Intelligent Humming Bird Optimization Based Distance Aware Routing Scheme for Vehicular Networks

In recent times, vehicular ad hoc network (VANET) has been significantly considered by several service providers from urban locations. Such a network could not only prevent accidents and enhance road safety but among them offer a means of entertainment to passengers. But, based on the present analys...

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Published inInternational Conference on Engineering Technology and their Applications (Online) pp. 564 - 570
Main Authors Abed, Z., Shnawa, Ammar H., Sheel, Shaid, Hussien alawadi, Ahmed, Ibrahim, Karrar
Format Conference Proceeding
LanguageEnglish
Published IEEE 15.07.2023
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ISSN2831-753X
DOI10.1109/IICETA57613.2023.10351192

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Abstract In recent times, vehicular ad hoc network (VANET) has been significantly considered by several service providers from urban locations. Such a network could not only prevent accidents and enhance road safety but among them offer a means of entertainment to passengers. But, based on the present analysis, effective routing is until remained a big open problem for the VANETs. The vehicle's limited broadcast range reasons the route for participating from data broadcast in the source S to destination D can vanish seldom. So, the stable route from source to destination requires for delivering data packets at planned destination. This study designs an Intelligent Artificial Humming Bird Optimization based Distance Aware Routing (IAHBO-DAR) scheme for VANET. The presented IAHBO-DAR model mainly considered the distance metric for route selection process. The IAHBO-DAR model is based on the integration of standard AHBO algorithm with dynamic oppositional based learning (DOBL) concept. In addition, the IAHBO-DAR model computes a fitness function with three variables like node degree (ND), residual energy (RE), and distance. A wide range of simulations have been conducted to exhibit the enhanced routing performance of the IAHBO-DAR approach. The experimental value demonstrates the betterment of the IAHBO-DAR algorithm compared to recent approaches.
AbstractList In recent times, vehicular ad hoc network (VANET) has been significantly considered by several service providers from urban locations. Such a network could not only prevent accidents and enhance road safety but among them offer a means of entertainment to passengers. But, based on the present analysis, effective routing is until remained a big open problem for the VANETs. The vehicle's limited broadcast range reasons the route for participating from data broadcast in the source S to destination D can vanish seldom. So, the stable route from source to destination requires for delivering data packets at planned destination. This study designs an Intelligent Artificial Humming Bird Optimization based Distance Aware Routing (IAHBO-DAR) scheme for VANET. The presented IAHBO-DAR model mainly considered the distance metric for route selection process. The IAHBO-DAR model is based on the integration of standard AHBO algorithm with dynamic oppositional based learning (DOBL) concept. In addition, the IAHBO-DAR model computes a fitness function with three variables like node degree (ND), residual energy (RE), and distance. A wide range of simulations have been conducted to exhibit the enhanced routing performance of the IAHBO-DAR approach. The experimental value demonstrates the betterment of the IAHBO-DAR algorithm compared to recent approaches.
Author Ibrahim, Karrar
Shnawa, Ammar H.
Sheel, Shaid
Hussien alawadi, Ahmed
Abed, Z.
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  organization: Al-Zahraa University for Women,Karbala,Iraq
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Snippet In recent times, vehicular ad hoc network (VANET) has been significantly considered by several service providers from urban locations. Such a network could not...
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StartPage 564
SubjectTerms Birds
Computational modeling
Distance
Energy efficiency
Heuristic algorithms
Measurement
Metaheuristics
Optimal path
Road safety
Routing
Routing process
Vehicular ad hoc networks
Vehicular networks
Title Intelligent Humming Bird Optimization Based Distance Aware Routing Scheme for Vehicular Networks
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