Decentralized Dynamic Coverage Control for Mobile Sensor Networks in a Non‐convex Environment

In this paper, we consider the problem of decentralized dynamic coverage control for mobile sensor networks in an environment with unknown obstacles. The goal is to cover each point in the mission domain but outside the obstacles to a desired level. Each agent is modeled as a point mass based on Newton's law. A decentralized control strategy is developed to accomplish the dynamic coverage task without collision with obstacles. Discrete update of the cooperative coverage is also considered to enhance the cooperation of the agents in the fleet. The collision avoidance and global convergence of the proposed control scheme are proved and illustrated via a simulation example.     

无线传感器监测网络分布式节点调度策略

无线传感器监测网络(WSSN)由数量众多的节点组成.每个节点通过传感器监测外界环境的变化并将监测数据以无线多跳的方式发回基站,实现对用户感兴趣的区域进行监测.WSSN节点的主要特点是电能、带宽、计算和存储能力等高度受限,尤其是其电源的不可替换性导致在保证对监测目标完全监测的同时延长系统工作寿命成为WSSN应用的一个中心问题.提出了WSSN的扩展工作寿命的定义,并在此基础上提出了一种延长WSSN工作寿命的分布式节点调度策略,在各节点簇内对节点进行调度以实现有差别监测服务并延长系统的工作寿命.提出的策略综合考虑节点的当前状态,具有较强的容错性.仿真实验结果表明相对于已提出的方法,该策略有效延长了WSSN的工作寿命.     

移动ZigBee节点无线传感器网络建模与性能仿真研究

在如智慧医疗等众多ZigBee无线传感器网络应用中,网络节点的移动常常不可避免,为保证移动节点在网络中的泛在通讯能力,研究节点移动引起的网络性能变化十分重要。论文首先对OPNET仿真开发平台的网络层进程域模型进行改进,利用状态转移过程模拟节点移动进程特性,优化节点路由协议,改善基于OPNET的ZigBee无线传感器网络模型组网能力及网络阻塞状况。其次,仿真研究移动节点数量、移动节点速度对三种拓扑结构ZigBee网络的MAC负载、MAC延迟、端到端延迟性能的影响。仿真结果表明,随着移动节点数量以及速度的增加,簇状ZigBee网络负载承受能力最好,星型ZigBee网络在延迟方面表现出更大优越性,综合考虑负载和延迟两方面性能,网状ZigBee网络具有更大的优势。     

一种传感器网络移动栅栏部署算法

栅栏覆盖是传感器网络研究中的热点问题,现有有关栅栏覆盖研究大多针对静态兴趣区域的栅栏覆盖,而对于实际应用中如海洋污染、森林火灾、部队行军等的栅栏覆盖应用不适用;该文主要针对动态对象研究移动传感器网络的有效栅栏覆盖;抽象了问题模型并提出了栅栏覆盖评价指标,然后结合凸优化理论提出了一种分布式的移动栅栏覆盖算法;通过3个不同场景分别测试了算法在400*600m的区域中随机部署有50个移动传感器节点对于不同动态对象构建一条封闭栅栏带所花费的时间以及栅栏带动态形成时的移动距离;测试结果算法能够快速有效实现动态区域的栅栏覆盖。     

Cluster Size Optimization in Sensor Networks with Decentralized Cluster-Based Protocols

Network lifetime and energy-efficiency are viewed as the dominating considerations in designing cluster-based communication protocols for wireless sensor networks. This paper analytically provides the optimal cluster size that minimizes the total energy expenditure in such networks, where all sensors communicate data through their elected cluster heads to the base station in a decentralized fashion. LEACH, LEACH-Coverage, and DBS comprise three cluster-based protocols investigated in this paper that do not require any centralized support from a certain node. The analytical outcomes are given in the form of closed-form expressions for various widely-used network configurations. Extensive simulations on different networks are used to confirm the expectations based on the analytical results. To obtain a thorough understanding of the results, cluster number variability problem is identified and inspected from the energy consumption point of view.     

Phenomena Detection in Mobile Wireless Sensor Networks

Environmental phenomena, such as fires, poisonous gases, and oil spills, can be detected by wireless sensor networks (WSNs) that cover the geographical area of the phenomena. These sensors collaboratively monitor the area to detect the sensors’ readings that deviate from normal reading patterns after which a phenomena is declared. This research proposes a distributed algorithm to detect dynamic phenomena using mobile WSNs under the assumption that there is no centralized server to collect and aggregate the sensors data. Therefore, the sensors self-organize into disjoint groups by first electing a few sensors to be group heads (GHs) and then the rest of the sensors group themselves with the nearest GH. Each group of sensors detect phenomena locally. Then, the GHs communicate the detected local phenomena information among themselves to aggregate the information and detect the global phenomena. Moreover, the paper proposes two GH election algorithms, namely the Last Group Head election algorithm and the Distributed Group Head election algorithm. The experimental results show that the proposed election algorithms reduce the energy costs of the mobile WSN by 54–66 % as compared with the straightforward election algorithm. In addition, this paper proposes an optimization technique to further reduce the energy costs of reporting the global phenomena to about 33 % by reducing the size of the reported phenomena information. The proposed algorithms are validated through a comprehensive set of experiments conducted using the NS2 network simulator.     

