带移动节点的无线传感器网络时间同步方法

为提高无线传感器网络中节点间时间同步的精度并且降低节点能量消耗,提出了一种基于移动节点与静态节点混合网络的时间同步方法.先建立一个带移动的节点的分簇网络结构,再结合发送者一接受者与改进的发送者一发送者两种同步模型从多个移动节点同时发起同步.通过数学分析和仿真得出该同步方法在同步时间精度和节点节能方面具有良好的性能.     

移动无线传感器网络中一种新的路由算法

在节点采用RWP移动模型的移动无线传感器网络中,为了提高网络的综合性能,提出了一种新的路由算法LDM.LDM运用节点在RWP模型的运动特点及节点的运动方向与当前位置,推导出节点的传输概率,并使用传输概率来指导路由选择,同时对节点的消息队列进行了有效的管理,提高了网络的综合性能.通过在ONE仿真器上与Epidemic、DT、FAD算法进行比较,结果表明LDM在综合性能上得到了提升.     

面向移动汇聚节点的无线传感器网络自适应路由方法

针对无线传感器网络面向移动汇聚节点的自适应路由问题,为实现路由过程中对节点能量以及计算、存储、通信资源的优化利用,并对数据传输时延和投递率等服务质量进行优化,提出一种基于强化学习的自适应路由方法,设计综合的奖赏函数以实现对能量、时延和投递率等多个指标的综合优化。从报文结构、路由初始化、路径选择等方面对路由协议进行详细设计,采用汇聚节点声明以及周期性洪泛机制加速收敛速度,从而支持汇聚节点的快速移动。理论分析表明基于强化学习的路由方法具备收敛快、协议开销低以及存储计算需求小等特点,能够适用于能量和资源受限的传感器节点。在仿真平台中通过性能评估和对比分析验证了所述自适应路由算法的可行性和优越性。     

无线传感器网络中载体的自主移动策略

针对部署在复杂环境中或者不易抵达区域的无线传感器网络(WSN)由于受环境影响,其节点修复、定点投放或搜索救援等环节存在人身安全、不易修复等问题,提出一种WSN中载体的自主移动策略。该策略首先基于少量锚节点,结合最大似然估计算法和接收的信号强度指示(RSSI)定位技术实现移动载体自身定位;然后依靠数学模型,根据当前获取的定位信息及目标节点坐标,完成下一步目标节点的选取和前进角度的修正,以最终实现移动载体的自主移动。仿真结果表明,该策略能够确保载体沿较短路径,在较短时间内到达目的地;且传感器节点密度越大,该策略成功率越高,分别对规模为130、180、300的无线传感器网络进行了仿真,成功率高达96.7%。     

无线传感器网络分布式的移动节点定位研究

针对WSN野外二维特定应用环境,提出了一种到主信标节点信号强度差定位算法（SSDLB）与运动预测定位算法（MPL）相结合的基于分布式的高覆盖率移动WSN节点定位算法,解决了在定位过程中未知节点在某定位时刻其邻居信标节点的个数小于3个的定位问题,并且避免了传统RSSI定位算法把信号强度值转化成距离再进行定位所带来的计算误差与计算开销,一定程度上提高了节点定位精度和覆盖率。仿真实验表明：此算法在较低的信标节点密度的条件下,能够达到较高的定位精度和定位覆盖率,与传统的RSSI算法相比定位性能有显著的提高。     

无线传感网络中移动节点定位技术研究

现有的定位方式因为需要建立网络模型和能量消耗不平均的现象,故不适用于有少量节点随机移动的无线传感网络.针对此类无线传感网络中各节点的定位问题,在分析了定位的计算复杂度和能量损耗的前提下,提出了分簇定位算法,在簇的范围内对发生移动的节点采用接收信号强度测距(RSSI)与质心定位相结合(CLA)的方法进行定位.分析与仿真结...     

Distributed network control for mobile multi-modal wireless sensor networks

A sensor network operates on an infrastructure of sensing, computation, and communication, through which it perceives the evolution of events it observes. We propose a fusion-driven distributed dynamic network controller, called MDSTC, for a multi-modal sensor network that incorporates distributed computation for in-situ assessment, prognosis, and optimal reorganization of constrained resources to achieve high quality multi-modal data fusion. For arbitrarily deployed sensors, a certain level of data quality cannot be guaranteed in sparse regions. MDSTC reallocates resources to sparse regions; reallocation of network resources in this manner is motivated by the fact that an increased density of sensor nodes in a region of interest leads to better quality data and enriches the network resilience. Simulation results in NS-2 show the effectiveness of the proposed MDSTC. ¹     

