Utilizing the Maximum Spanning Tree to Construct Stability-based Routes in Self-driving Vehicular Networks

碩士 === 國立成功大學 === 電腦與通信工程研究所 === 105 === In VANETs, vehicle-to-vehicle communication is challenging due to fast topology change, frequent route disruptions and recoveries, and highly variable traffic density caused by vehicles' mobility. The stability of routes between source vehicle and destin...

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Bibliographic Details
Main Authors: Hao-ZeJheng, 鄭皓澤
Other Authors: Kuo-Feng Ssu
Format: Others
Language:en_US
Published: 2017
Online Access:http://ndltd.ncl.edu.tw/handle/rzyuf5
Description
Summary:碩士 === 國立成功大學 === 電腦與通信工程研究所 === 105 === In VANETs, vehicle-to-vehicle communication is challenging due to fast topology change, frequent route disruptions and recoveries, and highly variable traffic density caused by vehicles' mobility. The stability of routes between source vehicle and destination vehicle is an important issue. Recently, some researchers have envisioned that most of the vehicles in the network will be self-driving vehicles in the near future. The most important characteristic of self-driving vehicular environments is that nearly perfect future position prediction of vehicles may be achieved. By utilizing the predicted trajectories information of self-driving vehicles, the link expiration time (LET) and the route expiration time (RET) can be estimated. The most stable forwarding route which has the longest RET will be constructed between source vehicle and destination vehicle. However, the time complexity of nding the most stable path grows drastically with the increase of vehicle density. In this paper, by utilizing maximum spanning tree (MST), a MST-based PTSRC scheme in self-driving vehicular networks is proposed. The simulation results demonstrate the calculation efficiency of the proposed scheme is better than compared scheme especially in the high vehicle density.