Probabilistic Analysis on Connectivity for Sensor Grids with Unreliable Nodes

This paper mainly investigates the connectivity of the unreliable sensor grid network. We consider an unreliable sensor grid network with mn nodes placed in a certain planar area A, and we assume that each node has independent failure probability p and has the same transmission range R. This paper presents a new method for calculating the connectivity probability of the network, which uses thorough mathematical methods to derive the relationship among the network connectivity probability, the probability that a node is ＂failed＂ （not active）, the numbers of node, and the node＇s transmission range in unreliable sensor networks. Our approach is more useful and efficient for given problem and conditions. Such as the numerical calculating results indicate that, for a 100×100 size sensot network, if node failure probability is bounded 0.5%, even if the transmission range is small （such as R = 10）, we can still maintain very high connectivity probability （reach 95.8%）. On the other hand, the simulation results show that building high connectivity probability is entirely possible on unreliable sensor grid networks.

Enabling Resource Awareness in Integrated Sensor Grid Framework Using Cross Layer Scheduling Mechanism

Researches related to wireless sensor networks primarily concentrate on Routing, Location Services, Data Aggregation and Energy Calculation Methods. Due to the heterogeneity of sensor networks using the web architecture, cross layer mechanism can be implemented for integrating multiple resources. Framework for Sensor Web using the cross layer scheduling mechanisms in the grid environment is proposed in this paper. The resource discovery and the energy efficient data aggregation schemes are used to improvise the effective utilization capability in the Sensor Web. To collaborate with multiple resources environment, the grid computing concept is integrated with sensor web. Resource discovery and the scheduling schemes in the grid architecture are organized using the medium access control protocol. The various cross layer metrics proposed are Memory Awareness, Task Awareness and Energy Awareness. Based on these metrics, the parameters-Node Waiting Status, Used CPU Status, Average System Utilization, Average Utilization per Cluster, Cluster Usage per Hour and Node Energy Status are determined for the integrated heterogeneous WSN with sensor web in Grid Environment. From the comparative analysis, it is shown that sensor grid architecture with middleware framework has better resource awareness than the normal sensor network architectures.

Malicious Node Detection Using Confidence Level Evaluation in a Grid-Based Wireless Sensor Network

In this paper, we present a malicious node detection scheme using confidence-level evaluation in a grid-based wireless sensor network. The sensor field is divided into square grids, where sensor nodes in each grid form a cluster with a cluster head. Each cluster head maintains the confidence levels of its member nodes based on their readings and reflects them in decision-making. Two thresholds are used to distinguish between false alarms due to malicious nodes and events. In addition, the center of an event region is estimated, if necessary, to enhance the event and malicious node detection accuracy. Experimental results show that the scheme can achieve high malicious node detection accuracy without sacrificing normal sensor nodes.

A Path-Based Approach for Data Aggregation in Grid-Based Wireless Sensor Networks

Sensor nodes in a wireless sensor network （WSN） are typically powered by batteries, thus the energy is constrained. It is our design goal to efficiently utilize the energy of each sensor node to extend its lifetime, so as to prolong the lifetime of the whole WSN. In this paper, we propose a path-based data aggregation scheme （PBDAS） for grid-based wireless sensor networks. In order to extend the lifetime of a WSN, we construct a grid infrastructure by partitioning the whole sensor field into a grid of cells. Each cell has a head responsible for aggregating its own data with the data sensed by the others in the same cell and then transmitting out. In order to efficiently and rapidly transmit the data to the base station （BS）, we link each cell head to form a chain. Each cell head on the chain takes turn becoming the chain leader responsible for transmitting data to the BS. Aggregated data moves from head to head along the chain, and finally the chain leader transmits to the BS. In PBDAS, only the cell heads need to transmit data toward the BS. Therefore, the data transmissions to the BS substantially decrease. Besides, the cell heads and chain leader are designated in turn according to the energy level so that the energy depletion of nodes is evenly distributed. Simulation results show that the proposed PBDAS extends the lifetime of sensor nodes, so as to make the lifetime of the whole network longer.

Grid-based directed diffusion for wireless sensor networks

Directed diffusion is a data dissemination protocol for wireless sensor networks.In directed diffu-sion,flooding is used for dissemination of interest and exploratory data,which will bring broadcast stormresulting in substantial energy consumption of networks.A grid-based directed diffusion is presented toimprove the energy efficiency of directed diffusion.Virtual geographic grid clusters are constructed byself-organization of nodes using geographic location information.The flooding of interest and exploratorydata of original directed diffusion is limited in cluster head nodes.The simulation results and testhed ex-periments show that the method effectively reduces the network energy consumption.This gain is notachieved at the cost of either delivery ratio or the delay.Importantly,the decreased load also leads to abetter delivery ratio and lower delay.

