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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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airitilibrary
2017
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| Online Access: | http://umpir.ump.edu.my/id/eprint/20116/ http://umpir.ump.edu.my/id/eprint/20116/7/fskkp-2017-ahmed-An%20Efficient%20Cluster%20Head1.pdf |
| _version_ | 1848821019643478016 |
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| 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 | UMP Institutional Repository |
| collection | Online Access |
| 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). |
| first_indexed | 2025-11-15T02:18:42Z |
| format | Article |
| id | ump-20116 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T02:18:42Z |
| publishDate | 2017 |
| publisher | airitilibrary |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-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/ http://umpir.ump.edu.my/id/eprint/20116/ http://umpir.ump.edu.my/id/eprint/20116/7/fskkp-2017-ahmed-An%20Efficient%20Cluster%20Head1.pdf |