Energy-efficient selection of cluster headers in wireless sensor networks

Adem Fanos Jemal, Redwan Hassen Hussen, Do-Yun Kim, Zhetao Li, Tingrui Pei and Young-June Choi

International Journal of Distributed Sensor Networks, 2018, vol. 14, issue 3, 1550147718764642

Abstract: Clustering is vital for lengthening the lives of resource-constrained wireless sensor nodes. In this work, we propose a cluster-based energy-efficient router placement scheme for wireless sensor networks, where the K-means algorithm is used to select the initial cluster headers and then a cluster header with sufficient battery energy is selected within each cluster. The performance of the proposed scheme was evaluated in terms of the energy consumption, end-to-end delay, and packet loss. Our simulation results using the OPNET simulator revealed that the energy consumption of our proposed scheme was better than that of the low-energy adaptive clustering hierarchy, which is known to be an energy-efficient clustering mechanism. Furthermore, our scheme outperformed low-energy adaptive clustering hierarchy in terms of the end-to-end delay, throughput, and packet loss rate.

Keywords: Wireless sensor networks; cluster head selection; energy efficiency; K-means algorithm (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:14:y:2018:i:3:p:1550147718764642

DOI: 10.1177/1550147718764642

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