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Published in: Neural Computing and Applications 11/2018

24-10-2016 | Original Article

F-Ant: an effective routing protocol for ant colony optimization based on fuzzy logic in vehicular ad hoc networks

Authors: Hamideh Fatemidokht, Marjan Kuchaki Rafsanjani

Published in: Neural Computing and Applications | Issue 11/2018

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Abstract

Vehicular ad hoc networks (VANETs) are a subset of mobile ad hoc networks that provide communication services between nearby vehicles and also between vehicles and roadside infrastructure. These networks improve road safety and accident prevention and provide entertainment for passengers of vehicles. Due to the characteristics of VANET such as self-organization, dynamic nature and fast-moving vehicles, routing in this network is a considerable challenge. Swarm intelligence algorithms (nature-inspired) such as ant colony optimization (ACO) have been proposed for developing routing protocols in VANETs. In this paper, we propose an enhanced framework for ACO protocol based on fuzzy logic for VANETs. To indicate the effectiveness and performance of our proposed protocol, the network simulator NS-2 is used for simulation. The simulation results demonstrate that our proposed protocol achieves high data packet delivery ratio and low end-to-end delay compared to traditional routing algorithms such as ACO and ad hoc on-demand distance vector (AODV).

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Metadata
Title
F-Ant: an effective routing protocol for ant colony optimization based on fuzzy logic in vehicular ad hoc networks
Authors
Hamideh Fatemidokht
Marjan Kuchaki Rafsanjani
Publication date
24-10-2016
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 11/2018
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-016-2631-y

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