IEEE INFOCOM 2023 – IEEE Conference on Computer Communications Workshops · Conference workshop paper · 2023
Authors: Can Cui, Ziye Jia, Chao Dong, Zhuang Ling, Jiahao You, Qihui Wu
Published in: IEEE INFOCOM 2023 – IEEE Conference on Computer Communications Workshops, Hoboken, NJ, USA, pp. 1–6.
Authorship: Coauthor / 合作作者
DOI: 10.1109/INFOCOMWKSHPS57453.2023.10226027
Research overview
This paper investigates access and power allocation in a hierarchical UAV computing network subject to uncertain channel conditions.
The problem
Environmental disturbances affect UAV antenna gains and introduce channel errors. The network must preserve service quality while controlling the power used by lower-layer data collectors and an upper-layer computing UAV.
The approach
Access selection and power allocation are modeled as a distributionally robust chance-constrained problem. A conditional value-at-risk reformulation converts the difficult constraints into a semidefinite programming form for joint optimization.
Evaluation
Numerical simulations evaluate the proposed algorithm under uncertainty. The workshop paper specifies the uncertainty sets, service constraints, and comparison methods.
面向分层无人机边缘计算的分布鲁棒机会约束优化
本文研究信道条件不确定时，分层无人机计算网络中的接入与功率分配。
研究问题
环境扰动影响无人机天线增益并引入信道误差。网络需要在保证服务质量的同时，控制下层采集节点及上层计算无人机的功率消耗。
研究方法
论文将接入选择与功率分配建模为分布鲁棒机会约束问题，利用条件风险价值将难处理的约束转换为半正定规划形式，进而进行联合优化。
研究评估
论文通过数值仿真评估不确定性条件下的算法效果。具体不确定集、服务约束与对比方法见研讨会原文。
中文题名为便于阅读所作的译名，正式引用请使用英文原题。
Citation
[1] C. Cui, Z. Jia, C. Dong, Z. Ling, J. You, and Q. Wu, “Distributionally robust chance-constrained optimization for hierarchical UAV-based MEC,” in Proc. IEEE Conf. Comput. Commun. Workshops (INFOCOM WKSHPS), Hoboken, NJ, USA, 2023, pp. 1–6, doi: 10.1109/INFOCOMWKSHPS57453.2023.10226027.
