Providing Aerial MEC Service in Areas Without Infrastructure: A Tethered-UAV-Based Energy-Efficient Task Scheduling Framework

The evolution of information and communication technology, besides the proliferation of mobile devices, pushes the horizon of the Internet of Things. The main challenges for mobile devices are limited battery power and insufficient computational resources. Multiaccess edge computing (MEC) is an emerging paradigm that can provide task offloading services in the proximity of mobile devices to alleviate their load. In addition, mobile devices cannot work in emergency scenarios (e.g., post-earthquake, post-flood, and post-hurricane) or areas without infrastructure. Tethered unmanned aerial vehicles (UAVs) have received widespread attention as an alternative base station because of their line-of-sight solid links status, flexible deployment, and sufficient energy supply. With this in mind, we propose a tethered-unmanned-aerial-vehicle-based aerial MEC network to provide communication and task offloading services in areas without infrastructure. In addition, an energy-efficient task scheduling framework is proposed to achieve more energy-efficient task scheduling. First, we propose a geometry-based placement algorithm to generate optimal placement positions for the UAV placement problem. Then, for the nonconvex task scheduling and the resource allocation problem, we propose a low complexity divide and conquer scheme, which decomposes the original problem into three subproblems and solves them separately. Extensive simulations demonstrate the better energy efficiency of the proposed framework.