Cluster Density of Dependent Thinning Distributed Clustering Class of Algorithms in Ad Hoc Deployed Wireless Networks
Distributed clustering is widely used in ad hoc deployed wireless networks. Distributed clustering algorithms like DMAC, HEED, MEDIC, ANTCLUST-based, and EDCR produce well-distributed Cluster Heads (CHs) using dependent thinning techniques where a node’s decision to be a CH depends on the decision o...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2012-01-01
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| Series: | Journal of Computer Networks and Communications |
| Online Access: | http://dx.doi.org/10.1155/2012/781275 |
| Summary: | Distributed clustering is widely used in ad hoc deployed
wireless networks. Distributed clustering algorithms like
DMAC, HEED, MEDIC, ANTCLUST-based, and EDCR produce
well-distributed Cluster Heads (CHs) using dependent thinning
techniques where a node’s decision to be a CH depends on the
decision of its neighbors. An analytical technique to determine
the cluster density of this class of algorithms is proposed. This
information is required to set the algorithm parameters before
a wireless network is deployed. Simulation results are presented
in order to verify the analytical findings. |
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| ISSN: | 2090-7141 2090-715X |