Resource-Efficient DNN Training and Inference for Heterogeneous Edge Intelligence in 6G
Edge intelligence is expected to be a key enabler of the future sixth generation (6G) mobile
network. However, the heterogeneous characteristics of edge intelligence, such as …
network. However, the heterogeneous characteristics of edge intelligence, such as …
EEAI: An End-edge Architecture for Accelerating Deep Neural Network Inference
Deep Neural Networks (DNNs), as a key technology for Artificial Intelligence (AI)
applications in the 5G era, have been widely used in the field of mobile intelligence …
applications in the 5G era, have been widely used in the field of mobile intelligence …
Edge AI: On-demand accelerating deep neural network inference via edge computing
As a key technology of enabling Artificial Intelligence (AI) applications in 5G era, Deep
Neural Networks (DNNs) have quickly attracted widespread attention. However, it is …
Neural Networks (DNNs) have quickly attracted widespread attention. However, it is …
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 …
Enabling low latency edge intelligence based on multi-exit dnns in the wild
In recent years, deep neural networks (DNNs) have witnessed a booming of artificial
intelligence Internet of Things applications with stringent demands across high accuracy and …
intelligence Internet of Things applications with stringent demands across high accuracy and …
Split computing: Dynamic partitioning and reliable communications in IoT-edge for 6G vision
Implementation of Deep Neural Networks (DNNs) in 6G era is expected to get widespread
attention in the applications of Internet of Things (IoT). Unfortunately, it is a challenging task …
attention in the applications of Internet of Things (IoT). Unfortunately, it is a challenging task …
Edge artificial intelligence for 6G: Vision, enabling technologies, and applications
KB Letaief, Y Shi, J Lu, J Lu - IEEE Journal on Selected Areas …, 2021 - ieeexplore.ieee.org
The thriving of artificial intelligence (AI) applications is driving the further evolution of
wireless networks. It has been envisioned that 6G will be transformative and will …
wireless networks. It has been envisioned that 6G will be transformative and will …
Federated learning in mobile edge computing: An edge-learning perspective for beyond 5G
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 …
operation today, centralized machine learning algorithms operating on such data incur an …
Functional split of in-network deep learning for 6G: A feasibility study
In existing mobile network systems, the data plane (DP) is mainly considered a pipeline
consisting of network elements end-to-end forwarding user data traffics. With the rapid …
consisting of network elements end-to-end forwarding user data traffics. With the rapid …
MEET: Mobility-enhanced edge intelligence for smart and green 6G networks
Edge intelligence is an emerging paradigm for real-time training and inference at the
wireless edge, thus enabling mission-critical applications. Accordingly, base stations (BSs) …
wireless edge, thus enabling mission-critical applications. Accordingly, base stations (BSs) …