LAUSR

This paper addresses the problem of optimizing the deployment of Flying Backhaul Networks (FBNs). The latter comprise Unmanned Aerial Vehicles (UAVs), which are used as access points to provide coverage to a set of ground nodes deployed in a target area. The optimization problem is addressed by means of a Multi-Objective Optimization Algorithm (MOEA), which calculates Pareto curves of UAV placement, providing different trade-offs between the considered objectives: (1) to minimize the number of UAVs, and (2) to maximize the Packet Delivery Ratio (PDR). The selected MOEA is NSGA-II. An embedded single objective Genetic Algorithm (inner-GA) is used to optimize routing, finding the paths that maximize the PDR. In order to obtain consistent solutions for the PDR taking into account MAC layer contention, the scheme makes use of an existing fixed-point algorithm (FPA). Simulation results were obtained for different scenarios combining average versus maximin PDR objective funtions, two different routing optimization algorithms, as well as single sink versus multiple sink traffic patterns.