A comprehensive review of computation offloading in UAV-assisted mobile edge computing for IoT applications

Abstract

Unmanned aerial vehicle (UAV)-based wireless networks have received increasing research interest in recent years and are gradually being utilized in various aspects of our society. Due to the growing demand of UAV applications such as disaster management, plant protection, and environment monitoring, Mobile edge computing (MEC) was introduced to resolve the conflict and the restricted resources of Internet of Thing (IoT) devices. Note that UAV support is crucial for establishing reliable connections in regions lacking or with inadequate communication infrastructure. Combining UAV-assisted communication with MEC has been seen as a potential model shift to handle the increasing demands for big data processing from UAV-aided IoT applications. In this paper, the overall performance of MEC is determined via offloading modeling. We provide a synopsis of all the relevant research on offloading modeling, including both historical developments and more current breakthroughs. First, we present some key aspects of edge computing architecture and then classify the previous works on computation offloading into different categories. Second, an overview of offloading and its metrics, as well as a discussion of UAVs, MEC, collaboration between UAV and MEC, and offloading strategies, methodologies, and factors. The two main categories of offloading strategies are full and partial offloading. Finally, discussion and future research directions related to offloading by UAV is presented.