3 papers
cs.NI2023
When Computing Power Network Meets Distributed Machine Learning: An Efficient Federated Split Learning Framework
Xinjing Yuan, Lingjun Pu, Lei Jiao +3
In this paper, we advocate CPN-FedSL, a novel and flexible Federated Split Learning (FedSL) framework over Computing Power Network (CPN). We build a dedicated model to capture the…
cs.NI2020
Cost-efficient and Skew-aware Data Scheduling for Incremental Learning in 5G Network
Lingjun Pu, Xinjing Yuan, Xiaohang Xu +3
To facilitate the emerging applications in 5G networks, mobile network operators will provide many network functions in terms of control and prediction. Recently, they have recogni…
cs.NI2016
Content Retrieval At the Edge: A Social-aware and Named Data Cooperative Framework
Lingjun Pu, Xu Chen, Jingdong Xu +1
Recent years with the popularity of mobile devices have witnessed an explosive growth of mobile multimedia contents which dominate more than 50\% of mobile data traffic. This signi…