基于环境中移动运输代理的传感器网络建模

针对大型稀疏传感器网络中的数据获取,本文提出了一种利用环境中普遍存在的移动代理来连接稀疏传感器的网络体系结构和一种2-维网格随机游走分析模型;提出的传感器网络模型由3个抽象层构成,即由无线传感器构成的底层、由各种运输代理构成的中间层和由接入点/中央存储库构成的顶层。具体实现原理是位于中间层的移动运输代理从底层分布的无线传感器收集数据并缓冲数据,然后经过游走运输,最后将从底层的无线传感器收集的数据交付到顶层必要的接入点进行必要的存储和处理,从而实现整个传感器网络的数据获取;理论分析和仿真实验结果表明,提出的基于移动运输代理的传感器网络模型不仅具有较好的鲁棒性和可扩展性,而且相比于基站网络模型和Ad-hoc网络模型,在传感器功率消耗、数据成功率和基础设施投入成本方面有明显的优势。

A Void Avoidance Scheme for Grid-Based Multipath Routing in Underwater Wireless Sensor Networks

This work proposes a geographic routing protocol for UWSNs based on the construction of a 3D virtual grid structure, called Void-Avoidance Grid-based Multipath Position-based Routing (VA-GMPR). It consists of two main components, the multipath routing scheme and the grid-based void avoidance (GVA) mechanism for handling routing holes. The multipath routing scheme adopts node-disjoint routes from the source to the sink in order to enhance network reliability and load balancing. While the GVA mechanism handles the problem of holes in 3D virtual grid structure based on three techniques: Hole bypass, path diversion, and path backtracking. The performance evaluation of the VA-GMPR protocol was compared to a recently proposed grid-based routing protocol for UWSNs, called Energy-efficient Multipath Geographic Grid-based Routing (EMGGR). The results showed that the VA-GMPR protocol outperformed the EMGGR protocol in terms of packet delivery ratio, and end-to end-delay. However, the results also showed that the VA-GMPR protocol exhibited higher energy consumption compared to EMGGR.

面向智能电网广域通信的可靠路由算法研究

无线传感器网络是智能电网广域通信中的基础组成单元,传统的无线传感器网络分簇路由协议虽能在一定程度上简化网络拓扑,但仍存在簇首选择不合理且系统能耗较高的问题。针对此,文中基于粒子群优化算法提出了一种改进的分簇路由协议。该协议利用粒子群算法的参数寻优特性对簇首搜寻方案加以改进,使得新方案考虑了距离、剩余能量、数据传输精度等多种因素。同时还使用粒子群自适应函数对该方案进行优化,从而提高了原算法的可靠性。在能耗实验测试中,所提算法迭代1 300次后的剩余能耗为31.2 J,在对比算法中为最优。而对路由路径的测试中,改进算法的平均运行时延为1.79 ms,平均误码率为0.212 5,在所有算法中均为最低,证明了该算法具有良好的实时性和可靠性。

Multipath Grid-Based Enabled Geographic Routing for Wireless Sensor Networks

This work proposes an efficient disjoint multipath geographic routing algorithm for dense wireless sensor networks (WSN), called Multipath Grid-based Enabled Geographic Routing (MGEGR). The proposed algorithm relies on the construction of a 2-D logical grid in the geographical region of deployment. The objective of the proposed scheme is to determine optimal or near-optimal (within a defined constant) multiple disjoint paths (multipath) from a source node to the sink, in order to enhance the reliability of the network. The determined multiple disjoint paths would be used by the source node in a round-robin way to balance the traffic across the disjoint paths, and to avoid discovered paths with cell holes. The proposed scheme limits the use of broadcasting to the process of gateway election within each cell, and the process of maintaining the table of neighbors of each gateway. Our simulation results show the effectiveness and scalability of our routing scheme with increased network size compared to on-demand routing protocols.

基于无网压传感器控制的单相并网逆变器预同步控制策略

针对无网压传感器控制在换流器与电网同步瞬间,可能导致冲击电流过大进而并网失败的问题,提出一种预同步控制策略,在保证跟网型变流器在弱电网下稳定性的前提下,实现基于无网压传感器控制的单相并网逆变器与电网平滑可靠并网。该控制策略通过对开关管施加占空比满足一定约束条件的周期性脉冲,使换流器作为逆变器连接到交流电网之前以单位功率因数运行在整流模式。因此,交流电网的初始相位可通过采样电流来估计,其中电流相位可通过锁相环(Phase⁃Locked Loop,PLL)获取。所提控制器策略无需采集公共耦合点(Point of Common Coupling,PCC)电压,即可实现换流器与电网平滑可靠并网。最后通过半实物实验测试,验证了所提控制策略的有效性。

AGQ-MAC:无线传感器网络中基于Grid Quorum的异步低占空比MAC协议

针对无线传感器网络占空比MAC协议在链路或节点失效环境下易导致严重的能量浪费问题,提出了一种基于Grid Quorum的异步低占空比M AC协议-AGQ-M AC(Asynchronous Grid Quorum M AC).AGQ-M AC采用Grid Quorum组分配信道,通过动态调配Quorum比率得到了节点的最优占空比,并在邻节点发现过程中采用双前导序文抽样来监测信道状态,以减少节点唤醒时间从而达到能量高效.仿真实验结果表明,与其他占空比MAC协议相比,AGQ-MAC延长了网络生存时间,降低了网络能耗,提高了邻发现数据传输率,同时保持较低的平均邻发现延迟.

