基于交通数据的车辆自组织网络连通性及广告分发问题研究

发布时间：2018-03-01 05:32

本文关键词： 车辆自组织网络海量数据网络连通性连通图广告分发　出处：《西安电子科技大学》2015年硕士论文　论文类型：学位论文

【摘要】：作为智能交通系统(Intelligent Transportation System,ITS)的重要组成部分,车辆自组织网络(Vehicular Ad Hoc Networks,VANET)是移动自组织网络(Mobile Ad Hoc Network,MANET)的重要分支,是专门为车辆间通信而设计的自组织网络,迅速获得了学术界和产业界的广泛重视和深入研究,已成为无线网络和智能交通等领域的研究热点。车辆自组织网络技术为驾驶员和乘客提供广泛的安全类和娱乐类应用,在社会生活中具有实质性的应用需求,被认为是现代无线网络技术中最有前途的商业应用,因此对于车辆自组织网络的研究具有重要意义。本文的研究工作主要包括两部分,具体研究内容如下:首先,针对快速路场景下车辆自组织网络连通性进行研究。VANET中的安全应用和娱乐应用的实现极度依赖于成功的分组交换,而成功的分组交换是基于可靠的链路质量或者网络中的节点是连通的,因此对于VANET网络连通性的研究是VANET领域中的关键问题。现实世界的交通数据被广泛用来研究VANET中与网络连通性有关的各种指标,例如,无线链路的寿命、节点度和簇的大小等。尽管对于VANET网络连通性的研究越来越多,但是对于大规模城市的网络连通性仍然缺乏清晰的认识。本文提出一种计算快速路固定区域网络连通概率的系统模型,根据该系统模型和台北市车辆检测器收集到的海量数据绘制了多张时变的连通图,并根据连通图宏观上对台北市的网络连通性进行了分析并且分析了影响VANET网络连通性的各个参数。分析结果有利于VANET协议的设计和VANET设施的部署。此外,针对车辆自组织网络场景中移动广告分发的种子车辆选择问题进行了研究。由于车辆自组织网络中节点处于高速运动状态,网络拓扑结构高动态变化,应用于传统的拓扑结构稳定的静态社交网络上的候选节点选择算法已经不再适用于车辆自组织网络场景。本文基于台湾海量环岛公交车数据提出一种在公交车中选择种子车辆作为传播移动广告的初始车辆的系统模型,该模型基于地理位置信息数据将车辆划分社团,并每隔一定时间绘制一张连通图。根据连通图分析图中每辆车的中心性变化,通过中心性指标选择种子车辆作为广告分发的初始车辆。
[Abstract]:As the intelligent transportation system (Intelligent Transportation System, ITS) is an important part of vehicle self-organizing network (Vehicular Ad Hoc Networks, VANET) is a mobile ad hoc network (Mobile Ad Hoc Network, MANET) is an important branch, is designed for inter vehicle communication and self-organizing network design, quickly gained widespread attention and further research in academia and industry, has become a hot research topic in wireless network and intelligent transportation and other fields. The vehicle self-organizing network technology to provide security and entertainment applications for drivers and passengers, with applications in terms of social life, is considered to be the most promising application of modern commercial radio the network technology, so it has important significance for the study of vehicular ad hoc networks. The main research work of this paper includes two parts, the specific contents are as follows: firstly, aiming at the expressway The scene of vehicular ad hoc network connectivity of.VANET security application and entertainment is extremely dependent on the success of packet switching and packet switching node is successful and reliable in the network based on link quality or is connected, so the research of VANET network connectivity is a key problem in the field of VANET. The traffic data of the real world is widely used in a variety of indicators related with network connectivity in VANET for example, wireless link lifetime, node degree and cluster size. Although the research of VANET network connectivity is more and more, but for the large scale city network connectivity is still a lack of clear understanding of this. For computing the probability of connectivity of fixed area network expressway system model, according to the data model and the system of Taipei city vehicle detector to collect more than a draw When the connected graph, and according to the graph on a macro Taipei city network connectivity has been analyzed and analyzed the influence of various parameters of the VANET network deployment. The analysis results can help the design of VANET protocol and VANET facilities. In addition, the vehicle ad hoc network scene in mobile advertising vehicle seed distribution selection problem is studied. Because the vehicle from the high-speed motion state in network nodes, high dynamic changes of network topology, the candidate node static social network topology is applied to the traditional stable on the choice of algorithm is no longer applicable to vehicle ad hoc network. In this paper, a scene on the bus in the vehicle system model as seed selection the initial vehicle borne mobile advertising of Taiwan Island bus data based on the massive information data model, based on geographic location of the vehicle division The community and draw a connected graph at regular intervals. According to the connected graph, we analyze the centrality of every vehicle and select the seed vehicle as the initial vehicle for advertisement distribution through centrality index.

【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：U495

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