算法;算法基于传感器节点覆盖圆盘与其邻居节点覆盖圆盘的交点构成正六边形蜂窝时,有效覆盖面积最大理论,设置对随机部署的节点虚拟引力锚点作为虚拟力导向移动的目标,建立锚点对节点的虚拟引力,建立节点之间虚拟斥力来避免节点移动中的碰撞问题;完成随机播撒的节点在虚拟力的作用下的再部署,提高覆盖率,保证覆盖质量;Matlab R2012a仿真实验中,随机部署不同数量的节点,网络覆盖率均较快达到95%以上,满足覆盖需求。     

完全覆盖热点区域的多重覆盖算法

针对传感器网络中节点的部署和覆盖问题,提出了一种完全覆盖热点区域的多重覆盖算法。该算法根据网络覆盖质量计算出覆盖某一指定区域所需要的移动节点和静止节点数目。移动节点在虚拟力的作用下到达合适的位置,使得该区域中的热点区域能被完全覆盖,整个区域的节点分布相对比较均匀。仿真实验表明,该算法具有良好的性能,达到了预期的目标。     

基于密集度的虚拟力节点部署算法

针对移动传感器网络节点部署易出现分布不均和能量消耗过高等问题,在传统虚拟力节点部署算法的基础上,提出一种基于密集度的虚拟力节点部署算法,通过对节点所受合力进行分析,推导出具有一定适应性的虚拟力引力参数和斥力参数,同时引入节点密集度的概念,利用节点自身密集度来选择虚拟力模型中最优距离阈值,从而改进传统的虚拟力模型,最终实现网络节点的部署优化.仿真结果表明,在随机部署的情况下,本文提出的算法能够更有效地提高网络覆盖率,减少覆盖漏洞并延长网络的生命周期.     

基于虚拟力和多种群粒子群的覆盖优化HSN节点部署并行算法

针对异构传感器网络中由于节点随机部署而导致覆盖盲区和覆盖冗余的问题,以最大化网络的覆盖率为目标,设计了一种基于虚拟力和多种群粒子群的异构移动节点部署并行算法;首先建立了改进的异构节点概率感知模型和目标优化函数,然后采用虚拟力算法在虚拟力的作用下引导节点移动进行初始部署,为了进一步提高网络的覆盖率和部署的效率,采用改进的多种群粒子群并行算法实现对节点部署的寻优,并定义了具体的部署算法,为了增强网络的鲁棒性,设计了一种当节点失效时的自适应节点替换机制;仿真实验表明:文中方法得到的平均网络覆盖率为95.6%,与其它方法相比,具有较高的网络覆盖率和较少的部署时间,具有较大的优越性。     

DSNs中基于虚拟力的节点部署与目标定位方案

基于分簇的分布式传感器网络的有效性在很大程度上取决于传感器部署所实现的覆盖范围。针对现有的节点部署与目标定位方案的不足,提出一种虚拟力量算法作为传感器部署策略,以便在传感器初始随机部署后提升覆盖范围。给定一定数量的传感器后,该策略通过综合利用引力和斥力来确定传感器在随机部署之后的虚拟移动路径和移动速度,从而使传感器区域覆盖最大化。同时,文中提出一种由簇头运行的概率目标定位算法。簇头只需查询少量传感器(汇报目标存在的部分传感器)即可获得详细定位信息。仿真实验结果表明,本文方案只需一次性计算即可同步确定所有传感器节点的位置,另外,概率定位算法也可显著节约目标检测和定位的能耗。     

三维曲面多移动节点的传感器网络部署算法

目前大多数传感器网络部署研究主要集中在二维平面和三维全空间区域,然而,许多现实世界的应用领域是一个复杂的三维空间曲面,现有的覆盖方法不能取得较好的结果。本文研究三维空间曲面传感器网络部署方法,提出一种三维曲面多移动节点的传感器网络部署算法,采用静态节点和动态节点组成的混合传感器网络,由静态节点估算覆盖空洞的位置和面积,再通过移动节点对覆盖空洞进行依次修复。仿真结果表明,该算法的最终网络覆盖率达到了99%,比3DGA算法提高了6个百分点,比Delaunay算法提高了8.5个百分点,同时降低了网络整体能耗。     

有向异构无线传感器网络节点覆盖率优化算法

针对有向异构节点部署存在覆盖漏洞多、局部部署不均匀等问题,提出一种有向异构传感器网络目标路径覆盖的精确部署算法（DHPSA）。自主部署过程分为两个阶段：首先,节点在邻居节点的虚拟作用力和指定路径虚拟引力的合力作用下实时选择最优路线部署到目标路径;然后,节点在邻居节点的组合虚拟力作用下通过自主旋转和自主移动实现位置的微调,继而实现对目标路径的精确覆盖。通过仿真实验对比分析,所提算法比基于虚拟力的精确部署算法（VFPSA）在覆盖率方面提高约4.4%、重叠率方面下降约3.4%,移动距离方面减少约2.1%及部署时间减少约4.3%。仿真实验结果表明该部署算法更能有效地增大覆盖率,减小重叠率,降低能耗。     

基于静态和移动传感器的WSN的k-覆盖研究

针对无线传感器网络的k-覆盖问题进行了研究。首先定义一个表征网络覆盖效率的过度提供因子,并在此基础上对静态传感器网络和全移动传感器网络的k-覆盖问题进行分析,得到这两种情形下的过度提供因子以及全移动传感器网络中移动传感器的最大移动距离;进而提出一种由静态传感器和少量移动传感器构成的混合网络结构,并得到了这种网络结构下不依赖于网络大小的k-覆盖以及调度移动传感器移动的分布式移动调度算法,从而实现有效覆盖。仿真结果表明,提出的混合网络结构不仅能够实现精确的k-覆盖,而且相比于其他k-覆盖算法,有更高的覆盖率。     

基于虚拟力算法的WMSNs覆盖研究

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。     

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.     

