Energy Efficient Routing Protocol in Sensor Networks Using Genetic Algorithm

In this paper, we examine routing protocols with the shortest path in sensor networks. In doing this, we propose a genetic algorithm (GA)-based Ad Hoc On-Demand Multipath Distance Vector routing protocol (GA-AOMDV). We utilize a fitness function that optimizes routes based on the energy consumption...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Jatinkumar Patel, Hosam El-Ocla
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
Materias:
DSR
Acceso en línea:https://doaj.org/article/382e776b7f7a4d95bef6561f1cdb5b11
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
id oai:doaj.org-article:382e776b7f7a4d95bef6561f1cdb5b11
record_format dspace
spelling oai:doaj.org-article:382e776b7f7a4d95bef6561f1cdb5b112021-11-11T19:05:00ZEnergy Efficient Routing Protocol in Sensor Networks Using Genetic Algorithm10.3390/s212170601424-8220https://doaj.org/article/382e776b7f7a4d95bef6561f1cdb5b112021-10-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/21/7060https://doaj.org/toc/1424-8220In this paper, we examine routing protocols with the shortest path in sensor networks. In doing this, we propose a genetic algorithm (GA)-based Ad Hoc On-Demand Multipath Distance Vector routing protocol (GA-AOMDV). We utilize a fitness function that optimizes routes based on the energy consumption in their nodes. We compare this algorithm with other existing ad hoc routing protocols including LEACH-GA, GA-AODV, AODV, DSR, EPAR, EBAR_BFS. Results prove that our protocol enhances the network performance in terms of packet delivery ratio, throughput, round trip time and energy consumption. GA-AOMDV protocol achieves average gain that is 7 to 22% over other protocols. Therefore, our protocol extends the network lifetime for data communications.Jatinkumar PatelHosam El-OclaMDPI AGarticleindex terms—AODVAOMDVDSRenergygeneticoptimizationChemical technologyTP1-1185ENSensors, Vol 21, Iss 7060, p 7060 (2021)
institution DOAJ
collection DOAJ
language EN
topic index terms—AODV
AOMDV
DSR
energy
genetic
optimization
Chemical technology
TP1-1185
spellingShingle index terms—AODV
AOMDV
DSR
energy
genetic
optimization
Chemical technology
TP1-1185
Jatinkumar Patel
Hosam El-Ocla
Energy Efficient Routing Protocol in Sensor Networks Using Genetic Algorithm
description In this paper, we examine routing protocols with the shortest path in sensor networks. In doing this, we propose a genetic algorithm (GA)-based Ad Hoc On-Demand Multipath Distance Vector routing protocol (GA-AOMDV). We utilize a fitness function that optimizes routes based on the energy consumption in their nodes. We compare this algorithm with other existing ad hoc routing protocols including LEACH-GA, GA-AODV, AODV, DSR, EPAR, EBAR_BFS. Results prove that our protocol enhances the network performance in terms of packet delivery ratio, throughput, round trip time and energy consumption. GA-AOMDV protocol achieves average gain that is 7 to 22% over other protocols. Therefore, our protocol extends the network lifetime for data communications.
format article
author Jatinkumar Patel
Hosam El-Ocla
author_facet Jatinkumar Patel
Hosam El-Ocla
author_sort Jatinkumar Patel
title Energy Efficient Routing Protocol in Sensor Networks Using Genetic Algorithm
title_short Energy Efficient Routing Protocol in Sensor Networks Using Genetic Algorithm
title_full Energy Efficient Routing Protocol in Sensor Networks Using Genetic Algorithm
title_fullStr Energy Efficient Routing Protocol in Sensor Networks Using Genetic Algorithm
title_full_unstemmed Energy Efficient Routing Protocol in Sensor Networks Using Genetic Algorithm
title_sort energy efficient routing protocol in sensor networks using genetic algorithm
publisher MDPI AG
publishDate 2021
url https://doaj.org/article/382e776b7f7a4d95bef6561f1cdb5b11
work_keys_str_mv AT jatinkumarpatel energyefficientroutingprotocolinsensornetworksusinggeneticalgorithm
AT hosamelocla energyefficientroutingprotocolinsensornetworksusinggeneticalgorithm
_version_ 1718431636650983424