A Quality of Service Driven Approach for Clustering in Mobile Ad hoc Networks Based on Metrics Adaptation: Looking Beyond Clustering
Recently, research topics are focusing on clustering approaches for Ad hoc networks due to their effectiveness in building a virtual backbone formed by a set of suitableclusterheads (CH) to guarantee the communications acrossclusters. In this paper, we propose a clustering approach to elect suitable...
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Croatian Communications and Information Society (CCIS)
2008-12-01
|
Series: | Journal of Communications Software and Systems |
Subjects: | |
Online Access: | https://jcomss.fesb.unist.hr/index.php/jcomss/article/view/215 |
_version_ | 1828470804094910464 |
---|---|
author | Zouhair El-Bazzal Michel Kadoch Basile L. Agba Mohamad Haidar François Gagnon |
author_facet | Zouhair El-Bazzal Michel Kadoch Basile L. Agba Mohamad Haidar François Gagnon |
author_sort | Zouhair El-Bazzal |
collection | DOAJ |
description | Recently, research topics are focusing on clustering approaches for Ad hoc networks due to their effectiveness in building a virtual backbone formed by a set of suitableclusterheads (CH) to guarantee the communications acrossclusters. In this paper, we propose a clustering approach to elect suitable nodes’ representatives and to store minimum topology information by reducing the propagation of routing information which facilitates the spatial reuse of resource and increase the system capacity. The clusters must adapt dynamically to the environment changes, we also propose a distributed maintenance procedure that allows managing nodes’ adhesion, nodes’ handoff and CHs’ re-election. Based on our analytical model used to estimate the quality of service (QoS) parameters, we implement an admission control algorithm to determine the number of members inside a cluster that can be accommodated while satisfying the constraints imposed by the current applications. This might effectively drive congestion avoidance on the CH andinterclusters load-balancing to achieve better network resource utilization. The obtained results will help us to readjust the clustering algorithm metrics in order to provide better maintenance and QoS guarantees depending on the used applications. Through numerical analysis and simulations, we have studied the performance of our model and compared it with that of other existing algorithms. The results demonstrate better performance in terms of number of clusters, number of handoffs, number of transitions (state change) on CHs, QoS parameters, load balancing and scalability. We also observed how the connectivity and the stability are maximized when the number of nodes increases in presence of the mobility. |
first_indexed | 2024-12-11T05:00:56Z |
format | Article |
id | doaj.art-fe6b40590e70435fbb1e19e9f35485e3 |
institution | Directory Open Access Journal |
issn | 1845-6421 1846-6079 |
language | English |
last_indexed | 2024-12-11T05:00:56Z |
publishDate | 2008-12-01 |
publisher | Croatian Communications and Information Society (CCIS) |
record_format | Article |
series | Journal of Communications Software and Systems |
spelling | doaj.art-fe6b40590e70435fbb1e19e9f35485e32022-12-22T01:20:10ZengCroatian Communications and Information Society (CCIS)Journal of Communications Software and Systems1845-64211846-60792008-12-0144254265A Quality of Service Driven Approach for Clustering in Mobile Ad hoc Networks Based on Metrics Adaptation: Looking Beyond ClusteringZouhair El-BazzalMichel KadochBasile L. AgbaMohamad HaidarFrançois GagnonRecently, research topics are focusing on clustering approaches for Ad hoc networks due to their effectiveness in building a virtual backbone formed by a set of suitableclusterheads (CH) to guarantee the communications acrossclusters. In this paper, we propose a clustering approach to elect suitable nodes’ representatives and to store minimum topology information by reducing the propagation of routing information which facilitates the spatial reuse of resource and increase the system capacity. The clusters must adapt dynamically to the environment changes, we also propose a distributed maintenance procedure that allows managing nodes’ adhesion, nodes’ handoff and CHs’ re-election. Based on our analytical model used to estimate the quality of service (QoS) parameters, we implement an admission control algorithm to determine the number of members inside a cluster that can be accommodated while satisfying the constraints imposed by the current applications. This might effectively drive congestion avoidance on the CH andinterclusters load-balancing to achieve better network resource utilization. The obtained results will help us to readjust the clustering algorithm metrics in order to provide better maintenance and QoS guarantees depending on the used applications. Through numerical analysis and simulations, we have studied the performance of our model and compared it with that of other existing algorithms. The results demonstrate better performance in terms of number of clusters, number of handoffs, number of transitions (state change) on CHs, QoS parameters, load balancing and scalability. We also observed how the connectivity and the stability are maximized when the number of nodes increases in presence of the mobility.https://jcomss.fesb.unist.hr/index.php/jcomss/article/view/215Ad hoc networksclustersmaintenancequality of servicescalability |
spellingShingle | Zouhair El-Bazzal Michel Kadoch Basile L. Agba Mohamad Haidar François Gagnon A Quality of Service Driven Approach for Clustering in Mobile Ad hoc Networks Based on Metrics Adaptation: Looking Beyond Clustering Journal of Communications Software and Systems Ad hoc networks clusters maintenance quality of service scalability |
title | A Quality of Service Driven Approach for Clustering in Mobile Ad hoc Networks Based on Metrics Adaptation: Looking Beyond Clustering |
title_full | A Quality of Service Driven Approach for Clustering in Mobile Ad hoc Networks Based on Metrics Adaptation: Looking Beyond Clustering |
title_fullStr | A Quality of Service Driven Approach for Clustering in Mobile Ad hoc Networks Based on Metrics Adaptation: Looking Beyond Clustering |
title_full_unstemmed | A Quality of Service Driven Approach for Clustering in Mobile Ad hoc Networks Based on Metrics Adaptation: Looking Beyond Clustering |
title_short | A Quality of Service Driven Approach for Clustering in Mobile Ad hoc Networks Based on Metrics Adaptation: Looking Beyond Clustering |
title_sort | quality of service driven approach for clustering in mobile ad hoc networks based on metrics adaptation looking beyond clustering |
topic | Ad hoc networks clusters maintenance quality of service scalability |
url | https://jcomss.fesb.unist.hr/index.php/jcomss/article/view/215 |
work_keys_str_mv | AT zouhairelbazzal aqualityofservicedrivenapproachforclusteringinmobileadhocnetworksbasedonmetricsadaptationlookingbeyondclustering AT michelkadoch aqualityofservicedrivenapproachforclusteringinmobileadhocnetworksbasedonmetricsadaptationlookingbeyondclustering AT basilelagba aqualityofservicedrivenapproachforclusteringinmobileadhocnetworksbasedonmetricsadaptationlookingbeyondclustering AT mohamadhaidar aqualityofservicedrivenapproachforclusteringinmobileadhocnetworksbasedonmetricsadaptationlookingbeyondclustering AT francoisgagnon aqualityofservicedrivenapproachforclusteringinmobileadhocnetworksbasedonmetricsadaptationlookingbeyondclustering AT zouhairelbazzal qualityofservicedrivenapproachforclusteringinmobileadhocnetworksbasedonmetricsadaptationlookingbeyondclustering AT michelkadoch qualityofservicedrivenapproachforclusteringinmobileadhocnetworksbasedonmetricsadaptationlookingbeyondclustering AT basilelagba qualityofservicedrivenapproachforclusteringinmobileadhocnetworksbasedonmetricsadaptationlookingbeyondclustering AT mohamadhaidar qualityofservicedrivenapproachforclusteringinmobileadhocnetworksbasedonmetricsadaptationlookingbeyondclustering AT francoisgagnon qualityofservicedrivenapproachforclusteringinmobileadhocnetworksbasedonmetricsadaptationlookingbeyondclustering |