Automatic virtual network embedding: A deep reinforcement learning approach with graph convolutional networks

Z Yan, J Ge, Y Wu, L Li, T Li - IEEE Journal on Selected Areas …, 2020 - ieeexplore.ieee.org
Virtual network embedding arranges virtual network services onto substrate network
components. The performance of embedding algorithms determines the effectiveness and …

Intelligent calibration and virtual sensing for integrated low-cost air quality sensors

MA Zaidan, NH Motlagh, PL Fung, D Lu… - IEEE Sensors …, 2020 - ieeexplore.ieee.org
This paper presents the development of air quality low-cost sensors (LCS) with improved
accuracy features. The LCS features integrate machine learning based calibration models …

[HTML][HTML] Reinforcement learning-based virtual network embedding: A comprehensive survey

HK Lim, I Ullah, YH Han, SY Kim - ICT Express, 2023 - Elsevier
Virtual network embedding plays a vital role in network virtualization, as it determines the
deployment and connection of virtual networks to the physical network in the 5G and …

A comprehensive review of machine learning in multi-objective optimization

Q Qu, Z Ma, A Clausen… - 2021 IEEE 4th …, 2021 - ieeexplore.ieee.org
In the real world, it is challenging to calculate a trade-off alternative with traditional classical
methods for complex non-linear systems, which always involve multiple conflicting …

Resource management and security scheme of ICPSs and IoT based on VNE algorithm

P Zhang, C Wang, C Jiang, N Kumar… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
The development of intelligent cyber–physical systems (ICPSs) in the virtual network
environment is facing severe challenges. On the one hand, the Internet of Things (IoT) …

Virtual network embedding based on hierarchical cooperative multi-agent reinforcement learning

HK Lim, I Ullah, JB Kim, YH Han - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Virtual network embedding (VNE) is a promising technique enabling 5G networks to satisfy
the given requirements of each service via network virtualization. For better performance of …

[HTML][HTML] An intelligent TCP congestion control method based on deep Q network

Y Wang, L Wang, X Dong - Future Internet, 2021 - mdpi.com
To optimize the data migration performance between different supercomputing centers in
China, we present TCP-DQN, which is an intelligent TCP congestion control method based …

A robust control-theory-based exploration strategy in deep reinforcement learning for virtual network embedding

G Dandachi, S Cerf, Y Hadjadj-Aoul, A Outtagarts… - Computer Networks, 2022 - Elsevier
Network slice management and, more generally, resource orchestration should be fully
automated in 6G networks, as envisioned by the ETSI ENI. In this context, artificial …

[HTML][HTML] Trust based multipath qos routing protocol for mission-critical data transmission in tactical ad-hoc networks

DH Keum, J Lim, YB Ko - Sensors, 2020 - mdpi.com
In tactical ad-hoc networks, the importance of various tactical sensors and mission-critical
data is increasing owing to their role in determining a tactical situation and ensuring the …

DRL-D: revenue-aware online service function chain deployment via deep reinforcement learning

Q Fan, P Pan, X Li, S Wang, J Li… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Network function virtualization (NFV) is a promising paradigm where network functions are
migrated from dedicated hardware appliances onto software middleboxes to promote …