TY - GEN
T1 - Improving clustering techniques in wireless sensor networks using thinning process
AU - Becker, Monique
AU - Gupta, Ashish
AU - Marot, Michel
AU - Singh, Harmeet
PY - 2011/12/1
Y1 - 2011/12/1
N2 - We propose a rapid cluster formation algorithm using a thinning technique : rC-MHP(rapid Clustering inspired from Matérn Hard-Core Process). In order to prove its performance, it is compared with a well known cluster formation heuristic: Max-Min. Experimental results show that rC-MHP outperforms Max-Min in terms of messages needed to choose the cluster head, cluster head maintenance and memory requirement, comprehensively in sparse as well as in dense networks. We show that rC-MHP has a scalable behavior and it is very easy to implement. rC-MHP can be used as an efficient clustering technique.
AB - We propose a rapid cluster formation algorithm using a thinning technique : rC-MHP(rapid Clustering inspired from Matérn Hard-Core Process). In order to prove its performance, it is compared with a well known cluster formation heuristic: Max-Min. Experimental results show that rC-MHP outperforms Max-Min in terms of messages needed to choose the cluster head, cluster head maintenance and memory requirement, comprehensively in sparse as well as in dense networks. We show that rC-MHP has a scalable behavior and it is very easy to implement. rC-MHP can be used as an efficient clustering technique.
U2 - 10.1007/978-3-642-25575-5_17
DO - 10.1007/978-3-642-25575-5_17
M3 - Conference contribution
AN - SCOPUS:84855539306
SN - 9783642255748
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 203
EP - 214
BT - Perform. Eval. Comput. and Comm. Syst.
T2 - IFIP WG 6.3/7.3 International Workshop on Performance Evaluation of Computer and Communication Systems: Milestones and Future Challenges, PERFORM 2010
Y2 - 14 October 2010 through 16 October 2010
ER -