This paper considers task priority and integrates intelligent reflecting surface (IRS) into traditional UAV-MEC to enhance offloading efficiency and indicates that the system utility of the proposed method is dramatically higher than other benchmark schemes under different scenes.
Liang Zhao, Si-Nong Zhang, Huan Zhou et al.· ACM Transactions on Internet...· 0 citations
UAV (unmanned aerial vehicle) and IRS (intelligent reflecting surface) assisted mobile edge computing (MEC) faces low quality of service (QoS) due to the single functionality of UAV and IRS. In response, we propose a simultaneous wireless information and power transfer (SWIPT)-MEC network aided by multi-functional UAV...
Si-Nong Zhang, Liang Zhao, Xing-Wang Li et al.· IEEE Wireless Communications...· 1 citation
Enabling collaborative generative AI (GenAI) inference at the network edge is challenging due to limited caching capacity, heterogeneous computing resources, and highly dynamic, latency-sensitive service demands. In this paper, we investigate the joint optimization of GenAI model caching, inference offloading, and reso...
Liang Zhao, Jing Wei, Huan Zhou et al.· IEEE Transactions on Cogniti...· 0 citations
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