Grid-Scan算法定位精度和定位率的改进

针对Grid-Scan算法定位率及定位精度较低的问题,提出了一种基于虚拟锚节点的Grid-Scan定位算法。具体做了3个方面的工作:有邻居锚节点的未知节点只利用邻居锚节点进行定位,定位后的节点升级为虚拟锚节点;没有邻居锚节点的未知节点利用虚拟锚节点完成定位;锚节点及虚拟锚节点与未知节点采用不同的通信半径进行扫描并完成定位。仿真结果表明,相比传统算法,改进算法的定位精度和定位率分别平均提高了约6.35%和23.37%。

一种结合角距特征的改进栅格星图识别算法

针对栅格算法易受邻域星点影响导致误匹配的问题,提出了一种结合角距特征的改进栅格星图识别算法。首先介绍了改进栅格算法的原理,其次设计了融合栅格识别模式和星角距识别模式的算法实现流程,最后开展了基于不同视角下的大视场仿真星图的算法试验验证和性能分析。结果表明,由于角距特征具有旋转不变性和不易受观测星邻域星点分布影响等特点,结合角距特征对失效观测星进行再匹配的改进栅格算法,在兼顾存储量需求小、运行速度快等优势的同时,识别率和鲁棒性也得到了提升,最高识别率可达98.88%,在位置噪声干扰以及缺失星干扰下,改进算法的识别率仍可保持在95%,说明算法鲁棒性强,具有较好的应用前景。

Grid-Scan定位算法的虚拟锚节点策略改进

针对无线传感器网络中Grid-Scan算法定位精度较低的问题,提出了一种基于虚拟锚节点策略的Grid-Scan定位算法。具体做了三个方面的工作:对未知节点设置可定位阈值,邻居锚节点数大于可定位阈值的未知节点使用Grid-Scan算法进行定位,定位后的节点升级为虚拟锚节点;邻居锚节点数小于可定位阈值的未知节点利用极大似然法完成定位,定位后的节点升级为虚拟锚节点;锚节点及虚拟锚节点共同参与对剩余未知节点的定位。仿真结果表明,改进算法在不同锚节点密度、不同通信半径和不同栅格大小的网络中以及通过不规则传播模型后都具有较好的定位精度。

基于Grid-VFACO的数字化车间WSNs路由算法

针对数字化车间中无线传感器网络(WSNs)对数据采集频率高,能量消耗快,提出了基于网格和虚拟力导向的蚁群优化(Grid-VFACO)高能效WSNs路由算法。该算法根据最优簇首数将数据采集区划分成网格,在网格中采用基于候选者的机制选择簇首,实现簇首均匀分布。在簇首形成的上层网络中,利用节点间的虚拟吸引力作为蚁群算法中转移概率规则启发因子,寻找最优数据转发路径。仿真实验结果表明:该算法能够有效减少网络能耗,保证数字化车间WSNs长时间稳定地工作。

高精度磁栅式隧道磁阻微位移传感器

利用隧道磁阻(TMR)效应设计了一种结构相对简单的磁栅式高精度微位移传感器。首先,介绍了磁栅式隧道磁阻位移传感器检测原理,凭借隧道磁阻传感器高灵敏度的特点检测磁栅敏感轴上方的空间磁场,接着利用COMSOL有限元仿真软件对磁栅结构进行仿真设计,验证了磁栅的磁场分布特性。通过搭建四桥路检测电路能够使TMR传感器有效抑制外部磁场干扰以及温度对TMR传感器的影响;得益于90°移相电路模块的加入,得到两路相位相差90°的标准正余弦信号,解决了传统的由于空间非正交引起的相位和幅值等误差问题,为超高倍数的细分插值技术奠定了基础,最后结合细分因子为9600的插值电路,理论上可实现208 nm的高分辨率位移检测,在20 mm量程范围内能达到0.15%的位移测量精度。

从PF和DPGrid的发展谈数字摄影测量发展的新特征

结合目前国内外新一代摄影测量处理系统的发展现状,从主要特点、功能组成、工艺流程、产品体系、关键技术等共性方面,深入分析和总结了新一代摄影测量处理系统的基本特征;同时指出了今后数字摄影测量处理系统的发展重点和方向。