An Improved Sunflower Optimization Algorithm for Cluster Head Selection in the Internet of Things

Due to the widespread of smart devices and services, the Internet of Things (IoT) has gained attention from researchers and is still in constant development. Many challenges face the IoT networks and need to be solved. Reducing energy consumption to increase the network lifetime is the main issue am...

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Autores principales:	Aliaa F. Raslan, Ahmed F. Ali, Ashraf Darwish, H. M. El-Sherbiny
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Cluster head selection Internet of Things (IoT) lèvy flight operator network life time sunflower optimization algorithm (SFO) Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/f6cfcaca96dd42719eaa4aaf5e4661c9
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spelling	oai:doaj.org-article:f6cfcaca96dd42719eaa4aaf5e4661c92021-12-01T00:00:55ZAn Improved Sunflower Optimization Algorithm for Cluster Head Selection in the Internet of Things2169-353610.1109/ACCESS.2021.3126537https://doaj.org/article/f6cfcaca96dd42719eaa4aaf5e4661c92021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9606664/https://doaj.org/toc/2169-3536Due to the widespread of smart devices and services, the Internet of Things (IoT) has gained attention from researchers and is still in constant development. Many challenges face the IoT networks and need to be solved. Reducing energy consumption to increase the network lifetime is the main issue among these challenges. The clustering approach is one of the best solutions to solve this issue. Choosing the best Cluster Heads (CHs) can consume less energy in the IoT-WSN. Swarm Intelligence (SI) algorithms can help to solve complicated problems. In this paper, we propose a novel algorithm to select the best CHs in the IoT-WSN. The novel algorithm is called an Improved Sunflower Optimization Algorithm (ISFO). In the ISFO, we combine the Sunflower Optimization Algorithm (SFO) with the lèvy flight operator. Such invoking can balance the diversification and intensification processes of the proposed algorithm and avoid trapping in local minima. We compare the ISFO algorithm with six SI algorithms. The results of the proposed algorithm show that it can consume less energy than the other algorithms, also the number of nodes still alive for it is larger than alive nodes for the other algorithms. Hence, the ISFO algorithm proved its superiority in reducing the consumed energy and increasing the lifetime of the network.Aliaa F. RaslanAhmed F. AliAshraf DarwishH. M. El-SherbinyIEEEarticleCluster head selectionInternet of Things (IoT)lèvy flight operatornetwork life timesunflower optimization algorithm (SFO)Electrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 156171-156186 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Cluster head selection Internet of Things (IoT) lèvy flight operator network life time sunflower optimization algorithm (SFO) Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Cluster head selection Internet of Things (IoT) lèvy flight operator network life time sunflower optimization algorithm (SFO) Electrical engineering. Electronics. Nuclear engineering TK1-9971 Aliaa F. Raslan Ahmed F. Ali Ashraf Darwish H. M. El-Sherbiny An Improved Sunflower Optimization Algorithm for Cluster Head Selection in the Internet of Things
description	Due to the widespread of smart devices and services, the Internet of Things (IoT) has gained attention from researchers and is still in constant development. Many challenges face the IoT networks and need to be solved. Reducing energy consumption to increase the network lifetime is the main issue among these challenges. The clustering approach is one of the best solutions to solve this issue. Choosing the best Cluster Heads (CHs) can consume less energy in the IoT-WSN. Swarm Intelligence (SI) algorithms can help to solve complicated problems. In this paper, we propose a novel algorithm to select the best CHs in the IoT-WSN. The novel algorithm is called an Improved Sunflower Optimization Algorithm (ISFO). In the ISFO, we combine the Sunflower Optimization Algorithm (SFO) with the lèvy flight operator. Such invoking can balance the diversification and intensification processes of the proposed algorithm and avoid trapping in local minima. We compare the ISFO algorithm with six SI algorithms. The results of the proposed algorithm show that it can consume less energy than the other algorithms, also the number of nodes still alive for it is larger than alive nodes for the other algorithms. Hence, the ISFO algorithm proved its superiority in reducing the consumed energy and increasing the lifetime of the network.
format	article
author	Aliaa F. Raslan Ahmed F. Ali Ashraf Darwish H. M. El-Sherbiny
author_facet	Aliaa F. Raslan Ahmed F. Ali Ashraf Darwish H. M. El-Sherbiny
author_sort	Aliaa F. Raslan
title	An Improved Sunflower Optimization Algorithm for Cluster Head Selection in the Internet of Things
title_short	An Improved Sunflower Optimization Algorithm for Cluster Head Selection in the Internet of Things
title_full	An Improved Sunflower Optimization Algorithm for Cluster Head Selection in the Internet of Things
title_fullStr	An Improved Sunflower Optimization Algorithm for Cluster Head Selection in the Internet of Things
title_full_unstemmed	An Improved Sunflower Optimization Algorithm for Cluster Head Selection in the Internet of Things
title_sort	improved sunflower optimization algorithm for cluster head selection in the internet of things
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/f6cfcaca96dd42719eaa4aaf5e4661c9
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An Improved Sunflower Optimization Algorithm for Cluster Head Selection in the Internet of Things

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