Graph-based deep learning for communication networks: A survey

W Jiang - Computer Communications, 2022 - Elsevier
Communication networks are important infrastructures in contemporary society. There are
still many challenges that are not fully solved and new solutions are proposed continuously …

Graph neural networks for intelligent modelling in network management and orchestration: a survey on communications

P Tam, I Song, S Kang, S Ros, S Kim - Electronics, 2022 - mdpi.com
The advancing applications based on machine learning and deep learning in
communication networks have been exponentially increasing in the system architectures of …

A survey on mobile edge computing infrastructure: Design, resource management, and optimization approaches

LA Haibeh, MCE Yagoub, A Jarray - IEEE Access, 2022 - ieeexplore.ieee.org
Emerging 5G cellular networks are expected to face a dramatic increase in the volume of
mobile traffic and IoT user requests due to the massive growth in mobile devices and the …

Mapping the VNFs and VLs of a RAN slice onto intelligent PoPs in beyond 5G mobile networks

MA Habibi, FZ Yousaf… - IEEE Open Journal of the …, 2022 - ieeexplore.ieee.org
The mapping of a virtual network service onto a physical network infrastructure is a
challenging task due to the joint allocation of virtual resources across nodes and links, the …

SARM: service function chain active reconfiguration mechanism based on load and demand prediction

J Cai, K Qian, J Luo, K Zhu - International Journal of Intelligent …, 2022 - Wiley Online Library
Network function virtualization is a promising technology for providing personalized services
via agile service function chains (SFCs). Flexible SFC orchestration and rational resource …

Automatic performance-optimal offloading of network functions on programmable switches

X Chen, H Liu, D Zhang, Z Meng… - … on Cloud Computing, 2022 - ieeexplore.ieee.org
In network function virtualization (NFV), network functions (NFs) are chained as a service
function chain (SFC) to enhance NF management with low cost and high flexibility. Recent …

Comparison of machine learning techniques for VNF resource requirements prediction in NFV

M Moradi, M Ahmadi, R Nikbazm - Journal of Network and Systems …, 2022 - Springer
The network function virtualization (NFV) is a developing architecture that uses virtualization
technology to separate software from hardware. One of the most important challenges of …

[HTML][HTML] Scaling migrations and replications of virtual network functions based on network traffic forecasting

F Carpio, W Bziuk, A Jukan - Computer Networks, 2022 - Elsevier
Migration and replication of virtual network functions (VNFs) are well-known mechanisms to
face dynamic resource requests in Internet Service Provider (ISP) edge networks. They are …

Mastering Neural Network Prediction for Enhanced System Reliability

J Baumgartner, A Schneider, U Zhenis… - Fusion of …, 2022 - fusionproceedings.com
Mastering neural network prediction is crucial for enhancing system reliability across various
fields, from healthcare to autonomous driving. Neural networks, with their ability to learn and …

KSN: Modeling and simulation of knowledge using machine learning in NFV/SDN-based networks

R Nikbazm, M Ahmadi - Simulation Modelling Practice and Theory, 2022 - Elsevier
The rapid advancement of networking and computing technologies has led to the
emergence of a wide range of diverse dynamic network services that present networks with …