Efficient terrain coverage for deploying wireless sensor nodes on multi-robot system

Coverage and connectivity are the two main functionalities of wireless sensor network. Stochastic node deployment or random deployment almost always cause hole in sensing coverage and cause redundant nodes in area. In the other hand precise deployment of nodes in large area is very time consuming and even impossible in hazardous environment. One of solution for this problem is using mobile robots with concern on exploration algorithm for mobile robot. In this work an autonomous deployment method for wireless sensor nodes is proposed via multi-robot system which robots are considered as node carrier. Developing an exploration algorithm based on spanning tree is the main contribution and this exploration algorithm is performing fast localization of sensor nodes in energy efficient manner. Employing multi-robot system and path planning with spanning tree algorithm is a strategy for speeding up sensor nodes deployment. A novel improvement of this technique in deployment of nodes is having obstacle avoidance mechanism without concern on shape and size of obstacle. The results show using spanning tree exploration along with multi-robot system helps to have fast deployment behind efficiency in energy.     

基于萤火虫群优化算法的无线传感器节点部署

为了提高传感器节点部署覆盖率,针对目前网络覆盖存在覆盖死角、节点冗余及不能再度优化的问题,在检测区域已知的情况下,提出基于萤火虫群优化(GSO)算法的传感器节点部署方案,并对原方案进行改进。该算法中,传感器节点等同于萤火虫,覆盖信号强度即是荧光素浓度,首先对节点进行随意初始部署,然后通过计算移动概率的大小,判断节点移动方向,最终完成节点部署。实验仿真表明,该部署方法适用于大量传感器节点部署,覆盖面积广,灵活性强。     

无线传感器网络基于路径的非均匀分布策略

无线传感器网络中多对一的数据传输方式导致节点负载的不均衡性,靠近汇聚节点(Sink)的节点要比远离Sink的节点消耗更多的能量,如此容易引发能量空洞问题。针对该问题,从网络数据的传递路径出发,根据网络中节点承担的路径数量的不同,平衡各层节点的能耗,提出感知节点覆盖率一致、内层路由节点与其所有外层感知节点数目相同的的非均匀分布策略,并通过仿真实验证明了该方法的有效性。     

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 cellular learning automata-based deployment strategy for mobile wireless sensor networks

One important problem which may arise in designing a deployment strategy for a wireless sensor network is how to deploy a specific number of sensor nodes throughout an unknown network area so that the covered section of the area is maximized. In a mobile sensor network, this problem can be addressed by first deploying sensor nodes randomly in some initial positions within the area of the network, and then letting sensor nodes to move around and find their best positions according to the positions of their neighboring nodes. The problem becomes more complicated if sensor nodes have no information about their positions or even their relative distances to each other. In this paper, we propose a cellular learning automata-based deployment strategy which guides the movements of sensor nodes within the area of the network without any sensor to know its position or its relative distance to other sensors. In the proposed algorithm, the learning automaton in each node in cooperation with the learning automata in the neighboring nodes controls the movements of the node in order to attain high coverage. Experimental results have shown that in noise-free environments, the proposed algorithm can compete with the existing algorithms such as PF, DSSA, IDCA, and VEC in terms of network coverage. It has also been shown that in noisy environments, where utilized location estimation techniques such as GPS-based devices and localization algorithms experience inaccuracies in their measurements, or the movements of sensor nodes are not perfect and follow a probabilistic motion model, the proposed algorithm outperforms the existing algorithms in terms of network coverage.     

Multi-objective optimization for coverage control in wireless sensor network with adjustable sensing radius

In this paper, the problem of maintaining sensing coverage by keeping a small number of active sensor nodes and a small amount of energy consumption in a wireless sensor network is studied. As opposed to the uniform sensing model previously, we consider a large number of sensors with adjustable sensing radius that are randomly deployed to monitor a target area. A novel coverage control scheme based on elitist non-dominated sorting genetic algorithm (NSGA-II) is proposed in a heterogeneous sensor network. By devising a cluster-based architecture, the algorithm is applied in a distributed way. Furthermore, an ameliorated binary coding is addressed to represent both sensing radius adjustment and sensor selection. Numerical and simulation results validate that the procedure to find the optimal balance point among the maximum coverage rate, the least energy consumption, as well as the minimum number of active nodes is fast and effective.     

基于虚拟力的混合感知网节点部署

感知网一般是由静态的或移动的节点组成,为保证感知网的感知功能,节点应该有自部署和自修复能力.然而全部由移动传感器组成的感知网的成本太高,为保证感知网的覆盖功能和低成本,提出了一种在静态传感器节点中加入移动传感器节点的混合感知网形式.为了更好地部署这些节点,最大化覆盖待感知区域,提出了一种基于节点间虚拟力的移动节点部署方法,利用静态节点和移动节点以及移动节点之间的虚拟人工势场产生的作用力来控制移动节点的运动,使移动节点能够在较短的时间内,以较少的能量消耗到达自己合适的位置.在理论上分析了算法的可行性,用仿真实验验证了此算法的有效性,并和其他3种类似算法进行了性能比较.     

