Wireless powered mobile edge computing networks: A survey

X Wang, J Li, Z Ning, Q Song, L Guo, S Guo… - ACM Computing …, 2023 - dl.acm.org
Wireless Powered Mobile Edge Computing (WPMEC) is an integration of Mobile Edge
Computing (MEC) and Wireless Power Transfer (WPT) technologies, to both improve …

AI models for green communications towards 6G

B Mao, F Tang, Y Kawamoto… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
Green communications have always been a target for the information industry to alleviate
energy overhead and reduce fossil fuel usage. In the current 5G and future 6G eras, there is …

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 …

A survey of incentive mechanism design for federated learning

Y Zhan, J Zhang, Z Hong, L Wu, P Li… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Federated learning is promising in enabling large-scale machine learning by massive
clients without exposing their raw data. It can not only enable the clients to preserve the …

[HTML][HTML] Survey on computation offloading in UAV-Enabled mobile edge computing

SMA Huda, S Moh - Journal of Network and Computer Applications, 2022 - Elsevier
With the increasing growth of internet-of-things (IoT) devices, effective computation
performance has become a critical issue. Many services provided by IoT devices (eg …

Single and multi-agent deep reinforcement learning for AI-enabled wireless networks: A tutorial

A Feriani, E Hossain - IEEE Communications Surveys & …, 2021 - ieeexplore.ieee.org
Deep Reinforcement Learning (DRL) has recently witnessed significant advances that have
led to multiple successes in solving sequential decision-making problems in various …

Blockchain and federated learning for collaborative intrusion detection in vehicular edge computing

H Liu, S Zhang, P Zhang, X Zhou… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
The vehicular networks constructed by interconnected vehicles and transportation
infrastructure are vulnerable to cyber-intrusions due to the expanded use of software and the …

Reducing offloading latency for digital twin edge networks in 6G

W Sun, H Zhang, R Wang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
6G is envisioned to empower wireless communication and computation through the
digitalization and connectivity of everything, by establishing a digital representation of the …

Toward enabled industrial verticals in 5G: A survey on MEC-based approaches to provisioning and flexibility

F Spinelli, V Mancuso - IEEE Communications Surveys & …, 2020 - ieeexplore.ieee.org
The increasing number of heterogeneous devices connected to the Internet, together with
tight 5G requirements have generated new challenges for designing network infrastructures …

Combining federated learning and edge computing toward ubiquitous intelligence in 6G network: Challenges, recent advances, and future directions

Q Duan, J Huang, S Hu, R Deng… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
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 …