ECABBO: Energy-efficient clustering algorithm based on Biogeography optimization for wireless sensor networks

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dc.contributor.authorNomosudro, P.
dc.contributor.authorMehra, J.
dc.contributor.authorNaik, C.
dc.contributor.authorShetty D, D.
dc.date.accessioned2026-02-06T06:37:16Z
dc.date.issued2019
dc.description.abstractCluster-based communication design is an assuring technique in wireless sensor networks to reduce energy consumption and enhance scalability. The requirement of data collection from neighbor nodes, data gathering, and data forwarding to the sink overloads each cluster head. Therefore, it is a highly significant issue to elect a set of optimal cluster heads from the normal sensor nodes. In this paper, the Biogeography Based Optimization for energy-efficient clustering is introduced for cluster head selection. The simulation outcomes show that the algorithm improves the network endurance as compared to other protocols such as Genetic algorithm, Low energy adaptive clustering hierarchy, and Clustered Routing for Selfish Sensors. © 2019 IEEE.
dc.identifier.citationIEEE Region 10 Annual International Conference, Proceedings/TENCON, 2019, Vol.2019-October, , p. 828-834
dc.identifier.issn21593442
dc.identifier.urihttps://doi.org/10.1109/TENCON.2019.8929685
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/30968
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.subjectBiogeography-based optimization
dc.subjectclustering
dc.subjectEnergy consumption
dc.subjectWireless sensor networks
dc.titleECABBO: Energy-efficient clustering algorithm based on Biogeography optimization for wireless sensor networks

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