Clustering algorithm for wireless sensor networks: the honeybee swarms nest-sites selection process based approach. (2018)

• Record Type: Journal Article
• Authors: Ari, Ado Adamou Abba; Labraoui, Nabila; Yenké, Blaise Omer; Gueroui, Abdelhak
• Is Part Of: International journal of sensor networks. Volume 27:Number 1(2018)
• Page Start: 1
• Page End: 13
• Publication Date: 2018
• Subjects: WSNs -- wireless sensor networks -- clustering -- cluster head -- swarm intelligence -- honeybees -- NEST; Sensor networks -- Periodicals; 681.2
• Languages: English
• ISSNs: 1748-1279

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.