4 papers
End-to-End Latency-Minimizing and Load-Balanced Request Scheduling for Edge LLM Inference in Agentic AI Services
Zhen Li, Jun Cai, Haoran Gao +2
Large language model (LLM)-powered agentic AI services increasingly demand low-latency inference, motivating the deployment of LLMs across distributed edge servers. However, hetero…
From State Synchronization to Cognitive Self-Evolution: An Operational Architecture for Cognitive Digital Twins
Haoran Gao, An Li, Zhen Li +1
As Digital Twin (DT) systems evolve beyond state synchronization toward task-oriented and knowledge-driven operation, Cognitive Digital Twins (CDTs) have emerged as an extension th…
Joint Optimization of Training and Inference in Federated Edge Learning via Constrained Multi-Objective Deep Reinforcement Learning
Zhen Li, Jun Cai, Chao Yang +1
Federated edge learning (FEEL) has recently emerged as a promising paradigm for achieving edge intelligence (EI) via enabling collaborative model training across edge devices while…
A Novel Collaborative Framework for Efficient Synchronization in Split Federated Learning over Wireless Networks
Haoran Gao, Samuel D. Okegbile, Jun Cai
Split Federated Learning (SFL) offers a promising approach for distributed model training in wireless networks, combining the layer-partitioning advantages of split learning with t…