A cooperative approach for content caching and delivery in UAV-assisted vehicular networks

Abstract

Given the advent of Intelligent Transportation Systems (ITSs), drivers and passengers could now spend more of their time enjoying entertainment applications, e.g., watching TV or streaming movies. However, such services can drastically increase the traffic load on the existing network infrastructure (i.e. Roadside Units (RSU) and Cellular Base Stations (CBS)). Recently, Unmanned Aerial Vehicles (UAVs) have been playing a remarkable role in offloading terrestrial networks and providing cellular services thanks to their agility and flexibility. Hence, this paper explores a cooperative approach for content caching and delivery in the context of internet of connected vehicles, where a RSU, having access to a library of contents but with limited communication coverage, collaborates with a UAV to deliver contents to vehicles on a road segment. In this context, the connected RSU is responsible for delivering contents to the UAV cache unit by leveraging passing by vehicles. The RSU loads the contents on these vehicles that in turn upload them to the UAV cache unit. We model this cooperation problem mathematically as a mixed integer non-linear programming (MINLP) problem with the objective to maximize the number of served vehicles. Owing to the complexity of solving this problem, it is alternatively cast as an MDP whose solution is obtained through a Dual-Task Reinforcement Learning method (DTDRL). Simulation results show the superiority of our proposed collaborative solution over non-collaborative methods.