Author

Jianxiong Guo

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Sep 2026

Efficient LLM Coserving at the Edge via Resource-Aware Cooperative Scheduling

Large language models (LLMs) are increasingly deployed on edge nodes to support edge intelligence applications. To overcome limited GPU memory, offloading-based methods partition model parameters between the GPU and host memory, enabling inference on commodity hardware. However, deploying a single model instance using...

Zhen-Zheng Li, Zhi-Qing Tang, Jian-Xiong Guo et al. · IEEE Internet of Things Jour... · 0 citations

Open access Aug 2026

Adaptive AI Agent Migration via Generative Diffusion-based Reinforcement Learning in Edge Intelligence Systems

This work introduces a diffusion model as a generative prior to produce high-quality global deployment plans, effectively avoiding the local-optima problem common in conventional reinforcement learning.

Jie Gao, Xing-Dan Wang, Zhi-Qing Tang et al. · Tsinghua Science and Technol... · 0 citations

#edge computing Sep 2026

Efficient Layer-Granularity Unloading for LLMs in Edge Computing

Advancements in edge computing and container technology have made it increasingly popular and convenient to deploy Large Language Models (LLMs) through containers at the edge. However, the limited GPU resources of edge servers make it impractical to retain the model in GPU memory for long periods due to the high memory...

Zhenzheng Li, Zhiqing Tang, Jianxiong Guo et al. · IEEE Transactions on Mobile... · 1 citation