无线传感器网络中移动节点定位算法研究

提出一种利用临时锚节点的蒙特卡罗箱定位算法.该算法是基于蒙特卡罗定位方法之上,通过引入节点平均速率来获取临时锚节点,并利用一跳范围内的临时锚节点构建最小锚盒、增强样本过滤条件,从而加速了采样和样本过滤.此外,在样本的获取上采用了非随机采样的均衡采样方法,有效地降低了采样次数.仿真结果表明:该算法同蒙特卡罗定位算法等相比,提高了节点的定位精度,降低了节点的能耗.     

无线传感器网络中一种移动节点定位算法

无线传感器网络中现有的大多数定位算法都是针对静态节点的,不能应用于节点移动的情况.本文提出了MCBE(Monte Carlo Localization Boxed Using Estimation)移动定位算法,该算法利用锚盒子(Anchor box),即包含待定位节点可能位置且平行于坐标轴的矩形以及非锚节点位置来帮助定位.锚盒子大小和定位误差存在正相关关系,算法根据待定位节点的一跳和二跳锚节点位置计算出锚盒子大小,当锚盒子大于一定值时,利用锚盒子小的非锚节点位置缩小锚盒子,最后在锚盒子范围内对位置采样,用蒙特卡罗MCL方法定位.理论分析和仿真结果表明,MCBE能有效地缩小采样区域,提高定位精度.     

移动无线传感网的移动感知路径选择算法

为解决稀疏网络环境下移动传感节点的区域全覆盖和数据传输问题,提出一种移动无线传感网的移动感知路径选择算法(MSPS)。在MSPS算法中,用数学公式表示邻居网格集合、区域覆盖率、数据传输时延、节点平均能耗等参数。采用机会路由算法进行数据传输,并建立能保证全覆盖监测区域且权衡数据传输时延、数据传输率和节点平均能耗的移动路径选择优化模型。提出到目标网格的路径寻找方法、初始染色体的确定方法和染色体适应度值计算方法。最终提出修正的多种群遗传算法求解优化模型,获得移动传感节点的最优移动方案。仿真结果表明:不管监测区域内是否存在障碍物,MSPS算法都能提高数据传输率,降低数据传输时延和节点丢弃的总数据量。在一定的条件下,MSPS算法比SGA、TCM_M、RAND_D和RAND算法更优。     

Decentralized Communication-Aware Motion Planning in Mobile Networks: An Information-Gain Approach

In this paper we consider decentralized motion-planning in mobile cooperative networks in the presence of realistic stochastic communication links, including path-loss, fading and shadowing effects. We propose a communication-aware motion-planning strategy, where each node considers the information gained through both its sensing and communication when deciding on its next move. More specifically, we show how each node can predict the information gained through its communications, by online learning of link quality measures such as received Signal to Noise Ratio (SNR) and correlation characteristics, and combine it with the information gained through its sensing in order to build objective functions for motion planning. We show that in the presence of path loss, our proposed strategy can improve the performance drastically. We furthermore show that while uncorrelated low-SNR fading channels can ruin the overall performance, the natural randomization of uncorrelated channels can potentially help the nodes leave deep fade spots with small movements. We finally show that highly correlated deep fades, on the other hand, can degrade the performance drastically for a long period of time. We then propose a randomizing motion-planning strategy that can help the nodes leave highly correlated deep fades.     

无线传感器网络移动Agent的应用

节点计算模式对网络性能影响很大。移动Agent计算模式在下一代网络中具有广阔应用前景。该文分析了移动Agent在无线传感器网络中的应用背景。从网络和节点两个层面提出一种基于移动Agent的传感器网络框架模型,阐述了模型组成、功能定义和交互接口等。给出一种基于定向扩散的移动Agent机制实现方法,并对其特点进行了分析和讨论。     

基于移动传感器网络的节能目标跟踪

首先证明最小化移动传感器网络的目标跟踪能耗是 NP 完全问题, 并基于邻近图理论提出一种近似最优的分布式引导跟随算法. 每一时刻离目标预测位置中心较近的节点引导较远处节点向中心移动, 逐步覆盖目标下一时刻可能在的区域, 整个网络在跟踪全程保持连通. 证明该算法的节点运动能耗在数值上逼近最小能耗. 仿真结果进一步验证了该方案的有效性.     

An Incremental Self-Deployment Algorithm for Mobile Sensor Networks

This paper describes an incremental deployment algorithm for mobile sensor networks. A mobile sensor network is a distributed collection of nodes, each of which has sensing, computation, communication and locomotion capabilities. The algorithm described in this paper will deploy such nodes one-at-a-time into an unknown environment, with each node making use of information gathered by previously deployed nodes to determine its deployment location. The algorithm is designed to maximize network coverage while simultaneously ensuring that nodes retain line-of-sight relationships with one another. This latter constraint arises from the need to localize the nodes in an unknown environment: in our previous work on team localization (A. Howard, M.J. Matari, and G.S. Sukhatme, in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, EPFL, Switzerland, 2002; IEEE Transactions on Robotics and Autonomous Systems, 2002) we have shown how nodes can localize themselves by using other nodes as landmarks. This paper describes the incremental deployment algorithm and presents the results from an extensive series of simulation experiments. These experiments serve to both validate the algorithm and illuminate its empirical properties.     

