Title: Clustering algorithm for wireless sensor networks: the honeybee swarms nest-sites selection process based approach

Authors: Ado Adamou Abba Ari; Nabila Labraoui; Blaise Omer Yenké; Abdelhak Gueroui

Addresses: LI-PaRAD Laboratory, Université Paris-Saclay, University of Versailles Saint-Quentin-en-Yvelines, 45, Avenue des États-Unis, 78035 Versailles, France; Faculty of Science, University of Maroua, P.O. Box 814, Maroua, Cameroon ' STIC Laboratory, University of Tlemcen, P.O. Box 230, Chetouane, Tlemcen 13000, Algeria ' LASE Laboratory, University of Ngaoundere, P.O. Box. 455, Ngaoundere, Cameroon ' LI-PaRAD Laboratory, Université Paris-Saclay, University of Versailles Saint-Quentin-en-Yvelines, 45, Avenue des États-Unis, 78035 Versailles, France

Abstract: A cluster-based sensor network with data aggregation on cluster heads is the most popular approach for optimising the energy consumption, in order to maximise the overall network lifetime. Clustering is also used for optimising the quality of service and scalability in sensor networks. In large-scale networks, the management of nodes becomes a challenge. It is therefore necessary that, these sensors act in a self-organised manner to perform tasks. A number of protocols has been proposed. Swarm intelligence based models, inspired by social insects behaviours, provide the most powerful tools that lead to a global intelligence through simple actions in a self-organised manner. In this paper, we proposed a distributed clustering approach called NEST, based on the nest-sites selection process of a honeybee. Extensive experiments have been conducted and the results demonstrated that our algorithm delivers better performance in terms of network lifetime, delivered packets, end-to-end delay, energy consumption and efficiency.

Keywords: WSNs; wireless sensor networks; clustering; cluster head; swarm intelligence; honeybees; NEST.

DOI: 10.1504/IJSNET.2018.092101

International Journal of Sensor Networks, 2018 Vol.27 No.1, pp.1 - 13

Received: 07 Mar 2016
Accepted: 03 Sep 2016
Published online: 04 Jun 2018 *

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