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...

Full description

Saved in:
Bibliographic Details
Main Authors: Adekiigbe, Adebanjo, Ahmed, Abdulghani Ali, Sadiq, Ali Safa, Ghafoor, Kayhan Zrar, Kamalrulnizam, Abu Bakar
Format: Article
Language:en
Published: airitilibrary 2017
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/20116/7/fskkp-2017-ahmed-An%20Efficient%20Cluster%20Head1.pdf
http://umpir.ump.edu.my/id/eprint/20116/
http://jit.ndhu.edu.tw/ojs/index.php/jit/article/view/1535
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1831525280688111616
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
building UMPSA Library
collection Institutional Repository
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
continent Asia
country Malaysia
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
id my.ump.umpir.20116
institution Universiti Malaysia Pahang
language en
publishDate 2017
publisher airitilibrary
record_format eprints
spelling my.ump.umpir.201162020-07-03T01:28:50Z 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 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. (Published) http://jit.ndhu.edu.tw/ojs/index.php/jit/article/view/1535
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
title 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_short 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
topic QA75 Electronic computers. Computer science
url http://umpir.ump.edu.my/id/eprint/20116/7/fskkp-2017-ahmed-An%20Efficient%20Cluster%20Head1.pdf
http://umpir.ump.edu.my/id/eprint/20116/
http://jit.ndhu.edu.tw/ojs/index.php/jit/article/view/1535
url_provider http://umpir.ump.edu.my/