activity
20172022
most citedDigital Twin-Empowered Network Planning for Multi-Tier Computing

30 citations · 63 across the 14 of their papers we have counts for

collaborators

19 papers

cs.NI20221 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.NI202230 cited

Digital Twin-Empowered Network Planning for Multi-Tier Computing

Conghao Zhou, Jie Gao, Mushu Li +3

In this paper, we design a resource management scheme to support stateful applications, which will be prevalent in 6G networks. Different from stateless applications, stateful appl…

cs.NI20213 cited

Slicing-Based AI Service Provisioning on Network Edge

Mushu Li, Jie Gao, Conghao Zhou +3

Edge intelligence leverages computing resources on network edge to provide artificial intelligence (AI) services close to network users. As it enables fast inference and distribute…

cs.NI2021

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…

cs.LG2020

Dynamic RAN Slicing for Service-Oriented Vehicular Networks via Constrained Learning

Wen Wu, Nan Chen, Conghao Zhou +4

In this paper, we investigate a radio access network (RAN) slicing problem for Internet of vehicles (IoV) services with different quality of service (QoS) requirements, in which mu…

cs.NI20201 cited

MAC for Machine Type Communications in Industrial IoT -- Part II: Scheduling and Numerical Results

Jie Gao, Mushu Li, Weihua Zhuang +3

In the second part of this paper, we develop a centralized packet transmission scheduling scheme to pair with the protocol designed in Part I and complete our medium access control…