CoSMoS: Cooperative Sky-Ground Mobile Edge Computing System

Resource Allocation and 3D Deployment of UAVs-Assisted MEC Network with Air-Ground Cooperation

“…(ii) The energy consumption of TDs and UAVs: In our system model, we aim to minimize the maximum delay among TDs in a novel multi-UAV assisted MEC system. We don’t consider the energy consumption of TDs and UAVs, which can also be feasible in some scenarios which pursue an extremely low delay regardless of energy consumption cost, such as the works [ 9 , 10 , 18 ] in our paper. However, there is some research which focuses on the endurance of both TDs and UAVs, which investigates the minimization of the weighted sum of transmission and hovering energy consumption.…”

“… Related works on UAV-assisted MEC systems. The references are in order from top to bottom: [ 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 ]. …”

“…In [ 17 ], subject to binary offloading strategy, the authors minimized the total energy consumption of UEs by jointly optimizing uplink power control, channel allocation, and computation capacity allocation. With a more effective partial offloading strategy, the authors in [ 18 ] aimed to minimize the maximum delay of TDs by designing a cooperative sky-ground mobile edge computing system, which has a significantly better performance compared to an only UAV-assisted MEC system and ground-only MEC system. In [ 19 ], the authors proposed a weighted computation efficiency maximization framework for MEC systems by jointly optimizing the computation resource scheduling, bandwidth allocation, and UAV’s trajectory, where the benefits of the proposal are more prominent when handling computation intensive latency-critical tasks.…”

“…In [ 19 ], the authors proposed a weighted computation efficiency maximization framework for MEC systems by jointly optimizing the computation resource scheduling, bandwidth allocation, and UAV’s trajectory, where the benefits of the proposal are more prominent when handling computation intensive latency-critical tasks. However, [ 18 , 19 ] are only considered the case of one UAV and investigate the condition that each time slot only services one TD with TDMA. Furthermore, the fixed height restriction of the UAV limited its excellent performance, and simple channel condition assumptions made its results inaccurate.…”

A comprehensive survey on aerial mobile edge computing: Challenges, state-of-the-art, and future directions

“…Thanks to the inherent attributes of UAVs, including the on-demand deployment, low cost, controllable maneuverability, high cruising altitude, and line-of-sight (LoS) connectivity, etc., UAVs acting as aerial MEC platforms can be employed in a wide range of applications varying from civilians to the military for critical operations [6]. Typically, the aerial MEC can work as a complement to the terrestrial MEC networks when the servers embedded in ground base stations (GBSs) are overloaded or unavailable [7,8]. In particular, the LoS connectivity and maneuverability of UAVs is able to significantly reduce the task offloading latency and energy consumption for MEC systems.…”