Joint optimization of task offloading and resource allocation for UAV swarm-assisted edge computing systems

被引：1
|
作者：
Liu S. [1 ]
Huang Y. [1 ]
Hu H. [1 ]
Si J. [2 ]
Han H. [1 ]
An Q. [1 ]
机构：
[1] College of Information and Navigation, Air Force Engineering University, Xi'an
[2] State Key Laboratory of Integrated Services Network, Xidian University, Xi'an
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2024年 / 46卷 / 02期
关键词：
edge computing; location optimization; resource allocation; task offloading; unmanned aerial vehicle swarm;
D O I：
10.12305/j.issn.1001-506X.2024.02.39
中图分类号：
学科分类号：
摘要：
To improve the performance of unmanned aerial vehicle swarm-assisted edge computing systems under load imbalancing scenarios, a new unmanned aerial vehicle swarm edge computing system is constructed to improve the utilization of computing resources by using offloading data among unmanned aerial vehicle. The weighted sum of the system' s delay and energy consumption are minimized by jointly optimizing the offloading scheme, deployment, and resource allocation of multiple unmanned aerial vehicle. The problem is highly nonconvex, and a two-layer optimization scheme is proposed to solve the problem, i. e., the heuristic optimal evaluation algorithm. The upper layer uses a particle swarm algorithm to optimize the unmanned aerial vehicle locations. The lower layer uses a block coordinate descent algorithm to optimize the unmanned aerial vehicle data offloading and resource allocation under the determined locations. The simulation results show that the proposed scheme can effectively reduce the system cost and has obvious advantages over the benchmark strategies. © 2024 Chinese Institute of Electronics. All rights reserved.
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页码：751 / 760
页数：9
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