Data Forwarding System with Error Detection and Leader Selection Features

Author:

Obias Karl,Magsino Elmer R.,Abad Alexander,Arada Gerald

Abstract

Abstract The concept of vehicular networks utilizes vehicular nodes and roadside units to exchange data to achieve travel comfort and convenience. However, as the number of vehicles on the road increases exponentially, the data dissemination becomes inefficient and lossy due to communication factors, one of which is the availability of too much sources of information. In this paper, a data forwarding system (DFS) is proposed to address communication failure due to bit error during data transmission and in the presence of data collision. The proposed system enables the receiver to detect errors in the received data using Hamming codes and utilizes a retransmission scheme to correct bit errors. DFS also selects a limited number of vehicles, called leaders, that can communicate with the infrastructure to minimize data collision and flooding. DFS, under various number of vehicles, is tested in additive white gaussian noise (AWGN) and Rayleigh channels. Simulation results show that DFS reduces bit error rate (BER) to approximately 54% in the AWGN and 62% in the Rayleigh channel for the maximum number of retransmissions simulated, respectively. Also, with DFS, data upload to infrastructures is reduced by at most 99.5% depending on the maximum allowable number of clusters and vehicles inside the RSU coverage.

Publisher

IOP Publishing

Subject

General Physics and Astronomy

Reference21 articles.

1. Efficient 3D road map data exchange for intelligent vehicles in vehicular fog networks;Ho;IEEE Transactions on Vehicular Technology,2019

2. Vehicle communication network in intelligent transportation system based on Internet of Things;Zhang;Comput. Commun.,2020

3. An intelligent highway tollgate queue selector for improving server utilization and vehicle waiting time;Magsino,2016

4. Cooperative Autonomous Driving for Traffic Congestion Avoidance through Vehicle-to-Vehicle Communications;Wang

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