Genetic Algorithms for Swarm UAV-Assisted Edge Content Delivery Optimisation Problem

Swarm unmanned aerial vehicles (UAV) have been increasingly studied for delivering the contents in 6G networks. In this paper, we propose an energy-aware capacity and trajectory (ECT) optimisation solution for swarm UAV-assisted edge content delivery networks (eCDN). The ECT optimisation solution enables a swarm UAV system to cooperatively fly 1) to the optimal set of stops and serve the user equipments in different clusters at maximum content delivery capacity and 2) in the optimal trajectory planning at minimum distance, under the constraint of energy resource. However, the ECT optimisation problem is challenging due to multiple objectives with respect to different optimisation variable types and complicated constraints. Genetic algorithms (GA) are therefore modified to address the challenge of solving the so-called multi-objective optimisation problem feasibly. Simulation results are shown to demonstrate the feasibility of GA and the benefits of ECT method for swarm UAV-assisted eCDN.