IEEE Transactions on Vehicular Technology · Journal article · 2026
Authors: Can Cui, Ziye Jia, Jiahao You, Chao Dong, Qihui Wu, Zhu Han
Published in: IEEE Transactions on Vehicular Technology, vol. 75, no. 3, pp. 4987–5000, Mar. 2026.
Authorship: Coauthor / 合作作者
Research overview
This paper studies energy-efficient UAV edge computing when aerial eavesdroppers and uncertain task demands must both be considered.
The problem
Ground users offload data to service UAVs, while malicious UAVs may overhear transmissions. Secure links, uncertain computation demand, and service-UAV movement must be coordinated.
The approach
A chance-constrained robust optimization model jointly selects connections, offloading ratios, and trajectories. Distributionally robust optimization and conditional value-at-risk yield tractable subproblems, combined with successive convex approximation and block coordinate descent.
Evaluation
Simulations and numerical analyses evaluate energy cost and robustness under the modeled uncertainty and eavesdropping conditions. The original article specifies the security assumptions and comparison settings.
面向空中窃听者的多无人机边缘计算鲁棒安全卸载与轨迹优化
本文研究同时存在空中窃听和任务需求不确定性时的节能无人机边缘计算。
研究问题
地面用户向服务无人机卸载数据时，恶意无人机可能窃听链路。安全通信、不确定计算需求和服务无人机运动需要协同考虑。
研究方法
论文构建带机会约束的鲁棒优化模型，联合选择连接、卸载比例与轨迹；通过分布鲁棒优化和条件风险价值转换问题，再结合连续凸近似与块坐标下降求解。
研究评估
论文通过仿真和数值分析评估所设不确定性与窃听条件下的能耗及鲁棒性。安全假设与对比设置见发表原文。
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, J. You, C. Dong, Q. Wu, and Z. Han, “Robust and secure computation offloading and trajectory optimization for multi-UAV MEC against aerial eavesdropper,” IEEE Trans. Veh. Technol., vol. 75, no. 3, pp. 4987–5000, Mar. 2026, doi: 10.1109/TVT.2025.3612755.