一种连通性覆盖的无线传感器网络节点调度算法

研究传感器节点随机部署于监测区域内,无节点地理位置信息情况下,如何能量有效地保证网络的通信连通与感知覆盖;节点采用基于概率的联合感知模型。提出CDS-based SSCA算法,其为一种基于连通支配集构造树的节点调度机制,每个节点根据剩余能量和与父节点的距离来设置等待时间及成为候选节点优先级。模拟实验结果显示,本算法能够能量有效地满足感知覆盖和连通覆盖要求;与ASW算法相比较,工作节点个数较少,网络生命周期明显延长,降低了网络整体耗能。     

网格法在无线传感器网络部署中的应用

传感器节点的数量关系到无线传感器网络的总成本和网络的性能,是设计无线传感器网络优先考虑的问题。对无线传感器网络部署中重点考虑的覆盖、连通性和节能问题进行了讨论,基于网格法对几种不同的传感器部署方案进行分析,计算了它们的有效覆盖面积和有效覆盖率。通过计算和分析可知,传感器按等边三角形部署时,重叠区域小,需要的传感器数量少,是最理想的部署策略。     

A key predistribution scheme for sensor networks using deployment knowledge

To achieve security in wireless sensor networks, it is important to be able to encrypt messages sent among sensor nodes. Keys for encryption purposes must be agreed upon by communicating nodes. Due to resource constraints, achieving such key agreement in wireless sensor networks is nontrivial. Many key agreement schemes used in general networks, such as Diffie-Hellman and public-key-based schemes, are not suitable for wireless sensor networks. Predistribution of secret keys for all pairs of nodes is not viable due to the large amount of memory used when the network size is large. Recently, a random key predistribution scheme and its improvements have been proposed. A common assumption made by these random key predistribution schemes is that no deployment knowledge is available. Noticing that, in many practical scenarios, certain deployment knowledge may be available a priori, we propose a novel random key predistribution scheme that exploits deployment knowledge and avoids unnecessary key assignments. We show that the performance (including connectivity, memory usage, and network resilience against node capture) of sensor networks can be substantially improved with the use of our proposed scheme. The scheme and its detailed performance evaluation are presented in this paper.     

矩形截面矿井巷道三维WSN覆盖机理

无线传感器节点在矿井巷道内壁上多采用径向直线型和径向V字型部署。针对矩形截面矿井巷道的无线传感器节点如何在三维空间实现单重无缝覆盖的问题,通过分析巷道几何尺寸,推导出其节点在两种部署类型中的最小感知半径;进一步推导出其节点覆盖密度与节点感知半径、巷道高度、巷道宽度之间的函数关系,比较两种部署类型节点覆盖密度,为现实运用选择节点部署方式提供有力依据。仿真实验验证了推导结果的正确性。利用推导的结论结合矿井的几何尺寸,可直接计算出节点必须满足的最小感知半径、部署方法、部署位置和覆盖密度,从而提高节点覆盖的有效性,减少工程成本支出。     

A smart node architecture for adding mobility to wireless sensor networks

Adding a few mobile nodes into the conventional wireless sensor networks can greatly improve the sensing and control capabilities of the networks and can help researchers solve many challenges such as network deployment and repair. This paper presents an enhanced node architecture for adding controlled mobility to wireless sensor networks. The structural model, the power model and the networking model of the proposed mobile node have been built respectively for better node control. And it provides a novel robotic platform for experimental research in hybrid sensor networks or other distributed measurement and control systems. A testbed has finally been created for validating the basic functions of the proposed mobile sensor node. The results of a coverage experiment show that the mobile node can provide additional support for network coverage and can ensure that the sensor network will work properly in undesirable environments.     

A Delaunay Triangulation based method for wireless sensor network deployment

To obtain a satisfied performance of wireless sensor network, an adaptable sensor deployment method for various applications is essential. In this paper, we propose a centralized and deterministic sensor deployment method, DT-Score (Delaunay Triangulation-Score), aims to maximize the coverage of a given sensing area with obstacles. The DT-Score consists of two phases. In the first phase, we use a contour-based deployment to eliminate the coverage holes near the boundary of sensing area and obstacles. In the second phase, a deployment method based on the Delaunay Triangulation is applied for the uncovered regions. Before deploying a sensor, each candidate position generated from the current sensor configuration is scored by a probabilistic sensor detection model. A new sensor is placed to the position with the most coverage gains. According to the simulation results, DT-Score can reach higher coverage than grid-based and random deployment methods with the increasing of deployable sensors.     

