Compressive sensing (CS)
can reduce the number of data transmissions and balance the traffic
load throughout networks. However, the total number of transmissions
for data collection by using pure CS is still large. The hybrid
method of using CS was proposed to reduce the number of transmissions
in sensor networks. However, the previous works use the CS method on
routing trees. In this paper, we propose a clustering method that
uses hybrid CS for sensor networks. The sensor nodes are organized
into clusters. Within a cluster, nodes transmit data to cluster head
(CH) without using CS. CHs use CS to transmit data to sink. We first
propose an analytical model that studies the relationship between the
size of clusters and number of transmissions in the hybrid CS method,
aiming at finding the optimal size of clusters that can lead to
minimum number of transmissions. Then, we propose a centralized
clustering algorithm based on the results obtained from the
analytical model. Finally, we present a distributed implementation of
the clustering method. Extensive simulations confirm that our method
can reduce the number of transmissions significantly
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