Abstract
With technological advancements in 6G and Internet of Things (IoT), the incorporation of Unmanned Aerial Vehicles (UAVs) and cellular networks has become a hot research topic. At present, the proficient evolution of 6G networks allows the UAVs to offer cost-effective and timely solutions for real-time applications such as medicine, tracking, surveillance, etc. Energy efficiency, data collection, and route planning are crucial processes to improve the network communication. These processes are highly difficult owing to high mobility, presence of non-stationary links, dynamic topology, and energy-restricted UAVs. With this motivation, the current research paper presents a novel Energy Aware Data Collection with Routing Planning for 6G-enabled UAV communication (EADCRP-6G) technique. The goal of the proposed EADCRP-6G technique is to conduct energy-efficient cluster-based data collection and optimal route planning for 6G-enabled UAV networks. EADCRP-6G technique deploys Improved Red Deer Algorithm-based Clustering (IRDAC) technique to elect an optimal set of Cluster Heads (CH) and organize these clusters. Besides, Artificial Fish Swarm-based Route Planning (AFSRP) technique is applied to choose an optimum set of routes for UAV communication in 6G networks. In order to validated whether the proposed EADCRP-6G technique enhances the performance, a series of simulations was performed and the outcomes were investigated under different dimensions. The experimental results showcase that the proposed model outperformed all other existing models under different evaluation parameters.
Highlights
In recent times, with the evolution of Internet of Things (IoT) and 6G technologies [1], the incorporation of cellular systems and Unmanned Aerial Vehicles (UAVs) has to shift towards novel network advance trends
In UAVs, the cellular converged network can perform as an aerial Access Node (AP)/Base Station (BS) to collect data from a huge amount of IoT nodes allocated to a specific extent and realize the connections with 6G networks
In order to examine the enhanced performance of EADCRP6G technique, a series of simulations was conducted and the outcomes were investigated under different dimensions
Summary
With the evolution of Internet of Things (IoT) and 6G technologies [1], the incorporation of cellular systems and UAVs has to shift towards novel network advance trends. UAVs has the potential to interact with ground cellular BS It creates a self-organizing cluster network via remote intelligence control framework [3]. The high mobility nature of the UAV causes periodic changes in the topology This requires a recurrent communication of new location among UAV nodes which results in energy utilization on the basis of overheads [7]. The sparse location of UAVs requires high energy for communication, owing to a considerably-longer distance among the UAVs. Smart clustering technique can enact the main role to enhance the energy efficiency of a network. The current research work presents a novel Energy Aware Data Collection with Route Planning for 6G-enabled UAV communication (EADCRP-6G) technique. The goal of the proposed EADCRP-6G technique is to perform energy-efficient cluster-based data collection and optimal route planning for 6G-enabled UAV networks. In order to examine the enhanced performance of EADCRP6G technique, a series of simulations was conducted and the outcomes were investigated under different dimensions
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