Energy-Efficient Clustering of UAVs with Crow Search Interaction
10 Pages Posted: 24 Jul 2020
Date Written: July 21, 2020
Abstract
With the advent of the Flying Ad-hoc Networks (FANETs), communication and coordination among UAVs (Unmanned Aerial Vehicles) are the key design challenges witnessed, owing to the unique characteristics of UAVs. The high mobility, dynamic topology, and the limited battery resources of UAVs alleviate the efficacy of the network. In this paper, a Crow Search based clustering scheme is presented addressing the aforementioned issues to improve the overall efficiency and network lifetime of the FANETs. The scheme takes into account the distances among the UAV nodes, residual energy, and the delay constraints for the formation of optimal clusters and its simultaneous election of cluster head. The performance of the clustering scheme is evaluated based on the cluster formation time and the network energy consumption over different deployment areas. The scheme is compared with the conventional Firefly algorithm. The results demonstrated better performance of the presented clustering scheme.
Keywords: UAV, FANET, Crow Search, Clustering, Energy Consumption
JEL Classification: C00,L15
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