A fully distributed energy‐aware multi‐level clustering and routing for WSN‐based IoT

One of the major problems in wireless sensor networks (WSNs) is that resource‐constrained sensor nodes consume their limited batteries quickly due to long‐distance data communications. The communication distance of the nodes can be decreased using clustering architectures and multi‐hop data transmis...

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Bibliographic Details
Published inTransactions on emerging telecommunications technologies Vol. 32; no. 12
Main Authors Abasıkeleş‐Turgut, İpek, Altan, Gokhan
Format Journal Article
LanguageEnglish
Published 01.12.2021
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Summary:One of the major problems in wireless sensor networks (WSNs) is that resource‐constrained sensor nodes consume their limited batteries quickly due to long‐distance data communications. The communication distance of the nodes can be decreased using clustering architectures and multi‐hop data transmissions; hence, the lifetime of the network can be increased. In this study, two‐level intra‐cluster and multi‐level inter‐cluster communication are proposed. The coverage area of the second‐level clusters is dynamically determined according to the distance of cluster heads to the BS. Self‐organized nodes in the network designate the clustering ranges, the clusters, and the cluster heads without a central control mechanism using a fully distributed approach. Moreover, with the help of static clustering, the control messages generated by the system are decreased. The proposed approach, FDEAM, is compared with recent approaches in terms of the network lifetime, network energy consumption, cluster head alteration frequency, dead parent statistics, and data collection. The results show that FDEAM outperforms state‐of‐the‐art approaches for all performance metrics. FDEAM is a novel two‐level intra‐cluster and multi‐level inter‐cluster communication approach. It provides self‐organized nodes to designate the clustering ranges, the clusters, and the cluster heads without a central control mechanism using a fully‐distributed approach.
ISSN:2161-3915
2161-3915
DOI:10.1002/ett.4355