传感网络中虫洞检测算法研究

发布时间：2018-05-21 08:31

本文选题：无线传感网络 + 虫洞　；参考：《成都理工大学》2017年硕士论文

【摘要】：无线传感器网络(WSN)为人类提供了一种可以从数据角度去感知客观世界的方式,其研究前景广阔。随着近年来的迅速发展,已在军事、工业、环境监测、医疗健康和日常生活中扮演着越来越重要的角色。无线传感器网络作为物联网中的一种核心技术,它在物联网中与其他技术协同工作,共同所产生的经济效率和社会效益远远大于单种技术产生效益的总和。无线传感器网络与有线网络和传统的无线网络有着巨大的不同之处,它仅由许多传感感器节点,没有复杂、高效的管理设备用于管理网络拓扑结构与各种协议。节点间的数据通信依靠自身与其他节点的相互覆盖而形成的无线链路。因为没有集中式的管理设备,节点网络拓扑的形成、管理和维护都只能依靠节点本身。而无线传感器网络的工作环境往往比较恶劣,其拓扑结构中很有可能会出现虫洞,从而带来恶劣的影响,所以虫洞检测是无线传感器网络的中的一个重要研究课题。检测和定位无线传感器网络的外边界与虫洞产生的内边界对网络的稳定性、工作效率与生命周期有着很强的关联性。本文基于复杂网络中的渗流理论对无线传感器网络的虫洞进行研究。本研究在无法获取节点位置信息的前提下,以检测网络中虫洞的边界与网络的外边界为目标,研究相关的检测算法与参数优化。本文主要内容如下:1)利用渗流理论中网络中某一点的状态突变会引起系统全局状态发生改变的特点,建立了回流模型。回流模型通过修改某个节点状态,然后分析处于不同位置节点的状态改变情况;2)在回流模型的基础上进行无线传感器网络的边界节点的识别形成边界森林,最后通过最短路径算法将边界森林形成闭环;3)通过仿真软件进行多组模拟实验,对算法的准确性进行验证。并分析部分参数的优化。本文提出的算法可以检测出90%以上的边界节点,针对无线传感感器中虫洞检测效果良好。
[Abstract]:Wireless sensor networks (WSNs) provide a way for human beings to perceive the objective world from the point of view of data. With the rapid development in recent years, it has played a more and more important role in military, industry, environmental monitoring, medical health and daily life. Wireless sensor network (WSN) is a core technology in the Internet of things. It works in collaboration with other technologies in the Internet of things, which results in far greater economic efficiency and social benefit than the sum of benefits produced by a single technology. Wireless sensor network has great difference from wired network and traditional wireless network. It is only composed of many sensor nodes without complex and efficient management equipment to manage network topology and various protocols. Wireless link formed by data communication between nodes by mutual coverage with other nodes. Because there is no centralized management equipment, node network topology formation, management and maintenance can only rely on the node itself. However, the working environment of wireless sensor networks is often bad, and wormholes are likely to appear in the topology of wireless sensor networks. Therefore, wormhole detection is an important research topic in wireless sensor networks. Detecting and locating the outer boundary of wireless sensor network and the inner boundary produced by wormhole have strong correlation with the network stability, work efficiency and life cycle. In this paper, wormholes of wireless sensor networks are studied based on percolation theory in complex networks. On the premise that the node location information can not be obtained, the detection of wormhole boundary and the outer boundary of the network are the targets of this study, and the related detection algorithms and parameter optimization are studied. The main contents of this paper are as follows: (1) based on the characteristic that the sudden change of the state at a certain point in the percolation theory can cause the change of the global state of the system, a reflux model is established. By modifying a node state and analyzing the state change of nodes in different locations, the reflux model is used to identify the boundary nodes of WSN to form a boundary forest based on the reflux model. Finally, the shortest path algorithm is used to form the boundary forest in closed loop. The simulation software is used to carry out multi-group simulation experiments to verify the accuracy of the algorithm. The optimization of some parameters is analyzed. The algorithm proposed in this paper can detect more than 90% of boundary nodes, and the detection effect of wormhole in wireless sensor is good.
【学位授予单位】：成都理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP212.9;TN929.5

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