79 citations · 159 across the 6 of their papers we have counts for
6 papers
Velocity-adaptive Access Scheme for MEC-assisted Platooning Networks: Access Fairness Via Data Freshness
Qiong Wu, Ziyang Wan, Qiang Fan +2
Platooning strategy is an important part of autonomous driving technology. Due to the limited resource of autonomous vehicles in platoons, mobile edge computing (MEC) is usually us…
Differential Privacy Meets Federated Learning under Communication Constraints
Nima Mohammadi, Jianan Bai, Qiang Fan +3
The performance of federated learning systems is bottlenecked by communication costs and training variance. The communication overhead problem is usually addressed by three communi…
Delay Sensitive Task Offloading in the 802.11p Based Vehicular Fog Computing Systems
Qiong Wu, Hanxu Liu, Ruhai Wang +3
Vehicular fog computing (VFC) is envisioned as a promising solution to process the explosive tasks in autonomous vehicular networks. In the VFC system, task offloading is the key t…
Time-dependent Performance Analysis of the 802.11p-based Platooning Communications Under Disturbance
Qiong Wu, Hongmei Ge, Pingyi Fan +3
Platooning is a critical technology to realize autonomous driving. Each vehicle in platoons adopts the IEEE 802.11p standard to exchange information through communications to maint…
Federated Learning in Mobile Edge Computing: An Edge-Learning Perspective for Beyond 5G
Shashank Jere, Qiang Fan, Bodong Shang +2
Owing to the large volume of sensed data from the enormous number of IoT devices in operation today, centralized machine learning algorithms operating on such data incur an unbeara…
Delay-aware Resource Allocation in Fog-assisted IoT Networks Through Reinforcement Learning
Qiang Fan, Jianan Bai, Hongxia Zhang +2
Fog nodes in the vicinity of IoT devices are promising to provision low latency services by offloading tasks from IoT devices to them. Mobile IoT is composed by mobile IoT devices…