Please use this identifier to cite or link to this item: https://idr.l4.nitk.ac.in/jspui/handle/123456789/7802
Title: ECABBO: Energy-efficient clustering algorithm based on Biogeography optimization for wireless sensor networks
Authors: Nomosudro, P.
Mehra, J.
Naik, C.
Pushparaj, S.D.
Issue Date: 2019
Citation: IEEE Region 10 Annual International Conference, Proceedings/TENCON, 2019, Vol.2019-October, , pp.828-834
Abstract: Cluster-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.
URI: http://idr.nitk.ac.in/jspui/handle/123456789/7802
Appears in Collections:2. Conference Papers

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.