Combining federated learning and edge computing toward ubiquitous intelligence in 6G network: Challenges, recent advances, and future directions
Full leverage of the huge volume of data generated on a large number of user devices for
providing intelligent services in the 6G network calls for Ubiquitous Intelligence (UI). A key to …
providing intelligent services in the 6G network calls for Ubiquitous Intelligence (UI). A key to …
Gossipfl: A decentralized federated learning framework with sparsified and adaptive communication
Recently, federated learning (FL) techniques have enabled multiple users to train machine
learning models collaboratively without data sharing. However, existing FL algorithms suffer …
learning models collaboratively without data sharing. However, existing FL algorithms suffer …
Enabling all in-edge deep learning: A literature review
In recent years, deep learning (DL) models have demonstrated remarkable achievements
on non-trivial tasks such as speech recognition, image processing, and natural language …
on non-trivial tasks such as speech recognition, image processing, and natural language …
Pyramid: Enabling hierarchical neural networks with edge computing
Machine learning (ML) is powering a rapidly-increasing number of web applications. As a
crucial part of 5G, edge computing facilitates edge artificial intelligence (AI) by ML model …
crucial part of 5G, edge computing facilitates edge artificial intelligence (AI) by ML model …
Green AI for IIoT: Energy efficient intelligent edge computing for industrial internet of things
Artificial Intelligence (AI) technology is a huge opportunity for the Industrial Internet of Things
(IIoT) in the fourth industrial revolution (Industry 4.0). However, most AI-driven applications …
(IIoT) in the fourth industrial revolution (Industry 4.0). However, most AI-driven applications …
Fededge: Accelerating edge-assisted federated learning
Federated learning (FL) has been widely acknowledged as a promising solution to training
machine learning (ML) model training with privacy preservation. To reduce the traffic …
machine learning (ML) model training with privacy preservation. To reduce the traffic …
Local scheduling in kubeedge-based edge computing environment
SH Kim, T Kim - Sensors, 2023 - mdpi.com
KubeEdge is an open-source platform that orchestrates containerized Internet of Things
(IoT) application services in IoT edge computing environments. Based on Kubernetes, it …
(IoT) application services in IoT edge computing environments. Based on Kubernetes, it …
Pepper: Empowering user-centric recommender systems over gossip learning
Recommender systems are proving to be an invaluable tool for extracting user-relevant
content hel** users in their daily activities (eg, finding relevant places to visit, content to …
content hel** users in their daily activities (eg, finding relevant places to visit, content to …
[HTML][HTML] Brainyedge: An ai-enabled framework for iot edge computing
Along with the proliferation of the Internet of Things (IoT) and the surge in the use of artificial
intelligence (AI), Edge Computing has proved considerable success in reducing latency …
intelligence (AI), Edge Computing has proved considerable success in reducing latency …
Tformer: A transmission-friendly vit model for iot devices
Deploying high-performance vision transformer (ViT) models on ubiquitous Internet of
Things (IoT) devices to provide high-quality vision services will revolutionize the way we live …
Things (IoT) devices to provide high-quality vision services will revolutionize the way we live …