An efficient trajectory design for mobile sink in a wireless sensor network

Mobile sink trajectory plays a pivotal role for network coverage, data collection and data dissemination in wireless sensor networks. Considering this, we propose a novel approach for mobile sink trajectory in wireless sensor networks. Our proposed approach is based on Hilbert Space Filling Curve, however, the proposed approach is different from the previous work in a sense that the curve order changes according to node density. In this paper, we investigate the mobile sink trajectory based on Hilbert Curve Order which depends upon the size of the network. Second, we calculate the Hilbert Curve Order based on node density to re-dimension the mobile sink trajectory. Finally, we perform extensive simulations to evaluate the effectiveness of proposed approach in terms of network coverage and scalability. Simulation results confirm that our proposed approach outperforms with size based Hilbert Curve in terms of network coverage, packet delivery ratio and average energy consumption.     

一种容迟移动传感器网络的MAC协议

根据容迟移动传感器网络中节点的能量消耗和传输延迟特性,提出一种减少能量消耗的媒体接入控制协议(ESMAC协议)。通过实验证明,依靠在MAC协议的帧结构中加入模式判别标识,减少了节点由于串音和竞争引起的能量消耗;通过节点发送的寻访报文,减少了由于空闲侦听引起的节点能量消耗,延长了网络的生命周期。     

移动无线传感网络节点协同避障的改进方法

传统蜂拥控制模型在协同避障跟踪方面,目前有Reynolds和Tanner的蜂拥模型。笔者曾对其做出了改进,提出了与Steer to Avoid法则相结合的避障模型,该模型在跟踪过程中对凸形障碍有较高的避障效率。由于在Steer to Avoid的方向判断中,目标对节点具有引力,使节点群陷入凹形区域无法绕出。将协同避障模型引入凹形障碍环境中,对模型进一步改进,在Steer to Avoid转向判断时暂时取消目标对节点群的引力,让节点群在进入凹形后自行做出环境的判断并沿着障碍边缘不断搜索路径,最终绕出障碍到达目标。仿真实验结果表明：与传统两个模型相比,该模型在避障的平均速率和时间效率上有显著提高,适用于避开未知的凹形障碍。     

基于移动机器人的无线传感器网络数据收集方法

稀疏无线传感器网络中各传感器节点距离较远,而传统的静态数据收集方法要求各传感器节点直接通信,导致网络延迟时间长,能耗高。针对该问题,提出一种基于移动机器人的无线传感器数据收集方法。该方法首先由静态节点选择与路径最短的移动机器人作为簇头,移动机器人比较一定周期内检测到的邻居节点的平均剩余能量与整个网络传感器节点平均剩余能量,根据比较结果决定其是否移动,若移动则采用范围可控的随机移动策略;当移动机器人移动到新位置时,传感器节点更新路由,选择新的移动机器人作为簇头。仿真结果表明,与传统的静态无线传感器网络数据收集方法相比,基于移动机器人的无线传感器网络数据收集方法大大降低了数据传输延迟和节点能量消耗。     

Monitoring civil structures with a wireless sensor network

Structural health monitoring (SHM) is an active area of research devoted to systems that can autonomously and proactively assess the structural integrity of bridges, buildings, and aerospace vehicles. Recent technological advances promise the eventual ability to cover a large civil structure with low-cost wireless sensors that can continuously monitor a building's structural health, but researchers face several obstacles to reaching this goal, including high data-rate, data-fidelity, and time-synchronization requirements. This article describes two systems the authors recently deployed in real-world structures.     

Simultaneous localization of multiple unknown CSMA-based wireless sensor network nodes using a mobile robot with a directional antenna

We use a single mobile robot equipped with a directional antenna to simultaneously localize unknown carrier sensing multiple access (CSMA)-based wireless sensor network nodes. We assume the robot can only sense radio transmissions at the physical layer. The robot does not know network configuration such as size and protocol. We formulate this new localization problem and propose a particle filter-based localization approach. We combine a CSMA model and a directional antenna model using multiple particle filters. The CSMA model provides network configuration data while the directional antenna model provides inputs for particle filters to update. Based on the particle distribution, we propose a robot motion planning algorithm that assists the robot to efficiently traverse the field to search radio source. The final localization scheme consists of two algorithms: a sensing algorithms that runs in O(n) time for n particles and a motion planning algorithm that runs in O(nl) time for l radio sources. We have implemented the algorithm, and the results show that the algorithms are capable of localizing unknown networked radio sources effectively and robustly.     

