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 …

Machine learning for large-scale optimization in 6g wireless networks

Y Shi, L Lian, Y Shi, Z Wang, Y Zhou… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
The sixth generation (6G) wireless systems are envisioned to enable the paradigm shift from
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …

Deep reinforcement learning for energy-efficient computation offloading in mobile-edge computing

H Zhou, K Jiang, X Liu, X Li… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Mobile-edge computing (MEC) has emerged as a promising computing paradigm in the 5G
architecture, which can empower user equipments (UEs) with computation and energy …

Lyapunov-guided deep reinforcement learning for stable online computation offloading in mobile-edge computing networks

S Bi, L Huang, H Wang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Opportunistic computation offloading is an effective method to improve the computation
performance of mobile-edge computing (MEC) networks under dynamic edge environment …

Energy-efficient joint task offloading and resource allocation in OFDMA-based collaborative edge computing

L Tan, Z Kuang, L Zhao, A Liu - IEEE Transactions on Wireless …, 2021 - ieeexplore.ieee.org
Mobile edge computing (MEC) is an emergent architecture, which brings computation and
storage resources to the edge of mobile network and provides rich services and applications …

Edge intelligence: A computational task offloading scheme for dependent IoT application

H Xiao, C Xu, Y Ma, S Yang, L Zhong… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Computational offloading, as an effective way to extend the capability of resource-limited
edge devices in Internet of Things (IoT), is considered as a promising emerging paradigm for …

Machine and deep learning for resource allocation in multi-access edge computing: A survey

H Djigal, J Xu, L Liu, Y Zhang - IEEE Communications Surveys …, 2022 - ieeexplore.ieee.org
With the rapid development of Internet-of-Things (IoT) devices and mobile communication
technologies, Multi-access Edge Computing (MEC) has emerged as a promising paradigm …

Reinforcement learning methods for computation offloading: a systematic review

Z Zabihi, AM Eftekhari Moghadam… - ACM Computing …, 2023 - dl.acm.org
Today, cloud computation offloading may not be an appropriate solution for delay-sensitive
applications due to the long distance between end-devices and remote datacenters. In …

Deep reinforcement learning-based task scheduling in iot edge computing

S Sheng, P Chen, Z Chen, L Wu, Y Yao - Sensors, 2021 - mdpi.com
Edge computing (EC) has recently emerged as a promising paradigm that supports resource-
hungry Internet of Things (IoT) applications with low latency services at the network edge …

Multitask offloading strategy optimization based on directed acyclic graphs for edge computing

J Chen, Y Yang, C Wang, H Zhang… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
With the advancement of the user application service demands, the IoT system tends to
offload the tasks to the edge server for execution. Most of the current studies on edge …