Unleashing the power of edge-cloud generative ai in mobile networks: A survey of aigc services

M Xu, H Du, D Niyato, J Kang, Z Xiong… - … Surveys & Tutorials, 2024 - ieeexplore.ieee.org
Artificial Intelligence-Generated Content (AIGC) is an automated method for generating,
manipulating, and modifying valuable and diverse data using AI algorithms creatively. This …

Combined federated and split learning in edge computing for ubiquitous intelligence in internet of things: State-of-the-art and future directions

Q Duan, S Hu, R Deng, Z Lu - Sensors, 2022 - mdpi.com
Federated learning (FL) and split learning (SL) are two emerging collaborative learning
methods that may greatly facilitate ubiquitous intelligence in the Internet of Things (IoT) …

Efficient parallel split learning over resource-constrained wireless edge networks

Z Lin, G Zhu, Y Deng, X Chen, Y Gao… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
The increasingly deeper neural networks hinder the democratization of privacy-enhancing
distributed learning, such as federated learning (FL), to resource-constrained devices. To …

Federated learning in cloud-edge collaborative architecture: key technologies, applications and challenges

G Bao, P Guo - Journal of Cloud Computing, 2022 - Springer
In recent years, with the rapid growth of edge data, the novel cloud-edge collaborative
architecture has been proposed to compensate for the lack of data processing power of …

Federated split learning for sequential data in satellite–terrestrial integrated networks

W Jiang, H Han, Y Zhang, J Mu - Information Fusion, 2024 - Elsevier
Satellite–terrestrial integrated networks (STINs) have been proposed for B5G/6G mobile
communication, and the increase in the computation and communication capacities of …

Vehicle as a service (VaaS): Leverage vehicles to build service networks and capabilities for smart cities

X Chen, Y Deng, H Ding, G Qu, H Zhang… - … Surveys & Tutorials, 2024 - ieeexplore.ieee.org
Smart cities demand resources for rich immersive sensing, ubiquitous communications,
powerful computing, large storage, and high intelligence (SCCSI) to support various kinds of …

Split learning in 6g edge networks

Z Lin, G Qu, X Chen, K Huang - IEEE Wireless …, 2024 - ieeexplore.ieee.org
With the proliferation of distributed edge computing resources, the 6G mobile network will
evolve into a network for connected intelligence. Along this line, the proposal to incorporate …

Federated learning-empowered mobile network management for 5G and beyond networks: From access to core

J Lee, F Solat, TY Kim, HV Poor - … Communications Surveys & …, 2024 - ieeexplore.ieee.org
The fifth generation (5G) and beyond wireless networks are envisioned to provide an
integrated communication and computing platform that will enable multipurpose and …

Splitlora: A split parameter-efficient fine-tuning framework for large language models

Z Lin, X Hu, Y Zhang, Z Chen, Z Fang, X Chen… - arXiv preprint arXiv …, 2024 - arxiv.org
The scalability of large language models (LLMs) in handling high-complexity models and
large-scale datasets has led to tremendous successes in pivotal domains. While there is an …

Netgpt: A native-ai network architecture beyond provisioning personalized generative services

Y Chen, R Li, Z Zhao, C Peng, J Wu, E Hossain… - arXiv preprint arXiv …, 2023 - arxiv.org
Large language models (LLMs) have triggered tremendous success to empower daily life by
generative information, and the personalization of LLMs could further contribute to their …