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

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.

A Route Planning Method for UAV Swarm Inspection of Roads Fusing Distributed Droneport Site Selection

“…Subsequently, leveraging this foundational information and considering the prevailing road network infrastructure, we embark on the meticulous planning of daily inspection routes for our fleet of UAVs. While extant literature has presented a plethora of studies concerning real-time route planning for UAV fleets [4][5][6][7] and offline planning methodologies [8][9][10][11], these endeavors, regrettably, have failed to incorporate the judicious selection of distributed droneport sites as an optimization objective. Moreover, they have largely neglected the critical issue of achieving equilibrium in UAV utilization.…”

“…The former refers to planning and updating the routes when the UAV swarm is working, and the latter refers to planning the complete routes before the UAV swarm moves. Pertaining to the UAV swarm real-time route planning, AI Duhayyim, M. et al [4] applied the 6G UAV communication routing planning technology to enable the UAVs to efficiently collect data and plan the routes. Lee, M.-T. et al [5] applied the edge computing system to provide the UAVs a higher level of autonomous control, which enabled the UAVs to be more flexible to automatically adapt to the dynamic changes of the environment.…”

A Review and Bibliometric Analysis of the Current Studies for the 6G Networks

“…This results in more efficient use of network resources and improved network performance. One of the main benefits of SDN in 6G networks is the ability to create virtual networks within a shared physical network infrastructure through network slicing [139][140][141]. This allows for dedicated resources for specific use cases or applications, improving network efficiency and supporting new and innovative use cases [14,142,143].…”