Performance Improvement of Ad-hoc On-demand Distance Vector (AODV) Routing Protocol Using K-Means Clustering in Flying Ad-hoc Network

Unmanned Aerial Vehicles (UAVs) have significant roles across diverse applications, including surveillance, disaster response, search and rescue, etc. Robust communication protocols are crucial in Flying Ad-hoc Networks (FANETs) to maintain reliable connectivity between UAVs. This research examines enhancements to the Ad-hoc On-demand Distance Vector (AODV) protocol by applying the K-Means Clustering method aiming to optimize communication in FANETs. Through extensive simulations in the ns-3 environment, the proposed approach is evaluated in diverse scenarios that consider factors such as node mobility and network density. The results show that integrating AODV with K-Means Clustering improves network Quality of Service metrics, including throughput, packet delivery ratio, and end-to-end delay. This research contributes insights into the feasibility and advantages of employing clustering techniques in FANETs routing protocol.