25 citations · 27 across the 5 of their papers we have counts for
6 papers
A Multi-User Effective Computation Offloading Mechanism for MEC System: Batched Multi-Armed Bandits Approach
Hangfan Li, Xiaoxiong Zhong, Xinghan Wang +2
With the development of 5G technology, mobile edge computing (MEC) is becoming a useful architecture, which is envisioned as a cloud computing extension version. Users within MEC s…
Two-Stage Coded Distributed Edge Learning: A Dynamic Partial Gradient Coding Perspective
Tingting Yang, Xinghan Wang, Jiahong Ning +1
The widespread adoption of distributed learning to train a global model from local data has been hindered by the challenge posed by stragglers. Recent attempts to mitigate this iss…
CFLMEC: Cooperative Federated Learning for Mobile Edge Computing
Xinghan Wang, Xiaoxiong Zhong, Yuanyuan Yang +1
We investigate a cooperative federated learning framework among devices for mobile edge computing, named CFLMEC, where devices co-exist in a shared spectrum with interference. Keep…
A Parallel Optimal Task Allocation Mechanism for Large-Scale Mobile Edge Computing
Xiaoxiong Zhong, Xinghan Wang, Yuanyuan Yang +3
We consider the problem of intelligent and efficient task allocation mechanism in large-scale mobile edge computing (MEC), which can reduce delay and energy consumption in a parall…
CL-ADMM: A Cooperative Learning Based Optimization Framework for Resource Management in MEC
Xiaoxiong Zhong, Xinghan Wang, Li Li +5
We consider the problem of intelligent and efficient resource management framework in mobile edge computing (MEC), which can reduce delay and energy consumption, featuring distribu…
Decentralized Bayesian Learning over Graphs
Anusha Lalitha, Xinghan Wang, Osman Kilinc +3
We propose a decentralized learning algorithm over a general social network. The algorithm leaves the training data distributed on the mobile devices while utilizing a peer to peer…