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 …

Zero touch management: A survey of network automation solutions for 5G and 6G networks

E Coronado, R Behravesh… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
Mobile networks are facing an unprecedented demand for high-speed connectivity
originating from novel mobile applications and services and, in general, from the adoption …

Convergence of edge computing and deep learning: A comprehensive survey

X Wang, Y Han, VCM Leung, D Niyato… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
Ubiquitous sensors and smart devices from factories and communities are generating
massive amounts of data, and ever-increasing computing power is driving the core of …

A survey of multi-access edge computing in 5G and beyond: Fundamentals, technology integration, and state-of-the-art

QV Pham, F Fang, VN Ha, MJ Piran, M Le, LB Le… - IEEE …, 2020 - ieeexplore.ieee.org
Driven by the emergence of new compute-intensive applications and the vision of the
Internet of Things (IoT), it is foreseen that the emerging 5G network will face an …

Edge intelligence: Empowering intelligence to the edge of network

D Xu, T Li, Y Li, X Su, S Tarkoma, T Jiang… - Proceedings of the …, 2021 - ieeexplore.ieee.org
Edge intelligence refers to a set of connected systems and devices for data collection,
caching, processing, and analysis proximity to where data are captured based on artificial …

A survey on end-edge-cloud orchestrated network computing paradigms: Transparent computing, mobile edge computing, fog computing, and cloudlet

J Ren, D Zhang, S He, Y Zhang, T Li - ACM Computing Surveys (CSUR), 2019 - dl.acm.org
Sending data to the cloud for analysis was a prominent trend during the past decades,
driving cloud computing as a dominant computing paradigm. However, the dramatically …

Machine learning for 5G/B5G mobile and wireless communications: Potential, limitations, and future directions

ME Morocho-Cayamcela, H Lee, W Lim - IEEE access, 2019 - ieeexplore.ieee.org
Driven by the demand to accommodate today's growing mobile traffic, 5G is designed to be
a key enabler and a leading infrastructure provider in the information and communication …

In-edge ai: Intelligentizing mobile edge computing, caching and communication by federated learning

X Wang, Y Han, C Wang, Q Zhao, X Chen… - Ieee …, 2019 - ieeexplore.ieee.org
Recently, along with the rapid development of mobile communication technology, edge
computing theory and techniques have been attracting more and more attention from global …

Federated deep reinforcement learning for Internet of Things with decentralized cooperative edge caching

X Wang, C Wang, X Li, VCM Leung… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
Edge caching is an emerging technology for addressing massive content access in mobile
networks to support rapidly growing Internet-of-Things (IoT) services and applications …

Application of machine learning in wireless networks: Key techniques and open issues

Y Sun, M Peng, Y Zhou, Y Huang… - … Surveys & Tutorials, 2019 - ieeexplore.ieee.org
As a key technique for enabling artificial intelligence, machine learning (ML) is capable of
solving complex problems without explicit programming. Motivated by its successful …