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Energy information and cluster heads the expectation for WSN

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A clustering algorithm based on energy information and cluster heads expectation for wireless sensor networks
Ab s t r a c t
A new method is proposed in this paper to improve Low Energy Adaptive Clustering Hier-
archy (LEACH) by electing cluster heads according to the residual energy of the nodes
dynamically. A sliding window is set up to adjust the electing probability and keep stable
the expected number of the cluster heads using two parameters in this method, one is the
initial energy information of the nodes and the other is the average energy information of
those that have not already been cluster heads in the network. Meanwhile, the number of
cluster heads which is fixed in the entire network lifetime in LEACH is modified to be a var-
iable according to the number of the living nodes. Simulations show that the improvement
for First Node Dies (FND) and Half of the Nodes Alive (HNA) is 41% and 36%, respectively
over LEACH, 17% and 26% for Low Energy Adaptive Clustering Hierarchy with Deterministic
Cluster-Head Selection (LEACH-DCHS), 22% and 21% for Advanced Low Energy Adaptive
Clustering Hierarchy (ALEACH).

Cite As

Wang, Aimin, et al. “A Clustering Algorithm Based on Energy Information and Cluster Heads Expectation for Wireless Sensor Networks.” Computers & Electrical Engineering, vol. 38, no. 3, Elsevier BV, May 2012, pp. 662–71, doi:10.1016/j.compeleceng.2011.11.017.

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