移动Agent在无线传感器网络中的应用

无线传感器网络是21世纪最为重要的新兴技术之一。为解决数据是被从节点传到处理中心去处理;传感器节点密度高、数量大;节点的电池能量、计算能力存储能力严格受限;网络通信半径小、带宽低等问题,提出采用基于移动A gent的分布式计算模式,设计了一种移动A gent系统,用于实现无线传感器网络的数据融合,系统有效减少网络负载、带宽、时延,实现网络的可扩展性、可靠性和容错性。     

一种基于几何约束的移动无线传感器网络定位算法

在许多无线传感器网络应用中节点定位是至关重要的,现有的节点定位算法大部分都是针对静态传感器网络,移动无线传感器网络的定位研究相对较少。针对定位节点和锚节点移动特性,结合无线传感器网络的特点,提出了一种基于几何约束的非测距定位算法。该算法不需要复杂的计算,也不需要大量的通信,仅仅利用移动锚节点的信息,通过几何约束条件来缩小未知节点所在区域的面积,从而完成定位。仿真实验结果表明,所提出的算法与其它算法相比,能够提高定位精度,有较好的抗干扰性,并且大大减少了能量消耗。     

机会移动传感网中基于感知方向的数据收集

机会移动传感网中数据收集策略既要保证传输成功率、减小网络开销,也要尽量降低传感器的能量消耗,从而延长网络生命期。遵循简单实用的原则,提出了基于方向感知的数据收集策略(Data Gathering based on Perceptive Direction,DGPD)。当两个传感器相遇时,以距离它们最近的Sink节点为参照点,分别计算各自的感知方向。把感知方向作为一个重要参数来确定两个相遇传感器的消息转发路由,把消息转发给更有利于接近Sink节点的传感器,从而提高数据收集成功率,减少过多的消息转发。模拟实验结果表明,这种策略可以有效地完成数据收集,并获得较高的网络性能。     

一种适用于无线传感器网络的移动IPv6协议

在基于IEEE 802.15.4 标准的低功耗无线传感器网络LoWPAN 中,让节点在移动过程中与IP 网络节点保持连续通信是物联网领域的一个重要课题.在现有的移动IPv6 协议(如MIPv6,HMIPv6 等)中,一些用于移动性管理的信令包长度超过了IEEE 802.15.4 MAC 帧的最大载荷,它们被分成多个分片在LoWPAN 中传递,这增大了控制信令包的丢失概率和传递时延.提出一种WoMIPv6(WPAN oriented MIPv6)协议,利用头部压缩技术将移动性管理信令长度压缩到不到60 字节,能够让节点只交换一些简短的信令包即可完成节点的跨子网移动切换.也就是说,WoMIPv6 协议的移动性管理信令不需要分片就可以在单个IEEE 802.15.4 MAC 帧中传递.此外,推导了WoMIPv6 的时延表达式.数值分析结果表明,在信令长度开销和时延方面,WoMIPv6 协议优于HMIPv6 协议.     

移动无线传感器网络基于扩散的时钟同步

研究了移动无线传感器网络中基于扩散的时钟同步方法,针对当前移动无线传感器网络时钟同步速度较慢 的问题,对影响时钟同步性能的要素进行了分析,并做出了两点改进以提高同步速度。通过仿真的方法,说明移动无 线传感器网络的同步运算轮次、网络节点数目、节点通信范围和运动速度都对同步速度有影响,通过改变节点参与同 步运算的概率可以在不增加总计算量的同时提高同步速度。仿真结果证明,与其他同步方法相比,基于扩散的时钟同 步可以充分利用移动无线传感器网络中节点移动的特性,并且改进方法可以进一步提高网络的同步速度。     

无线移动感知网络上的数据聚集传输规划

随着城市交通日益增多,智能交通系统研究受到工业界和学术界的极大关注.智能交通系统上的实时导航、交通监控等应用都需要大量实时车辆速度、位置等信息.由智能车组成的无线移动感知网络的链路变化频繁并且无线干扰严重,现有的车辆网络上的数据聚集算法没有考虑无线链路变化的具体情况,就进行数据聚集和传输的规划.文中分析并求解了移动感知网络上的无冲突数据聚集传输规划问题,将该问题形式化为移动通信拓扑图上的单传聚集传输规划问题,并证明了该问题是NP完全的;提出了移动聚集路由树,将无线冲突分为树内冲突和树间冲突,首先构建树间冲突图描述树间冲突,过滤节点的传输候选时刻集以消除树间冲突,然后利用动态规划思想进行聚集路由树上的数据聚集传输时刻规划来消除树内冲突.并且在真实出租车移动轨迹数据集上进行了实验,实验结果表明文中的算法比现有的算法在数据收集率上提高了1/4左右,并且收集上来的数据的平均延迟也更小.