activity
20182025
most citedEnergy-Efficient UAV-Assisted Mobile Edge Computing: Resource Allocation and Trajectory Optimization

501 citations · 908 across the 19 of their papers we have counts for

collaborators

19 papers

cs.NI2025

Drift-Adaptive Slicing-Based Resource Management for Cooperative ISAC Networks

Shisheng Hu, Jie Gao, Xue Qin +5

In this paper, we propose a novel drift-adaptive slicing-based resource management scheme for cooperative integrated sensing and communication (ISAC) networks. Particularly, we est…

cs.DC2024★ 30 cited

Adaptive Device-Edge Collaboration on DNN Inference in AIoT: A Digital Twin-Assisted Approach

Shisheng Hu, Mushu Li, Jie Gao +2

Device-edge collaboration on deep neural network (DNN) inference is a promising approach to efficiently utilizing network resources for supporting artificial intelligence of things…

cs.NI2023

Digital Twin-Based User-Centric Edge Continual Learning in Integrated Sensing and Communication

Shisheng Hu, Jie Gao, Xinyu Huang +5

In this paper, we propose a digital twin (DT)-based user-centric approach for processing sensing data in an integrated sensing and communication (ISAC) system with high accuracy an…

cs.NI2023★ 22 cited

Digital Twin-based 3D Map Management for Edge-assisted Device Pose Tracking in Mobile AR

Conghao Zhou, Jie Gao, Mushu Li +3

Edge-device collaboration has the potential to facilitate compute-intensive device pose tracking for resource-constrained mobile augmented reality (MAR) devices. In this paper, we…

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★ 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★ 3 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.IT2021★ 92 cited

Collaborative Multi-Resource Allocation in Terrestrial-Satellite Network Towards 6G

Shu Fu, Jie Gao, Lian Zhao

Terrestrial-satellite networks are envisioned to play a significant role in the sixth-generation (6G) wireless networks. In such networks, hot air balloons are useful as they can r…

cs.NI2020★ 1 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…

cs.NI2020

MAC for Machine Type Communications in Industrial IoT -- Part I: Protocol Design and Analysis

Jie Gao, Weihua Zhuang, Mushu Li +3

In this two-part paper, we propose a novel medium access control (MAC) protocol for machine-type communications in the industrial internet of things. The considered use case featur…

eess.SY2020★ 254 cited

Deep Reinforcement Learning for Collaborative Edge Computing in Vehicular Networks

Mushu Li, Jie Gao, Lian Zhao +1

Mobile edge computing (MEC) is a promising technology to support mission-critical vehicular applications, such as intelligent path planning and safety applications. In this paper,…

cs.NI2020★ 501 cited

Energy-Efficient UAV-Assisted Mobile Edge Computing: Resource Allocation and Trajectory Optimization

Mushu Li, Nan Cheng, Jie Gao +4

In this paper, we study unmanned aerial vehicle (UAV) assisted mobile edge computing (MEC) with the objective to optimize computation offloading with minimum UAV energy consumption…

cs.NI2020★ 2 cited

Low-Latency and Fresh Content Provision in Information-Centric Vehicular Networks

Shan Zhang, Junjie Li, Hongbin Luo +4

In this paper, the content service provision of information-centric vehicular networks (ICVNs) is investigated from the aspect of mobile edge caching, considering the dynamic drivi…

cs.NI2020

The Design of Dynamic Probabilistic Caching with Time-Varying Content Popularity

Jie Gao, Shan Zhang, Lian Zhao +2

In this paper, we design dynamic probabilistic caching for the scenario when the instantaneous content popularity may vary with time while it is possible to predict the average con…

cs.OS2019

The Study of Dynamic Caching via State Transition Field -- the Case of Time-Varying Popularity

Jie Gao, Lian Zhao, Xuemin +1

In the second part of this two-part paper, we extend the study of dynamic caching via state transition field (STF) to the case of time-varying content popularity. The objective of…

cs.OS2019★ 1 cited

The Study of Dynamic Caching via State Transition Field -- the Case of Time-Invariant Popularity

Jie Gao, Lian Zhao, Xuemin +1

This two-part paper investigates cache replacement schemes with the objective of developing a general model to unify the analysis of various replacement schemes and illustrate thei…

eess.SY2019

Contention Intensity based Distributed Coordination for V2V Safety Message Broadcast

Jie Gao, Mushu Li, Lian Zhao +2

In this paper, we propose a contention intensity based distributed coordination (CIDC) scheme for safety message broadcast. By exploiting the high-frequency and periodical features…

cs.GT2019

Network Utility Maximization based on Incentive Mechanism for Truthful Reporting of Local Information

Jie Gao, Lian Zhao, Xuemin +1

Classic network utility maximization problems are usually solved assuming all information is available, implying that information not locally available is always truthfully reporte…

cs.NI2018

SMDP-based Downlink Packet Scheduling Scheme for Solar Energy Assisted Heterogeneous Networks

Qizhen Li, Jie Gao, Jinming Wen +3

Renewable energy assisted heterogeneous networks can improve system capacity and reduce conventional energy consumption. In this paper, we propose a semi-Markov decision process (S…