100 citations · 234 across the 21 of their papers we have counts for
8 papers · 1 filter
BeeFlow: Behavior Tree-based Serverless Workflow Modeling and Scheduling for Resource-Constrained Edge Clusters
Ke Luo, Tao Ouyang, Zhi Zhou +1
Serverless computing has gained popularity in edge computing due to its flexible features, including the pay-per-use pricing model, auto-scaling capabilities, and multi-tenancy sup…
Serving Graph Neural Networks With Distributed Fog Servers For Smart IoT Services
Liekang Zeng, Xu Chen, Peng Huang +3
Graph Neural Networks (GNNs) have gained growing interest in miscellaneous applications owing to their outstanding ability in extracting latent representation on graph structures.…
iGniter: Interference-Aware GPU Resource Provisioning for Predictable DNN Inference in the Cloud
Fei Xu, Jianian Xu, Jiabin Chen +4
GPUs are essential to accelerating the latency-sensitive deep neural network (DNN) inference workloads in cloud datacenters. To fully utilize GPU resources, spatial sharing of GPUs…
GNN at the Edge: Cost-Efficient Graph Neural Network Processing over Distributed Edge Servers
Liekang Zeng, Chongyu Yang, Peng Huang +3
Edge intelligence has arisen as a promising computing paradigm for supporting miscellaneous smart applications that rely on machine learning techniques. While the community has ext…
HFEL: Joint Edge Association and Resource Allocation for Cost-Efficient Hierarchical Federated Edge Learning
Siqi Luo, Xu Chen, Qiong Wu +2
Federated Learning (FL) has been proposed as an appealing approach to handle data privacy issue of mobile devices compared to conventional machine learning at the remote cloud with…
Edge Intelligence: Paving the Last Mile of Artificial Intelligence with Edge Computing
Zhi Zhou, Xu Chen, En Li +3
With the breakthroughs in deep learning, the recent years have witnessed a booming of artificial intelligence (AI) applications and services, spanning from personal assistant to re…
Efficient Resource Allocation for On-Demand Mobile-Edge Cloud Computing
Xu Chen, Wenzhong Li, Sanglu Lu +2
Mobile-edge cloud computing is a new paradigm to provide cloud computing capabilities at the edge of pervasive radio access networks in close proximity to mobile users. Aiming at p…
Edge Intelligence: On-Demand Deep Learning Model Co-Inference with Device-Edge Synergy
En Li, Zhi Zhou, Xu Chen
As the backbone technology of machine learning, deep neural networks (DNNs) have have quickly ascended to the spotlight. Running DNNs on resource-constrained mobile devices is, how…