Traffic-aware Gateway Placement and Queue Management in Flying Networks

TL;DR

This paper introduces a traffic-aware algorithm for optimal placement of flying gateways and queue management in UAV-based networks, significantly improving QoS by leveraging UAV positions and traffic demands.

Contribution

It presents a novel GPQM algorithm that optimizes gateway placement and queue sizes in flying networks based on traffic demand and UAV positions.

Findings

Significant QoS improvements demonstrated in ns-3 simulations.

Enhanced aggregate throughput and stochastic delay guarantees achieved.

Effective traffic-aware placement outperforms traditional methods.

Abstract

Unmanned Aerial Vehicles (UAVs) have emerged as adequate platforms to carry communications nodes, including Wi-Fi Access Points and cellular Base Stations. This has led to the concept of flying networks composed of UAVs as a flexible and agile solution to provide on-demand wireless connectivity anytime, anywhere. However, state of the art works have been focused on optimizing the placement of the access network providing connectivity to ground users, overlooking the backhaul network design. In order to improve the overall Quality of Service (QoS) offered to ground users, the placement of Flying Gateways (FGWs) and the size of the queues configured in the UAVs need to be carefully defined to meet strict performance requirements. The main contribution of this article is a traffic-aware gateway placement and queue management (GPQM) algorithm for flying networks. GPQM takes advantage of knowing in advance the positions of the UAVs and their traffic demand to determine the FGW position and the queue size of the UAVs, in order to maximize the aggregate throughput and provide stochastic delay guarantees. GPQM is evaluated by means of ns-3 simulations, considering a realistic wireless channel model. The results demonstrate significant gains in the QoS offered when GPQM is used.