  Network lifetime is always a challenging issue in battery-powered networks
due to the difficulty of recharging or replacing nodes in some scenarios.
Clustering methods are a promising approach to tackle this challenge and
prolong lifetime by efficiently distributing tasks among nodes in the cluster.
The present study aimed to improve energy consumption in heterogeneous IoT
devices using an energy-aware clustering method. In a heterogeneous IoT
network, nodes (i.e., battery-powered IoT devices) can have a variety of energy
profiles and communication capabilities. Most of the existing clustering
algorithms have neglected the heterogeneity of energy capacity among nodes and
assumed that they are of the same energy level. In this work, we present
HetEng, a Cluster Head (CH) selection process that extended an existing
clustering algorithm, named Smart-BEEM. To this end, we proposed a statistical
approach that distributes energy consumption among highly energetic nodes in
the network topology by constantly changing the CH role between the nodes based
on their real energy levels (in joules). Experimental results showed that
HetEng resulted in a 6.6% increase of alive nodes and 3% improvement in
residual energy among the nodes in comparison with SmartBEEM. Moreover, our
method reduced the total number of iterations by 1% on average.