一种基于六边形部署模型的面向传感器网络的随机密钥预分配方案

针对基本随机密钥预分配方案和基于部署信息的密钥管理方案中存在的不足,提出了一种基于六边形部署模型的面向传感器网络的随机密钥预分配方案。该方案更充分地利用了六边形部署模型的特点,通过将部署区域划分为六边形网格,并将传感器节点按其标志号进行分类,然后根据节点期望部署的网格位置和其节点类别进行相应的密钥预分配,从而有效改善了网络的安全性能。分析和仿真表明,在相同的存储开销下,本方案具有更高的安全连通率和更强的抗节点捕获攻击能力。     

随机部署的无线传感器网络的负载平衡

从结构的角度来研究在大规模随机部署时所形成的无线传感器网络的数据流负载平衡。通过统计分析邻居节点数目来分析其对无线传感器网络的数据流负载平衡的影响,发现在大规模随机部署时节点的邻居节点数目近似服从正态分布,其成因在于边缘效应。仿真实验发现节点通信半径的增大比部署密度的增大更不利于负载平衡。     

Self-orienting wireless multimedia sensor networks for occlusion-free viewpoints

Wireless multimedia sensor networks (WMSN) are formations of a large number of compact form-factor computing devices that can capture multimedia content, such as video and audio, and communicate them over wireless channels. The efficiency of a WMSN heavily depends on the correct orientation (i.e., view) of its individual sensory units in the field. In this paper, we study the problem of self-orientation in WMSN, that is finding the most beneficial orientation for all multimedia sensors to maximize multimedia coverage. We propose a new algorithm to determine a node’s multimedia coverage and find the sensor orientation that minimizes the negative effect of occlusions and overlapping regions in the sensing field. Our approach enables multimedia sensor nodes to compute their directional coverage leading to an efficient and self-configurable sensor orientation calculation. By using simulations, we show that the occlusion-free viewpoint approach increases the multimedia coverage significantly. The self-orientation methodology is designed in the form of a distributed algorithm, making it a suitable candidate for deployment in practical systems.     

基于平衡距离的无线传感器网络节点部署算法

针对随机部署的无线传感器节点,提出一种节点移动方案。将节点移动划分成若干个过程进行,在每个移动过程中根据平衡距离和位置关系进行节点移动,使聚集在一起的节点分散开,实现对监测区域的最大覆盖。由于节点间平衡距离逐渐增大,因此在每个移动过程中节点的移动距离均较小,减少了节点移动距离总和。仿真结果表明,该算法在保证覆盖效果的基础上,降低节点的总移动距离。     

基于Voronoi的无线传感器网络栅栏覆盖策略

在栅栏覆盖研究中,针对节点部署区域存在无法被监测到的穿越路径的问题,将[Voronoi]图引入栅栏覆盖,划分整个部署区域,提出了基于[Voronoi]图的无线传感器网络栅栏覆盖策略,并监测部署区域是否存在栅栏覆盖空洞,以决定节点是否通过有限移动重新部署空洞区域,实现了对栅栏部署区域的有效覆盖。仿真实验结果表明,该算法提高了对监测区域的覆盖质量,以较低能耗和较少节点构建栅栏,达到预期覆盖要求。     

异构无线传感器网络中基于模拟退火算法的成本最优部署机制

针对异构传感器网络节点的高密度部署和监测目标非均匀分布的情况,提出了一种基于模拟退火算法的成本最优部署方法.算法在保证网络覆盖和容错性的条件下,以异构节点部署成本最小为优化目标进行操作.仿真结果表明该算法能快速收敛于最优解,有效降低网络部署的成本,提高了目标监测质量.     

Simple,extensible and flexible random key predistribution schemes for wireless sensor networks using reusable key pools

Sensor nodes are tiny, low-power, computationally limited and battery constrained electromechanical devices. A sensor node contains a sensing unit and a wireless communication unit. Sensor nodes are deployed over a field for sensing an event data in the environment and transfer it towards a base station over its wireless channel. In a typical application, vast amount of sensor nodes are deployed over a field which constitute a sensor network. Sensor nodes must be customized for a specific sensor network application before the deployment. This customization is needed not only for underlying networking application, but also for security related configurations. Random key predistribution mechanisms have been proposed to provide security for wireless sensor networks. In the literature, there are well known random key predistribution schemes. Some of these schemes are secure, but quite complex to apply in real-world applications due to their node-based customization requirements, while some other are easily applicable but they do not offer reasonable security. In this paper, we propose random key predistribution schemes for wireless sensor networks that provide varying ranges of security. The proposed schemes are easily applicable in real world scenarios due to their simplicity and relaxed node customization requirements. In this respect, our schemes provide a tradeoff. Moreover, our proposed schemes show a good extensibility property. We assume prior deployment knowledge. We examine performance of our schemes and compare them with well known random key predistribution schemes.