基于无坐标信息的无线传感器网络边缘检测技术的研究
发布时间：2018-07-21 17:26
【摘要】：无线传感器网络[1-4](Wireless Sensor Network：WSN)由一组微小型功能齐全的MEMS装置构成，这些微型装置包括传感器、无线发射器和接收器、电源，它们分布在一个地理区域中对该区域进行实时监测[5]。无线传感器网络本身具有计算处理能力，网络中的各节点之间可以互相通信以便获取网络中的数据，同时节点之间还可以自动组织网络并且协同进行工作。与传统的单一大型传感器或有线通信装置相比，无线传感器网络内部主要靠无线通信，这使得无线传感器网络在精度、灵活性、经济性、可靠性等诸多方面都有明显的优越性[6]。无线传感器网络边缘检测[7]对于实现无线传感器网络优质应用至关重要，是网络实现高效应用的支撑技术之一。在无线传感器网络应用中，边缘检测在目标跟踪、覆盖检测和路由构造等方面都发挥着举足轻重的作用。 论文研究了无线传感器网络边缘节点的识别问题，在一个无线传感器网络中，邻居节点之间可以直接建立连接，并且可以估计与附近节点的距离（并不是实际的距离）。论文的目的是在不依靠网络中节点的坐标信息的情况下，仅仅通过节点之间的连接关系和邻居节点之间的距离来寻找边缘节点。 论文首先提出一种寻找网络边缘节点的算法并分别应用于分布式与集中式场景中，网络中的节点分布在一个有边界、无坐标、低密度、随机部署的无线传感器网络中，此算法的关键思想是在集中式场景中提出的，并且扩展到了分布式场景中，通过仿真实验证明分布式实现相对于真实的无线传感器网络更加有效，而且分布式算法相对于集中式算法能够检测出更高质量的网络边界，尤其是在稀疏网络中由于节点之间的稀疏连接而不能收集到所有节点的位置信息，分布式算法具有很高的优势。之后论文在几何知识与拓扑知识相结合的前提下提出了一种无线传感器网络边缘检测新的分布式算法，基于有向树扩展的多边形包围检测算法，算法对于网络节点的密度没有限制要求，仿真结果表明该算法有效避免了错检、漏检情况的发生，判别方法简单准确，，有效提高了无线传感器网络边缘检测的效率和精度。 论文研究无线传感器网络边缘检测技术，旨在对现有算法进行详细分析并设计相应新的优化算法，不需要任何节点的位置信息，仅依靠节点之间的连通性质来完成所需任务，并且在边缘检测实现的基础上本文对无线传感器网络的应用方面进行了概括总结，并详细介绍了无线传感器网络中目标跟踪技术的相关算法及应用。
[Abstract]:The wireless sensor network [1-4] (Wireless Sensor Network:WSN) is made up of a set of small and fully functional MEMS devices, which include sensors, wireless transmitters and receivers, and power sources. They are distributed in a geographic area to monitor the region in real time [5]. The wireless sensor network itself has the computing power, The nodes in the network can communicate with each other so that the data in the network can be obtained. At the same time, the nodes can also automatically organize the network and work together. Compared with the traditional single large sensor or cable communication device, the wireless sensor network is mainly based on wireless communication, which makes the wireless sensor network with precision and flexibility. There are obvious advantages in many aspects, such as activity, economy, reliability and so on. [6]. wireless sensor network edge detection [7] is very important for the realization of high quality application of wireless sensor networks. It is one of the support technologies for efficient application of network. In wireless sensor network applications, edge detection is tracking, covering detection and routing. All of them play a decisive role.
The paper studies the recognition of the edge nodes of wireless sensor networks. In a wireless sensor network, the neighbor nodes can directly establish a connection and estimate the distance from the nearby nodes (not the actual distance). The purpose of the paper is to only pass the node without relying on the coordinates of the nodes in the network. The connection between points and the distance between neighbor nodes to find edge nodes.
