An Efficient Cluster Head Election Algorithm for Client Mesh Networks using Fuzzy Logic Control

Enough attention has not been paid to the client nodes in the wireless mesh networks architecture which tend to also improve quality of service of WMNs if well managed with a cluster structure. In this paper, a fuzzy logic control clustering algorithm (FLCCA) is proposed for client nodes in WMN...

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Main Authors:	Adekiigbe, Adebanjo, Ahmed, Abdulghani Ali, Sadiq, Ali Safa, Ghafoor, Kayhan Zrar, Kamalrulnizam, Abu Bakar
Format:	Article
Language:	English English
Published:	airitilibrary 2017
Subjects:	QA75 Electronic computers. Computer science
Online Access:	http://umpir.ump.edu.my/id/eprint/20116/ http://umpir.ump.edu.my/id/eprint/20116/ http://umpir.ump.edu.my/id/eprint/20116/1/Internet%20echnology.pdf http://umpir.ump.edu.my/id/eprint/20116/7/fskkp-2017-ahmed-An%20Efficient%20Cluster%20Head1.pdf

id	ump-20116
recordtype	eprints
spelling	ump-201162018-10-17T02:48:27Z http://umpir.ump.edu.my/id/eprint/20116/ An Efficient Cluster Head Election Algorithm for Client Mesh Networks using Fuzzy Logic Control Adekiigbe, Adebanjo Ahmed, Abdulghani Ali Sadiq, Ali Safa Ghafoor, Kayhan Zrar Kamalrulnizam, Abu Bakar QA75 Electronic computers. Computer science Enough attention has not been paid to the client nodes in the wireless mesh networks architecture which tend to also improve quality of service of WMNs if well managed with a cluster structure. In this paper, a fuzzy logic control clustering algorithm (FLCCA) is proposed for client nodes in WMNs. A detailed process for the fuzzification of client node parameters used in the selection of optimal cluster heads to obtain low control overheads and highly stable clusters is presented. Three client node parameters considered in our proposal are node mobility speed, traffic delivery capacity and the cost of service with the goals to build stable cluster structure with lowest number of clusters formation and minimize the overhead for the clustering and maintenance. The algorithm applied fuzzy logic control to produce score value for each client nodes based on the three parameters for the cluster heads to be selected. Simulation experiments were conducted to evaluate the performance of FLCCA in terms of the number of clusters formed, reaffiliation count and clustering control overheads. The simulation results show that FLCCA performs better than Distributed Fuzzy Score based Clustering Algorithm (DFSCA). airitilibrary 2017 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/20116/1/Internet%20echnology.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/20116/7/fskkp-2017-ahmed-An%20Efficient%20Cluster%20Head1.pdf Adekiigbe, Adebanjo and Ahmed, Abdulghani Ali and Sadiq, Ali Safa and Ghafoor, Kayhan Zrar and Kamalrulnizam, Abu Bakar (2017) An Efficient Cluster Head Election Algorithm for Client Mesh Networks using Fuzzy Logic Control. Journal of Internet Technology, 18 (5). pp. 1057-1067. ISSN 1607-9264 http://jit.ndhu.edu.tw/ojs/index.php/jit/article/view/1535
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English English
topic	QA75 Electronic computers. Computer science
spellingShingle	QA75 Electronic computers. Computer science Adekiigbe, Adebanjo Ahmed, Abdulghani Ali Sadiq, Ali Safa Ghafoor, Kayhan Zrar Kamalrulnizam, Abu Bakar An Efficient Cluster Head Election Algorithm for Client Mesh Networks using Fuzzy Logic Control
description	Enough attention has not been paid to the client nodes in the wireless mesh networks architecture which tend to also improve quality of service of WMNs if well managed with a cluster structure. In this paper, a fuzzy logic control clustering algorithm (FLCCA) is proposed for client nodes in WMNs. A detailed process for the fuzzification of client node parameters used in the selection of optimal cluster heads to obtain low control overheads and highly stable clusters is presented. Three client node parameters considered in our proposal are node mobility speed, traffic delivery capacity and the cost of service with the goals to build stable cluster structure with lowest number of clusters formation and minimize the overhead for the clustering and maintenance. The algorithm applied fuzzy logic control to produce score value for each client nodes based on the three parameters for the cluster heads to be selected. Simulation experiments were conducted to evaluate the performance of FLCCA in terms of the number of clusters formed, reaffiliation count and clustering control overheads. The simulation results show that FLCCA performs better than Distributed Fuzzy Score based Clustering Algorithm (DFSCA).
format	Article
author	Adekiigbe, Adebanjo Ahmed, Abdulghani Ali Sadiq, Ali Safa Ghafoor, Kayhan Zrar Kamalrulnizam, Abu Bakar
author_facet	Adekiigbe, Adebanjo Ahmed, Abdulghani Ali Sadiq, Ali Safa Ghafoor, Kayhan Zrar Kamalrulnizam, Abu Bakar
author_sort	Adekiigbe, Adebanjo
title	An Efficient Cluster Head Election Algorithm for Client Mesh Networks using Fuzzy Logic Control
title_short	An Efficient Cluster Head Election Algorithm for Client Mesh Networks using Fuzzy Logic Control
title_full	An Efficient Cluster Head Election Algorithm for Client Mesh Networks using Fuzzy Logic Control
title_fullStr	An Efficient Cluster Head Election Algorithm for Client Mesh Networks using Fuzzy Logic Control
title_full_unstemmed	An Efficient Cluster Head Election Algorithm for Client Mesh Networks using Fuzzy Logic Control
title_sort	efficient cluster head election algorithm for client mesh networks using fuzzy logic control
publisher	airitilibrary
publishDate	2017
url	http://umpir.ump.edu.my/id/eprint/20116/ http://umpir.ump.edu.my/id/eprint/20116/ http://umpir.ump.edu.my/id/eprint/20116/1/Internet%20echnology.pdf http://umpir.ump.edu.my/id/eprint/20116/7/fskkp-2017-ahmed-An%20Efficient%20Cluster%20Head1.pdf
first_indexed	2023-09-18T22:28:50Z
last_indexed	2023-09-18T22:28:50Z
_version_	1777416148134920192

An Efficient Cluster Head Election Algorithm for Client Mesh Networks using Fuzzy Logic Control

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