A testbed for coverage control using mixed wireless sensor networks

Wireless sensor networks (WSNs) is a relatively new technology that has been proposed for several applications including wide area monitoring. Such applications may include stationary or mobile sensor platforms or they may include several stationary and some mobile-robotic sensor nodes that can move in the area in order to achieve certain objectives, e.g., monitor areas that are not adequately covered or assist in the transfer of data to prevent the energy depletion of certain critical nodes. Such networks that consist of both stationary and mobile nodes are referred to as mixed WSNs. This paper presents the development of an experimental testbed for mixed WSNs consisting of stationary and mobile sensor nodes that collaborate to improve the sensing coverage and event detection of the network in a given deployment area. The paper describes the hardware and infrastructure of the testbed as well as a case study for coverage control that was investigated using the testbed. We point out that the developed testbed can be used for the evaluation and validation of different algorithms for coverage control that involve collaboration between stationary and mobile sensors to improve the WSN's monitoring capabilities. In addition, it can also be used to investigate other objectives as well as other concepts (e.g., network control).     

Efficient solution techniques for the integrated coverage, sink location and routing problem in wireless sensor networks

Sensors are tiny electronic devices having limited battery energy and capability for sensing, data processing and communicating. They can collectively behave to provide an effective wireless network that monitors a region and transmits the collected information to gateway nodes called sinks. Most of the applications require the operation of the network for long periods of times, which makes the efficient management of the available energy resources an important concern. There are three major issues in the design of sensor networks: sensor deployment or the coverage of the sensing area, sink location, and data routing. In this work, we consider these three design problems within a unified framework and develop two mixed-integer linear programming formulations. They are difficult to solve exactly. However, it is possible to compute good feasible solutions of the sink location and routing problems easily, when the sensors are deployed and their locations in the sensor field become known. Therefore, we propose a tabu search heuristic that tries to identify the best sensor locations satisfying the coverage requirements. The objective value corresponding to each set of sensor locations is calculated by solving the sink location and routing problem. Computational tests carried out on randomly generated test instances indicate that the proposed hybrid approach is both accurate and efficient.     

WSN中基于分布式的覆盖洞修复算法

无线传感器网络(WSN)中存在因节点能量耗尽和移动节点撒播不均而出现的覆盖洞问题,覆盖洞的出现会降低网络的覆盖率和连通性,严重影响网络性能。为解决该问题,构造一种既有静态节点又有移动节点的混合网络模型,并提出一种WSN中基于分布式的覆盖洞修复算法。利用静态节点指导移动节点移动到最优位置,达到修复覆盖洞目的。仿真实验结果证明,该算法能在空洞覆盖率和节点代价之间取得最佳平衡。     

有向移动异构传感网分布式部署策略

针对移动异构有向传感网的覆盖增强问题,提出了一种基于虚拟全向感知圆的节点分布式部署策略DDS（Distrib?uted Deployment Strategy）。DDS采用等面积虚拟全向感知圆替代有向节点感知扇形,根据不同感知圆之间的位置与半径大小关系为每个有向节点合理构建区域覆盖子区间,最后由该子区间多边形的形心确定节点的候选位置坐标。同时,DDS策略充分利用有向节点的旋转特性,计算节点视角方向使其面向检测区域外侧。节点通过视角调整和合理移动,不断提高网络覆盖率。仿真结果表明,DDS在提高网络覆盖率,增强节点分布均衡性方面具有明显的优势。     

移动传感器k栅栏覆盖研究

在随机部署的无线静态传感器网络中,为保证监控区域的栅栏覆盖而需要大量的节点,从而导致节点之间覆盖区域相互重叠,产生覆盖冗余。通过利用移动传感器节点重部署的能力,可以使用少量的节点保证监控区域的栅栏覆盖。针对1栅栏覆盖问题,提出了基于集中式再部署算法CBarrier的改进算法MCBarrier。通过将监控区域划分为若干片段区域,分别进行栅栏覆盖,并设计基于分治算法的k栅栏覆盖构建算法kMCBarrier。实验表明:MCBarrier算法与kMCBarrier算法能量高效的实现栅栏覆盖,且kMCBarrie算法具有良好的扩展性。     

Coverage rate calculation in wireless sensor networks

The deployment of sensors without enough coverage can result in unreliable outputs in wireless sensor networks (WSNs). Thus sensing coverage is one of the most important quality of service factors in WSNs. A useful metric for quantifying the coverage reliability is the coverage rate that is the area covered by sensor nodes in a region of interest. The network sink can be informed about locations of all nodes and calculate the coverage rate centrally. However, this approach creates huge load on the network nodes that had to send their location information to the sink. Thus, a distributed approach is required to calculate the coverage rate. This paper is among the very first to provide a localized approach to calculate the coverage rate. We provide two coverage rate calculation (CRC) protocols, namely distributed exact coverage rate calculation (DECRC) and distributed probabilistic coverage rate calculation (DPCRC). DECRC calculates the coverage rate precisely using the idealized disk graph model. Precise calculation of the coverage rate is a unique property of DECRC compared to similar works that have used the disk graph model. In contrast, DPCRC uses a more realistic model that is probabilistic coverage model to determine an approximate coverage rate. DPCRC is in fact an extended version of DECRC that uses a set of localized techniques to make it a low cost protocol. Simulation results show significant overall performance improvement of CRC protocols compared to related works.