Air-Ground Integrated Mobile Edge Networks: Architecture, Challenges, and Opportunities

Abstract

The ever-increasing mobile data demands have posed significant challenges in the current radio access networks, while the emerging computation-heavy Internet of things (IoT) applications with varied requirements demand more flexibility and resilience from the cloud/edge computing architecture. In this article, to address the issues, we propose a novel air-ground integrated mobile edge network (AGMEN), where UAVs are flexibly deployed and scheduled, and assist the communication, caching, and computing of the edge network. In specific, we present the detailed architecture of AGMEN, and investigate the benefits and application scenarios of drone-cells, and UAV-assisted edge caching and computing. Furthermore, the challenging issues in AGMEN are discussed, and potential research directions are highlighted.

Mobile Edge Computing in Unmanned Aerial Vehicle Networks

“…The role of the UAV Operation modes Contributions [3] User with computation task Partial offloading Cost minimization [4] User with computation task Partial offloading Cost minimization [5] User with computation task Partial offloading Completion time minimization [6] MEC server executing computation Partial offloading Architecture establishment [7] MEC server executing computation Partial offloading Energy consumption minimization [8] MEC server executing computation Partial offloading Energy consumption minimization [9] MEC server executing computation Partial offloading and binary computation Computation bits maximization [10] Relay offloading computation task Partial offloading Offloading bits maximization are assumed to hover in the sky and their trajectories are not optimized. Different from the works in [3] and [4], the authors in [5] proposed a resource allocation strategy that jointly optimizes the trajectory of the UAV and the offloading time in order to minimize the mission completion time of the UAV.…”

“…In [6]- [9], the second UAV-enabled MEC architecture was studied, where the UAV is identified as the MEC server for providing computing services to the ground users. In particular, the authors in [6] established an UAV-enabled MEC architecture. The UAV can be flexibly deployed and scheduled to assist the communication, caching, and computing of the ground networks.…”

“…The research and development on UAV-enabled MEC networks are still in their early stage and there have been very limited investigations along this direction [6]- [10]. In [6], an UAV-enabled MEC architecture was presented, which the UAV can be flexibly deployed and scheduled to assist the communication, caching, and computing of the ground networks. The authors in [6] only presented the challenges of the proposed UAV-enabled MEC architecture.…”

Lightweight Simulation of Hybrid Aerial- and Ground-Based Vehicular Communication Networks

“…1. As a consequence, ITS-based mobility management and communication systems will be required to support heterogeneous vehicle classes, which raises new challenges for both domains [3].…”

3D Multi-Drone-Cell Trajectory Design for Efficient IoT Data Collection

“…In the future Internet-of-things (IoT), the IoT devices are foreseen to be widely deployed to collect the data required by a myriad of applications. However, in certain areas where the terrestrial network coverage is unavailable due to signal blockage, spectrum scarcity or low IoT transmit power, collecting the IoT data becomes a challenging issue [1]. Although such an issue can be alleviated through densely deploying massive BSs or small-cells, the prohibitive capital expenditure (CapEx) and operating expenditure (OpEx) are unacceptable for IoT operators.…”