In this paper, an algorithm for finding network edge nodes is proposed and applied to distributed and centralized scenarios. The nodes in the network are distributed in a wireless sensor network with boundary, no coordinate, low density and random deployment. The key idea of this algorithm is put forward in the centralized scene and extends to the distributed field. The simulation experiments show that the distributed implementation is more effective than the real wireless sensor network, and the distributed algorithm can detect the higher quality of the network boundary relative to the centralized algorithm, especially in the sparse network, which can not collect the location information of all nodes because of the sparse connection between nodes. Based on the combination of geometric knowledge and topology knowledge, a new distributed algorithm for edge detection in wireless sensor networks is proposed, based on a polygon encircling detection algorithm based on directed tree expansion, and the algorithm has no restriction on the density of network nodes. The simulation results show that the algorithm has the advantages of the algorithm. This method avoids the wrong detection and missed detection, and the method is simple and accurate. It effectively improves the efficiency and accuracy of edge detection in wireless sensor networks.
This paper studies the edge detection technology of wireless sensor network, which aims to analyze the existing algorithms in detail and design a new optimization algorithm. It does not need the location information of any node, only relies on the connectivity between nodes to complete the required tasks, and on the basis of the implementation of the edge detection, the application of this paper to the wireless sensor network is made. In this paper, we summarize and introduce the related algorithms and applications of target tracking technology in wireless sensor networks.
【学位授予单位】：中北大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TP212.9;TN929.5
本文编号：2136250
[Abstract]:The wireless sensor network [1-4] (Wireless Sensor Network:WSN) is made up of a set of small and fully functional MEMS devices, which include sensors, wireless transmitters and receivers, and power sources. They are distributed in a geographic area to monitor the region in real time [5]. The wireless sensor network itself has the computing power, The nodes in the network can communicate with each other so that the data in the network can be obtained. At the same time, the nodes can also automatically organize the network and work together. Compared with the traditional single large sensor or cable communication device, the wireless sensor network is mainly based on wireless communication, which makes the wireless sensor network with precision and flexibility. There are obvious advantages in many aspects, such as activity, economy, reliability and so on. [6]. wireless sensor network edge detection [7] is very important for the realization of high quality application of wireless sensor networks. It is one of the support technologies for efficient application of network. In wireless sensor network applications, edge detection is tracking, covering detection and routing. All of them play a decisive role.
The paper studies the recognition of the edge nodes of wireless sensor networks. In a wireless sensor network, the neighbor nodes can directly establish a connection and estimate the distance from the nearby nodes (not the actual distance). The purpose of the paper is to only pass the node without relying on the coordinates of the nodes in the network. The connection between points and the distance between neighbor nodes to find edge nodes.
In this paper, an algorithm for finding network edge nodes is proposed and applied to distributed and centralized scenarios. The nodes in the network are distributed in a wireless sensor network with boundary, no coordinate, low density and random deployment. The key idea of this algorithm is put forward in the centralized scene and extends to the distributed field. The simulation experiments show that the distributed implementation is more effective than the real wireless sensor network, and the distributed algorithm can detect the higher quality of the network boundary relative to the centralized algorithm, especially in the sparse network, which can not collect the location information of all nodes because of the sparse connection between nodes. Based on the combination of geometric knowledge and topology knowledge, a new distributed algorithm for edge detection in wireless sensor networks is proposed, based on a polygon encircling detection algorithm based on directed tree expansion, and the algorithm has no restriction on the density of network nodes. The simulation results show that the algorithm has the advantages of the algorithm. This method avoids the wrong detection and missed detection, and the method is simple and accurate. It effectively improves the efficiency and accuracy of edge detection in wireless sensor networks.
This paper studies the edge detection technology of wireless sensor network, which aims to analyze the existing algorithms in detail and design a new optimization algorithm. It does not need the location information of any node, only relies on the connectivity between nodes to complete the required tasks, and on the basis of the implementation of the edge detection, the application of this paper to the wireless sensor network is made. In this paper, we summarize and introduce the related algorithms and applications of target tracking technology in wireless sensor networks.
【学位授予单位】：中北大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TP212.9;TN929.5
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