1 citations · 2 across the 8 of their papers we have counts for
8 papers
Enhancing Mobile Crowdsensing Efficiency: A Coverage-aware Resource Allocation Approach
Yaru Fu, Yue Zhang, Zheng Shi +2
In this study, we investigate the resource management challenges in next-generation mobile crowdsensing networks with the goal of minimizing task completion latency while ensuring…
3D Stochastic Geometry Model for Aerial Vehicle-Relayed Ground-Air-Satellite Connectivity
Yulei Wang, Yalin Liu, Yaru Fu +2
Due to their flexibility, aerial vehicles (AVs), such as unmanned aerial vehicles and airships, are widely employed as relays to assist communications between massive ground users…
Energy-Efficient Federated Learning and Migration in Digital Twin Edge Networks
Yuzhi Zhou, Yaru Fu, Zheng Shi +3
The digital twin edge network (DITEN) is a significant paradigm in the sixth-generation wireless system (6G) that aims to organize well-developed infrastructures to meet the requir…
Joint System Latency and Data Freshness Optimization for Cache-enabled Mobile Crowdsensing Networks
Kexin Shi, Yaru Fu, Yongna Guo +2
Mobile crowdsensing (MCS) networks enable large-scale data collection by leveraging the ubiquity of mobile devices. However, frequent sensing and data transmission can lead to sign…
Sustainable Placement with Cost Minimization in Wireless Digital Twin Networks
Yuzhi Zhou, Yaru Fu, Zheng Shi +3
Digital twin (DT) technology has a high potential to satisfy different requirements of the ever-expanding new applications. Nonetheless, the DT placement in wireless digital twin n…
Age-of-Information and Energy Optimization in Digital Twin Edge Networks
Yongna Guo, Yaru Fu, Yan Zhang +1
In this paper, we study the intricate realm of digital twin synchronization and deployment in multi-access edge computing (MEC) networks, with the aim of optimizing and balancing t…
When Digital Twin Meets 6G: Concepts, Obstacles, and Research Prospects
Wenshuai Liu, Yaru Fu, Zheng Shi +1
The convergence of digital twin technology and the emerging 6G network presents both challenges and numerous research opportunities. This article explores the potential synergies b…
Two-Timescale Synchronization and Migration for Digital Twin Networks: A Multi-Agent Deep Reinforcement Learning Approach
Wenshuai Liu, Yaru Fu, Yongna Guo +3
Digital twins (DTs) have emerged as a promising enabler for representing the real-time states of physical worlds and realizing self-sustaining systems. In practice, DTs of physical…