UAV-Enabled Mobile Edge-Computing for IoT Based on AI: A Comprehensive Review

Abstract

Unmanned aerial vehicles (UAVs) are becoming integrated into a wide range of modern IoT applications. The growing number of networked IoT devices generates a large amount of data. However, processing and memorizing this massive volume of data at local nodes have been deemed critical challenges, especially when using artificial intelligence (AI) systems to extract and exploit valuable information. In this context, mobile edge computing (MEC) has emerged as a way to bring cloud computing (CC) processes within reach of users, to address computation-intensive offloading and latency issues. This paper provides a comprehensive review of the most relevant research works related to UAV technology applications in terms of enabled or assisted MEC architectures. It details the utility of UAV-enabled MEC architecture regarding emerging IoT applications and the role of both deep learning (DL) and machine learning (ML) in meeting various limitations related to latency, task offloading, energy demand, and security. Furthermore, throughout this article, the reader gains an insight into the future of UAV-enabled MEC, the advantages and the critical challenges to be tackled when using AI.

UAV Computing-Assisted Search and Rescue Mission Framework for Disaster and Harsh Environment Mitigation

“…[21] Air learning for autonomous UAVs × × × (2021) [22] FL for scheduling and power allocation cooperation of UAV swarms × × × (2020) [24] Challenges and architecture of decentralized FL in UAV networks × × × (2021) [26] Securing data sharing for UAV computing networks × × × × (2021) [27] Performance of FL for edge-assisted UAV networks with data sharing × × × (2020) [29] UAV-enabled edge computing to support IoT devices × × (2021) [28] Combination of FL and Blockchain for drone edge intelligence over × × (2021) smart environments…”

“…In addition, UAVs' ability to fly closer to the disaster locations and surroundings with IoT devices and SAR makes them a critical disaster management choice. Yazid et al [29] introduced UAVs to enable mobile computing with intelligence in several applications.…”

Computing in the Sky: A Survey on Intelligent Ubiquitous Computing for UAV-Assisted 6G Networks and Industry 4.0/5.0

“…However, UAV-assisted relaying was not taken into account. The authors of [33] studied ML and DLbased strategies in UAV-enabled MEC networks. However, the authors of [24] introduced Federated DL (FDL) for UAVs in wireless communication networks.…”

“…UAVs have recently gained a lot of interest in various applications, including delivery, agriculture, emergency response, communication services [77], and mars exploration [154]. The authors of [33] evaluated UAV mobile edge computing for upcoming IoT applications and the role of ML and DL in overcoming latency, job offloading, energy demand, and security constraints. Below, we provide a range of application domains where UAV edge computing could be used, as also shown in Figure 6.…”

Integrating LoRa-Based Communications into Unmanned Aerial Vehicles for Data Acquisition from Terrestrial Beacons

“…WSNs combine a wide range of different types of devices and are the cornerstone of all IoT systems [10]. However, this technology is not exempt from problems, and one of the challenges in this field is the application of IoT technology in large areas, where devices can be scattered, far apart from each other, and where communication coverage can also be poor or even null [11]. Some proposed solutions to address this issue are based on the application of cellular or satellite communication; however, these alternatives are very complex and expensive [12].…”