Energy Efficient Clustering-Based Mobile Routing Algorithm on WSNs

In this paper, we propose and discuss two types of algorithms to improve energy efficiency in Wireless Sensor Networks. An efficient approach for extending the life of a network is known as “sensor clustering” in wireless sensor networks. In proposed algorithms, the study area...

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Main Authors: Muhammed Ali Aydin, Baybars Karabekir, Abdul Halim Zaim
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9460987/
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spelling doaj-ab4e7e1c1ed84a6b974391b55977c2cc2021-06-28T23:00:27ZengIEEEIEEE Access2169-35362021-01-019895938960110.1109/ACCESS.2021.30909799460987Energy Efficient Clustering-Based Mobile Routing Algorithm on WSNsMuhammed Ali Aydin0https://orcid.org/0000-0002-1846-6090Baybars Karabekir1https://orcid.org/0000-0002-4375-1440Abdul Halim Zaim2Department of Computer Engineering, Istanbul University-Cerrahpaşa, İstanbul, TurkeyDepartment of Computer Engineering, İstanbul Commerce University, İstanbul, TurkeyDepartment of Computer Engineering, İstanbul Commerce University, İstanbul, TurkeyIn this paper, we propose and discuss two types of algorithms to improve energy efficiency in Wireless Sensor Networks. An efficient approach for extending the life of a network is known as “sensor clustering” in wireless sensor networks. In proposed algorithms, the study area where sensor nodes are randomly distributed is divided into clusters. In each cluster, the sensor that is the closest to the cluster center and has the highest residual energy is chosen as the cluster head. To make this choice, a greedy approach and artificial neural network methods are applied. In addition, to reduce the energy consumption of cluster heads, a mobile sink is used. The list of routes to be used by the mobile sink is calculated with the genetic algorithm. According to the route information, the mobile sink moves to the clusters and initiates the data collection process for each cluster. We compared our models according to the round value at which all sensor nodes run out of energy and the energy consumption by the network per round. Simulation results show that the proposed models increase the energy efficiency and extend the network lifespan.https://ieeexplore.ieee.org/document/9460987/Energy efficiencyLEACHwireless sensor network
collection DOAJ
language English
format Article
sources DOAJ
author Muhammed Ali Aydin
Baybars Karabekir
Abdul Halim Zaim
spellingShingle Muhammed Ali Aydin
Baybars Karabekir
Abdul Halim Zaim
Energy Efficient Clustering-Based Mobile Routing Algorithm on WSNs
IEEE Access
Energy efficiency
LEACH
wireless sensor network
author_facet Muhammed Ali Aydin
Baybars Karabekir
Abdul Halim Zaim
author_sort Muhammed Ali Aydin
title Energy Efficient Clustering-Based Mobile Routing Algorithm on WSNs
title_short Energy Efficient Clustering-Based Mobile Routing Algorithm on WSNs
title_full Energy Efficient Clustering-Based Mobile Routing Algorithm on WSNs
title_fullStr Energy Efficient Clustering-Based Mobile Routing Algorithm on WSNs
title_full_unstemmed Energy Efficient Clustering-Based Mobile Routing Algorithm on WSNs
title_sort energy efficient clustering-based mobile routing algorithm on wsns
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2021-01-01
description In this paper, we propose and discuss two types of algorithms to improve energy efficiency in Wireless Sensor Networks. An efficient approach for extending the life of a network is known as “sensor clustering” in wireless sensor networks. In proposed algorithms, the study area where sensor nodes are randomly distributed is divided into clusters. In each cluster, the sensor that is the closest to the cluster center and has the highest residual energy is chosen as the cluster head. To make this choice, a greedy approach and artificial neural network methods are applied. In addition, to reduce the energy consumption of cluster heads, a mobile sink is used. The list of routes to be used by the mobile sink is calculated with the genetic algorithm. According to the route information, the mobile sink moves to the clusters and initiates the data collection process for each cluster. We compared our models according to the round value at which all sensor nodes run out of energy and the energy consumption by the network per round. Simulation results show that the proposed models increase the energy efficiency and extend the network lifespan.
topic Energy efficiency
LEACH
wireless sensor network
url https://ieeexplore.ieee.org/document/9460987/
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AT baybarskarabekir energyefficientclusteringbasedmobileroutingalgorithmonwsns
AT abdulhalimzaim energyefficientclusteringbasedmobileroutingalgorithmonwsns
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