A review of graph neural networks and their applications in power systems
W Liao, B Bak-Jensen, JR Pillai… - Journal of Modern …, 2021 - ieeexplore.ieee.org
Deep neural networks have revolutionized many machine learning tasks in power systems,
ranging from pattern recognition to signal processing. The data in these tasks are typically …
ranging from pattern recognition to signal processing. The data in these tasks are typically …
Vnf and cnf placement in 5g: Recent advances and future trends
With the growing demand for openness, scalability, and granularity, mobile network function
virtualization (NFV) has emerged as a key enabler for the most of mobile network operators …
virtualization (NFV) has emerged as a key enabler for the most of mobile network operators …
Network slice reconfiguration by exploiting deep reinforcement learning with large action space
It is widely acknowledged that network slicing can tackle the diverse usage scenarios and
connectivity services that the 5G-and-beyond system needs to support. To guarantee …
connectivity services that the 5G-and-beyond system needs to support. To guarantee …
Dynamic service function chain orchestration for NFV/MEC-enabled IoT networks: A deep reinforcement learning approach
Y Liu, H Lu, X Li, Y Zhang, L Xi… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
Network function virtualization (NFV) and mobile-edge computing (MEC) have been
introduced by Internet service providers (ISPs) to deal with various challenges, which hinder …
introduced by Internet service providers (ISPs) to deal with various challenges, which hinder …
A survey on the placement of virtual network functions
The dependence of traditional network functions (NFs) on special hardware results in high
capital expenditures (CAPEX) and operating expenditures (OPEX). Network Function …
capital expenditures (CAPEX) and operating expenditures (OPEX). Network Function …
Virtualized network function forwarding graph placing in SDN and NFV-enabled IoT networks: A graph neural network assisted deep reinforcement learning method
Y Xie, L Huang, Y Kong, S Wang, S Xu… - … on Network and …, 2021 - ieeexplore.ieee.org
With an ambitious increase in the number of Internet of Things (IoT) terminals, IoT networks
face a huge challenge which is providing diverse and complex network services with …
face a huge challenge which is providing diverse and complex network services with …
Graph neural networks for intelligent modelling in network management and orchestration: a survey on communications
The advancing applications based on machine learning and deep learning in
communication networks have been exponentially increasing in the system architectures of …
communication networks have been exponentially increasing in the system architectures of …
基于深度强化学习的组合优化研究进展
李凯文， 张涛， 王锐， 覃伟健， 贺惠晖， 黄鸿 - 自动化学报, 2021 - aas.net.cn
组合优化问题广泛存在于国防, 交通, 工业, 生活等各个领域, 几十年来, 传统运筹优化方法是解决
组合优化问题的主要手段, 但随着实际应用中问题规模的不断扩大, 求解实时性的要求越来越高 …
组合优化问题的主要手段, 但随着实际应用中问题规模的不断扩大, 求解实时性的要求越来越高 …
Reinforcement learning on graphs: A survey
M Nie, D Chen, D Wang - IEEE Transactions on Emerging …, 2023 - ieeexplore.ieee.org
Graph mining tasks arise from many different application domains, including social
networks, biological networks, transportation, and E-commerce, which have been receiving …
networks, biological networks, transportation, and E-commerce, which have been receiving …
Multi-objective optimization service function chain placement algorithm based on reinforcement learning
H Liu, S Ding, S Wang, G Zhao, C Wang - Journal of Network and Systems …, 2022 - Springer
Network function virtualization (NFV) makes the realization of specific network functions no
longer depend on inherent hardware by executing virtual network functions (VNFs), but …
longer depend on inherent hardware by executing virtual network functions (VNFs), but …