207 citations · 833 across the 51 of their papers we have counts for
12 papers · 1 filter
Federated Learning over Wireless Networks: A Band-limited Coordinated Descent Approach
Junshan Zhang, Na Li, Mehmet Dedeoglu
We consider a many-to-one wireless architecture for federated learning at the network edge, where multiple edge devices collaboratively train a model using local data. The unreliab…
Deep Reinforcement Learning with Spatio-temporal Traffic Forecasting for Data-Driven Base Station Sleep Control
Qiong Wu, Xu Chen, Zhi Zhou +2
To meet the ever increasing mobile traffic demand in 5G era, base stations (BSs) have been densely deployed in radio access networks (RANs) to increase the network coverage and cap…
FedHome: Cloud-Edge based Personalized Federated Learning for In-Home Health Monitoring
Qiong Wu, Xu Chen, Zhi Zhou +1
In-home health monitoring has attracted great attention for the ageing population worldwide. With the abundant user health data accessed by Internet of Things (IoT) devices and rec…
CoEdge: Cooperative DNN Inference with Adaptive Workload Partitioning over Heterogeneous Edge Devices
Liekang Zeng, Xu Chen, Zhi Zhou +2
Recent advances in artificial intelligence have driven increasing intelligent applications at the network edge, such as smart home, smart factory, and smart city. To deploy computa…
Content Popularity Prediction Towards Location-Aware Mobile Edge Caching
Peng Yang, Ning Zhang, Shan Zhang +3
Mobile edge caching enables content delivery within the radio access network, which effectively alleviates the backhaul burden and reduces response time. To fully exploit edge stor…
Mobile Edge Caching: An Optimal Auction Approach
Xuanyu Cao, Junshan Zhang, H. Vincent Poor
With the explosive growth of wireless data, the sheer size of the mobile traffic is challenging the capacity of current wireless systems. To tackle this challenge, mobile edge cach…