Open Access

ARTICLE

Energy Aware Data Collection with Route Planning for 6G Enabled UAV Communication

Mesfer Al Duhayyim¹, Marwa Obayya², Fahd N. Al-Wesabi^3,4, Anwer Mustafa Hilal^5,*, Mohammed Rizwanullah⁵, Majdy M. Eltahir⁶
1 Department of Natural and Applied Sciences, College of Community-Aflaj, Prince Sattam bin Abdulaziz University, Saudi Arabia
2 Department of Biomedical Engineering, College of Engineering, Princess Nourah bint Abdulrahman University, Saudi Arabia
3 Department of Computer Science, King Khalid University, Muhayel Aseer, Saudi Arabia
4 Faculty of Computer and IT, Sana’a University, Sana’a, Yemen
5 Department of Computer and Self Development, Preparatory Year Deanship, Prince Sattam bin Abdulaziz University, AlKharj, Saudi Arabia
6 Department of Information Systems, King Khalid University, Muhayel Aseer, Saudi Arabia
* Corresponding Author: Anwer Mustafa Hilal. Email:

Computers, Materials & Continua 2022, 71(1), 825-842. https://doi.org/10.32604/cmc.2022.021490

Received 04 July 2021; Accepted 27 August 2021; Issue published 03 November 2021

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.

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Keywords

Unmanned aerial vehicle; 6G networks; artificial intelligence; energy efficiency; clustering; route planning; data collection; metaheuristics

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