Design and performance evaluation of Improved DFACO protocol based on dynamic clustering in VANETs

Sahar Ebadinezhad

doi:10.1007/s42452-021-04494-8

Abstract

This study focuses on Vehicular Ad-hoc Networks (VANETs) stability in an environment that is dynamic which often leads to major challenges in VANETs, such as dynamic topology changes, shortest routing paths and also scalability. One of the best solutions for such challenges is clustering. In this study, we present five novel routing protocols based on Dynamic Flying Ant Colony Optimization (DFACO) algorithm to achieve minimum number of clusters, high accuracy, minimum time and solution cost by selecting the best cluster-head which is obtained from a new mechanism of dynamic metaheuristic-based clustering. In this regard, major improvements are applied on classical DFACO by adjusting the procedure for updating the pheromone and tuning the evaporation rate that has a major role in DFACO. In this research two individual phases of experiments are conducted for performance evaluation of proposed routing protocols. The presented solution is verified and compared to classic Ant Colony Optimization (ACO), DFACO and ACO Based Clustering Algorithm for VANET (CACONET) algorithms in phase one; and compared to clustering algorithms such as Center Position and Mobility CPM), Highest-Degree algorithm (HD), Angle-based Clustering Algorithm (ACA) in phase two through NS-2 and SUMO simulation tools. Simulation results have confirmed the expected behaviour and show that our proposed protocols achieve better node connectivity and cluster stability than the former.

Highlights

A well-known combinatorial optimization problem is raised as the Vehicle Routing Problem (VRP) in transportation dialectics
The main objective of VRP is decreasing the cost of routes which are discovered in the progress of vehicular route discovery
Most of the studies on the clustering field are concentrated on the static/traditional clustering method that forms the clusters based on the closeness of vehicles to the Base Station/Road Side Unit (BS/RSU) to be elected as Cluster Head (CH)

Summary

Introduction

A well-known combinatorial optimization problem is raised as the Vehicle Routing Problem (VRP) in transportation dialectics. The VANET network communication includes Vehicle-toInfrastructure (V2I) and Vehicle-to-Vehicle (V2V) which are a dynamic network, being that there are nodes having inconsistent/random motion leading to nodes frequently experiencing structural deviations. In cases of surveillance and safety application, delay can be dangerous In this regard, five new algorithms are proposed in this study for the VANET environment with the aim of discovering a best route. Most of the studies on the clustering field are concentrated on the static/traditional clustering method that forms the clusters based on the closeness of vehicles to the Base Station/Road Side Unit (BS/RSU) to be elected as Cluster Head (CH)

Objectives

Findings

Discussion

Conclusion