基于无线传感器网络的室内移动灭火机器人系统设计

针对室内移动灭火机器人依靠自身传感器无法及时获取全面环境信息和缺少远程网络控制功能的问题,提出了一种基于无线传感器网络（WSN）且具有远程网络控制功能的系统架构。首先,构建网型拓扑结构的无线传感器网络,采集室内环境信息;其次,通过分析系统各部分的逻辑功能,构建数据库和Web服务器,实现远程客户浏览功能;最后,通过开发具有Socket网络通信功能的网络客户端,实现远程网络控制机器人。经实验测试,网型拓扑无线传感器网络,在发送间隔为1.5 s,网关节点无遮挡时,数据传输丢包率为2%,与相同情况下的树型拓扑相比,降低了67%。结果表明此系统架构能获取更加全面的室内环境信息,降低无线传感器网络数据传输丢包率,并能通过网络客户端实现远程控制。     

优化网络生命周期和最短化路径的WSN移动sink路径规划算法

为了缓解无线传感器网络（WSN）中传感器节点分布不均匀、传感器节点感知数据量不同而造成能耗不均衡、"热区"等问题,提出一种优化网络生命周期和最短化路径的WSN移动sink路径规划算法（MSPPA）。首先,通过监测区域网格化,在每个网格内分布若干个移动sink候选访问站点,sink在每个网格中选择一个站点停留收集网格中节点数据;然后,分析所有传感器节点的生命周期与sink站点选择的关系,建立权衡网络生命周期和sink移动路径的优化模型;最后,使用双链遗传算法规划移动sink遍历网格的顺序和选择每个网格中移动sink访问站点,得到移动sink节点遍历所有网格收集数据的路径。仿真结果显示,与已有的低功耗自适应分簇（LEACH）算法与基于移动sink节点与集合节点（RN）的优化LEACH分簇算法（MS-LEACH-RN）相比,MSPPA在网络生命周期方面提高了60%,且具有良好的能耗均衡性。实验结果表明,MSPPA能有效缓解能量不均衡、"热区"问题,延长网络生命周期。     

Using mobile data collectors to improve network lifetime of wireless sensor networks with reliability constraints

In this paper, we focus on maximizing network lifetime of a Wireless Sensor Network (WSN) using mobile Data Collectors (DCs) without compromising on the reliability requirements. We consider a heterogeneous WSN which consists of a large number of sensor nodes, a few DCs, and a static Base Station (BS). The sensor nodes are static and are deployed uniformly in the terrain. The DCs have locomotion capabilities and their movement can be controlled. Each sensor node periodically sends sensed event packets to its nearest DC. The DCs aggregate the event packets received from the sensor nodes and send these aggregate event packets to the static BS. We address the following problem: the DCs should send the aggregate event packets to the BS with a given reliability while avoiding the hotspot regions such that the network lifetime is improved. Reliability is achieved by sending each aggregate event packet via multiple paths to the BS. The network lifetime is maximized by moving the DCs in such a way that the forwarding load is distributed among the sensor nodes. We propose both centralized and distributed approaches for finding a movement strategy of the DCs. We show via simulations that the proposed approaches achieve the required reliability and also maximize the network lifetime compared to the existing approaches.     

一种基于虚拟力的移动传感器网络再部署算法

针对移动传感器网络中,数据的大规模定向传输的实际特性,提出一种基于虚拟力的移动传感器网络节点精确部署算法（VFPDA）。通过引入“中继节点簇”的概念,在源节点到目的节点之间生成多条虚拟“引力线”,这些引力线相互衔接从而构成一条虚拟的通路,然后吸引周围的移动节点向其靠拢,在“引力线”所产生的引力以及节点之间的斥力等作用力的共同作用下,构建一条从源节点到目的节点的通路。实验仿真验证了该算法的有效性。     

管道支持移动传感器网络部署和调度研究综述*

在分析移动传感网络用途的基础上,综述了移动传感网络部署和调度的研究现状,提出了基于管道支持的移动传感器网络部署和调度方法,识别和分析了其当前面临的一组关键挑战,展望和讨论了其未来的发展方向。     

无线传感器网络中移动传感器的再定位技术

回顾了在传感器网络中引入移动传感器的过程。介绍了移动传感器再定位技术可解决传感器网络中的事件深入感知、传感器失效和非精确投放等问题。详细阐述了现有的移动传感器移动至感兴趣区域深入感知、扩大网络覆盖面积和修补网络覆盖洞三类技术。剖析了现有技术中存在的问题。总结分析了主要解决方法和模型,并对未来研究方向进行了展望。