activity
20202023
most citedAI-Native Network Slicing for 6G Networks

20 citations · 23 across the 5 of their papers we have counts for

collaborators

5 papers

cs.NI2023★ 1 cited

Holistic Network Virtualization and Pervasive Network Intelligence for 6G

Xuemin, Shen, Jie Gao +4

In this tutorial paper, we look into the evolution and prospect of network architecture and propose a novel conceptual architecture for the 6th generation (6G) networks. The propos…

cs.NI2022

Cost-Effective Two-Stage Network Slicing for Edge-Cloud Orchestrated Vehicular Networks

Wen Wu, Kaige Qu, Peng Yang +4

In this paper, we study a network slicing problem for edge-cloud orchestrated vehicular networks, in which the edge and cloud servers are orchestrated to process computation tasks…

cs.NI2022★ 1 cited

Digital Twin-Driven Computing Resource Management for Vehicular Networks

Mushu Li, Jie Gao, Conghao Zhou +3

This paper presents a novel approach for computing resource management of edge servers in vehicular networks based on digital twins and artificial intelligence (AI). Specifically,…

cs.NI2021★ 20 cited

AI-Native Network Slicing for 6G Networks

Wen Wu, Conghao Zhou, Mushu Li +6

With the global roll-out of the fifth generation (5G) networks, it is necessary to look beyond 5G and envision the 6G networks. The 6G networks are expected to have space-air-groun…

math.OC2020★ 1 cited

On the Convergence of Quantized Parallel Restarted SGD for Central Server Free Distributed Training

Feijie Wu, Shiqi He, Yutong Yang +4

Communication is a crucial phase in the context of distributed training. Because parameter server (PS) frequently experiences network congestion, recent studies have found that tra…