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

Authors:
Hao-Ze Jheng
Hsin-Han Lin
Kuo-Feng Ssu
Yu-Yuan Lin

Keywords: self-driving; vehicular network; stable routing; maximum spanning tree.

Abstract:
In vehicular ad hoc networks (VANETs), the communication is challenging due to fast topology changes, frequent route disruptions and recoveries, and the highly variable traffic density caused by the vehicles’ mobility. The stability of routes between source vehicles and destination vehicles becomes an important issue. It can be expected that most of the vehicles will be self-driving cars in the future. The most important characteristic of the self-driving vehicular environment is that accurate future positions of vehicles can be obtained. By utilizing the predicted trajectories 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, can be constructed between source vehicles and destination vehicles. However, the time complexity of determining the most stable path grows drastically with the increase of the vehicle density. In this paper, by utilizing maximum spanning trees (MST), an MST-based route construction scheme with predicted trajectories is developed. The simulation results demonstrate that the calculation efficiency of the scheme is better than the PTSRC scheme especially in the environment with the higher vehicle densities.

Pages: 26 to 31

Copyright: Copyright (c) IARIA, 2018

Publication date: June 24, 2018

Published in: conference

ISSN: 2308-4219

ISBN: 978-1-61208-642-2

Location: Venice, Italy

Dates: from June 24, 2018 to June 28, 2018