Software Journal:
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Developing the idea of clustering networks of the Internet of things

E.V. Gorina ( Saint-Petersburg State University of Industrial Technologies and Design, St. Petersburg, Russian Federation, ph.d;
F. Bimbetov ( Saint Petersburg Electrotechnical University (Postgraduate Student), St. Petersburg, Russian Federation;
T.M. Tatarnikova ( Saint Petersburg Electrotechnical University, Saint Petersburg State University of Aerospace Instrumentation (Professor), St. Petersburg, Russian Federation, ph.d;

The development of new algorithms, methods and technologies that help reduce energy consumption in Internet of Things networks is a relevant task. Sensor nodes of the Internet of things consume limited energy resources when performing computing operations, receiving and transmitting data. One of the well-known approaches to reduce the energy consumption of sensor nodes is network clustering. The head node of the cluster assumes the functions of a relay of data from sensor nodes.

The paper proposes an algorithm that develops the idea of clustering networks of the Internet of things. The algorithm is based on bee swarm intelligence that assumes determining the current round cluster head and potential heads of clusters for subsequent rounds of the cycle immediately at the be-ginning of the cycle. Thus, the phase of choosing the cluster head node becomes redundant starting from the second round of the cycle, and sensor nodes do not need to perform energy-intensive calcula-tions associated with choosing the cluster head.

The simulation results show the superiority of the bee swarm algorithm in comparison with the well-known LEACH adaptive clustering algorithm with low energy consumption in terms of the duration of a wireless sensor network.