A Distributed Multi-Hop Intra-Clustering Approach Based on Neighbors Two-Hop Connectivity for IoT Networks
Résumé
Under a dense and large IoT network, a star topology where each device
is directly connected to the Internet gateway may cause serious waste of
energy and congestion issues. Grouping network devices into clusters
provides a suitable architecture to reduce the energy consumption and
allows an effective management of communication channels. Although
several clustering approaches were proposed in the literature, most of
them use the single-hop intra-clustering model. In a large network, the
number of clusters increases and the energy draining remains almost the
same as in un-clustered architecture. To solve the problem, several
approaches use the k-hop intra-clustering to generate a reduced number
of large clusters. However, k-hop proposed schemes are, generally,
centralized and only assume the node direct neighbors information which
lack of robustness. In this regard, the present work proposes a
distributed approach for the k-hop intra-clustering called Distributed
Clustering based 2-Hop Connectivity (DC2HC). The algorithm uses the
two-hop neighbors connectivity to elect the appropriate set of cluster
heads and strengthen the clusters connectivity. The objective is to
optimize the set of representative cluster heads to minimize the number
of long range communication channels and expand the network lifetime.
The paper provides the convergence proof of the proposed solution.
Simulation results show that our proposed protocol outperforms similar
approaches available in the literature by reducing the number of
generated cluster heads and achieving longer network lifetime.