Zhang, T.K., Chen, C.B., Loo, Jonathan ORCID: https://orcid.org/0000-0002-2197-8126 and Xu, W.J (2023) Joint task scheduling and multi-UAV deployment for aerial computing in emergency communication networks. SCience China Information Sciences, 66. ISSN 1674-733X
PDF (PDF/A)
A.joint_task_scheduling multi-UAV.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Attribution. Download (786kB) |
Abstract
This article studies mobile edge computing technologies enabled by unmanned aerial vehicles (UAVs) in disasters. First, considering that the ground servers may be damaged in emergency scenarios, we proposed an air-ground cooperation architecture based on ad-hoc UAV networks. We defined the system cost as the weighted sum of task delay and energy consumption because of different delay sensitivity and energy sensitivity tasks in emergency communication networks. Then, we formulated the system cost-minimization problem of task scheduling and multi-UAV deployments. To solve the proposed mixed integer nonlinear programming problem, we decomposed it to two sub-problems that were solved by proposing a swap matching-based task scheduling sub-algorithm and a successive convex approximation-based multi-UAV deployment sub-algorithm. Accordingly, we propose a joint optimization algorithm by iterating the two sub-algorithms to obtain a low complexity sub-optimal solution. Finally, the simulation results show that (i) the proposed algorithm converges in several iterations, and (ii) compared with the benchmark algorithms, the proposed algorithm has better performance of reducing task delay and energy consumption and achieves a good trade-off between them for diverse tasks.
Item Type: | Article |
---|---|
Identifier: | 10.1007/s11432-022-3667-3 |
Keywords: | emergency communication, mobile edge computing, swap matching algorithm, unmanned aerial vehicle |
Subjects: | Construction and engineering > Aerospace engineering Computing Construction and engineering |
Depositing User: | Jonathan Loo |
Date Deposited: | 27 Sep 2023 10:26 |
Last Modified: | 04 Nov 2024 11:15 |
URI: | https://repository.uwl.ac.uk/id/eprint/10395 |
Actions (login required)
View Item |