College of Computing, Engineering & Construction
Master of Science in Electrical Engineering (MSEE)
NACO controlled Corporate Body
University of North Florida. School of Engineering
Dr. Hemani Kaushal, Ph.D.
Dr. Iman Vakilinia, Ph.D.
Dr. Zornitza Prodanoff, Ph.D.
Dr. Alan Harris, Ph.D.
Dr. William Klostermeyer, Ph.D.
Research on Flying Ad-Hoc Networks (FANETs) has increased due to the availability of Unmanned Aerial Vehicles (UAVs) and the electronic components that control and connect them. Many applications, such as 3D mapping, construction inspection, or emergency response operations could benefit from an application and adaptation of swarm intelligence-based deployments of multiple UAVs. Such groups of cooperating UAVs, through the use of local rules, could be seen as network nodes establishing an ad-hoc network for communication purposes.
One FANET application is to provide communication coverage over an area where communication infrastructure is unavailable. A crucial part of a FANET implementation is computing the optimal position of UAVs to provide connectivity with ground nodes while maximizing geographic span. To achieve optimal positioning of FANET nodes, an adaptation of the Particle Swarm Optimization (PSO) algorithm is proposed. A 3D mobility model is defined by adapting the original PSO algorithm and combining it with a fixed-trajectory initial flight. A Long Range (LoRa) mesh network is used for air-to-air communication, while a Wi-Fi network provides air-to-ground communication to several ground nodes with unknown positions. The optimization problem has two objectives: maximizing coverage to ground nodes and maintaining an end-to-end communication path to a control station, through the UAV mesh. The results show that the hybrid mobility approach performs similarly to the fixed trajectory flight regarding coverage, and outperforms fixed trajectory and PSO-only algorithms in both path maintenance and overall network efficiency, while using fewer UAVs.
Paredes, William David, "Assessing the Performance of a Particle Swarm Optimization Mobility Algorithm in a Hybrid Wi-Fi/LoRa Flying Ad Hoc Network" (2023). UNF Graduate Theses and Dissertations. 1191.
Aeronautical Vehicles Commons, Artificial Intelligence and Robotics Commons, Digital Communications and Networking Commons, Electrical and Electronics Commons, Multi-Vehicle Systems and Air Traffic Control Commons, Navigation, Guidance, Control and Dynamics Commons, Numerical Analysis and Scientific Computing Commons, Programming Languages and Compilers Commons, Systems and Communications Commons, Systems Engineering and Multidisciplinary Design Optimization Commons, Theory and Algorithms Commons