Joint Optimization of Throughput and Energy Consumption in Microservices-Based UAV Networks

The application of Unmanned Aerial Vehicle (UAV) networks to the coverage problem in rural and low-income areas is actively studied nowadays by the research community. A UAV-based network infrastructure is different from traditional cellular networks relying on Base Stations. By mounting small cells on top of UAVs, coverage can be enhanced in regions where network operators avoid to invest due to the low Return on Investment. In case there is a requirement for an enhanced throughput in a rural area (e.g., users requesting IoT applications with strict QoS requriements), a potential solution is to place several UAV s over the same area, thus maximizing the offered throughput. However, this situation would lead to an increase in the energy consumption. To tackle this problem, this paper proposes an optimal solution to the problem of jointly maximizing the offered throughput in rural scenarios where users request microservice-based IoT applications, while minimizing the energy consumption of the swarm of UAV s. A Mixed Integer Linear Programming (MILP)-based formulation is defined and evaluated over realistic scenarios. Experimental results demonstrate how the solution is able to perform UAV placement in a way to maximize the offered throughput in the highest number of areas, while minimizing the total number of deployed UAVs.