SFTD: A SMART forwarding technique based reliable data dissemination scheme for VANETs

被引:0
|
作者
Mahesh R.K. [1 ]
Jawaligi S.S. [1 ]
Patil V. [1 ]
机构
[1] Department of Electronics & Communication Engineering, Sharnbasva University, Karnataka, Kalaburagi
来源
Measurement: Sensors | 2022年 / 24卷
关键词
Clustering; Fitness based Ad-hoc on demand distance vector(FBAODV); Link consistency rate; Predictive geographic routing protocol(PGRP); Received signal strength indication; VANET;
D O I
10.1016/j.measen.2022.100572
中图分类号
学科分类号
摘要
In the transportation field, a promising architecture is vehicular Ad hoc networks (VANETs) for vehicle-to-vehicle communications. In VANETs, various challenges create by the changes in frequent topology for data delivery due to the variation of vehicle velocity with time. It's essential that the efficient routing protocol is designed for achieving the communication with reliability and stability. In a mobile environment, a promising approach is the clustering for efficient routing. For Mobile Ad-hoc Networks (MANETs), most of the clustering algorithms have been designed primarily and not suitable to build a cluster structure in VANETs as it doesn't design for link quality and vehicle behaviour. Both link quality for dissemination of data and vehicle behaviour for clustering are considered in the proposed routing protocol of an efficient cluster based SMART forwarding scheme. The proposed work selects Cluster Heads (CHs) based on the important parameters like link consistency rate (LCR) and Signal to Interference plus Noise Ratio (SINR). The LCR can be described as the amount of time the link is being active. The data dissemination is carried out by Received Signal Strength Indication (RSSI) based probability routing protocol, which measure the link quality based on Link Duration (LD), RSSI of the link. By analysing simulation results, the proposed scheme of SFTD dissemination shows high performance in terms of high Packet delivery Ratio (PDR), and low latency with efficient energy consumption rate. © 2022
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