TY - GEN
T1 - Towards scalable clustering of infrastructured mobile ad hoc networks
AU - Mahdy, Ahmed M.
AU - Deogun, Jitender S.
AU - Wang, Jun
PY - 2005
Y1 - 2005
N2 - For last several years, much research has been dedicated to the development of a reliable infrastructure for mobile ad hoc networks. A hierarchal approach has been a major player, in this context, especially its clusterhead based scheme. Many techniques have been proposed for the clustering and selection of clusterheads in mobile ad hoc networks. However, almost all techniques use only a single quality measure to distinguish between the capabilities of the nodes in the selection of clusterheads. This bounds the efficiency of the selection process and degrades network performance. In this paper, we present a scalable clustering approach that can generate customizable clustering techniques with as many quality measures as desired. Empirical results show that our clustering method experiences significant improvement on network performance compared to single measure clustering with reductions of up to 31% and 46% on average number of clusterhead switches and energy standard deviation, respectively.
AB - For last several years, much research has been dedicated to the development of a reliable infrastructure for mobile ad hoc networks. A hierarchal approach has been a major player, in this context, especially its clusterhead based scheme. Many techniques have been proposed for the clustering and selection of clusterheads in mobile ad hoc networks. However, almost all techniques use only a single quality measure to distinguish between the capabilities of the nodes in the selection of clusterheads. This bounds the efficiency of the selection process and degrades network performance. In this paper, we present a scalable clustering approach that can generate customizable clustering techniques with as many quality measures as desired. Empirical results show that our clustering method experiences significant improvement on network performance compared to single measure clustering with reductions of up to 31% and 46% on average number of clusterhead switches and energy standard deviation, respectively.
KW - Clusterhead Selection
KW - Clustering
KW - Infrastructure Organization
KW - Mobile Ad Hoc Networks
KW - Scalability
UR - http://www.scopus.com/inward/record.url?scp=33746606104&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33746606104&partnerID=8YFLogxK
U2 - 10.1109/SARNOF.2005.1426516
DO - 10.1109/SARNOF.2005.1426516
M3 - Conference contribution
AN - SCOPUS:33746606104
SN - 0780388542
SN - 9780780388543
T3 - 2005 IEEE/Sarnoff Symposium on Advances in Wired and Wireless Communication
SP - 77
EP - 80
BT - 2005 IEEE/Sarnoff Symposium on Advances in Wired and Wireless Communication
T2 - 2005 IEEE/Sarnoff Symposium on Advances in Wired and Wireless Communication
Y2 - 18 April 2005 through 19 April 2005
ER -