基于隶属云的车载传感网移动模型研究

发布时间：2018-03-10 23:24

本文选题：车载传感网　切入点：移动模型　出处：《长安大学》2016年硕士论文　论文类型：学位论文

【摘要】：作为物联网技术的典型应用,车载传感网已成为提高道路通行质量的优先发展技术。由于城市道路车流量较大,构成具有一定密度、稳定的车载传感网成为可能。车载传感网中,节点的高速移动导致网络拓扑结构频繁变化,网络特性受限。影响节点移动行为的因素具有模糊性和随机性等不确定性,传统的车辆移动模型已不能准确表征节点的移动规律。因此,针对节点移动的不确定性,开展车载传感网移动模型研究,具有重要研究价值。本文仿真分析了现有车载传感网节点移动模型,归纳了各模型节点移动的差异性及不足。结合车载网节点移动过程中的不确定性分析,提取了相对速度、相对位置、时间依赖度、空间依赖度和路面依赖度5类不确定性指标。计算得出了每个指标的云数字特征,利用云模型完成不确定性指标定性分析与定量描述之间的转换,解决了节点移动过程中模糊性和随机性问题。提出了一种改进型智能驾驶员模型,可最大程度地涵盖节点移动过程中的不确定性,更真实地表征节点移动规律与策略,拓展了智能驾驶员模型的描述能力。依据道路实测数据,对比改进模型的计算结果与实测得出的加速度与速度值,验证了模型的有效性。结合Vanet MobiSim与NS2仿真平台,对比改进模型与智能驾驶员模型对路由协议的影响。以平均端到端时延与分组数据投递率指标,表征两种移动模型对路由协议的影响程度。验证与分析表明,改进模型可客观反映城市道路上的车辆移动行为,与智能驾驶员模型相比,提高了在交通运行环境复杂时通信链路的稳定性,更真实地表征了车辆移动规律。
[Abstract]:As a typical application of the Internet of things technology, the vehicle-borne sensor network has become the priority development technology to improve the road traffic quality. Stable vehicle-borne sensor network is possible. In vehicle-borne sensor network, the high speed movement of nodes leads to frequent changes in network topology and limited network characteristics. The factors influencing node mobility are uncertain, such as fuzziness and randomness. The traditional vehicle movement model can not accurately represent the moving law of nodes. Therefore, the research on the mobility model of vehicle sensor network is carried out in view of the uncertainty of node movement. It has important research value. This paper simulates and analyzes the existing vehicle sensor network node movement model, sums up the differences and shortcomings of each model node movement, combines with the uncertainty analysis in the vehicle network node movement process, extracts the relative speed. The relative position, time dependence, spatial dependence and road dependence are five kinds of uncertain indexes. The cloud digital features of each index are calculated, and the transformation between qualitative analysis and quantitative description of uncertainty index is completed by using cloud model. The fuzziness and randomness in the process of node movement are solved. An improved intelligent driver model is proposed, which can cover the uncertainty in the process of node movement to the greatest extent and represent the law and strategy of node movement more realistically. The ability to describe the intelligent driver model is expanded. The validity of the model is verified by comparing the calculated results of the improved model with the measured acceleration and velocity values according to the measured data of the road. The simulation platform of Vanet MobiSim and NS2 is used to verify the validity of the model. The influence of the improved model and the intelligent driver model on the routing protocol is compared. The average end-to-end delay and packet data delivery rate index are used to characterize the influence of the two mobile models on the routing protocol. Compared with the intelligent driver model, the improved model can objectively reflect the mobile behavior of vehicles on urban roads. Compared with the intelligent driver model, it can improve the stability of communication links when the traffic environment is complex, and represent the vehicle movement law more truthfully.
【学位授予单位】：长安大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：U463.67;U495

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