A comprehensive survey on machine learning for networking: evolution, applications and research opportunities

R Boutaba, MA Salahuddin, N Limam, S Ayoubi… - Journal of Internet …, 2018 - Springer
Abstract Machine Learning (ML) has been enjoying an unprecedented surge in applications
that solve problems and enable automation in diverse domains. Primarily, this is due to the …

Unsupervised machine learning for networking: Techniques, applications and research challenges

M Usama, J Qadir, A Raza, H Arif, KLA Yau… - IEEE …, 2019 - ieeexplore.ieee.org
While machine learning and artificial intelligence have long been applied in networking
research, the bulk of such works has focused on supervised learning. Recently, there has …

In-network machine learning using programmable network devices: A survey

C Zheng, X Hong, D Ding, S Vargaftik… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
Machine learning is widely used to solve networking challenges, ranging from traffic
classification and anomaly detection to network configuration. However, machine learning …

Bearing fault diagnostics using EEMD processing and convolutional neural network methods

IIE Amarouayache, MN Saadi, N Guersi… - … International Journal of …, 2020 - Springer
The development of an intelligent fault diagnosis system to identify automatically and
accurately micro-faults affecting motors continues to be a challenge for industrial rotary …

Machine learning-assisted closed-control loops for beyond 5g multi-domain zero-touch networks

NFS de Sousa, MT Islam, RU Mustafa… - Journal of Network and …, 2022 - Springer
Abstract End-to-End (E2E) services in beyond 5G (B5G) networks are expected to be built
upon resources and services distributed in multi-domain, multi-technology environments. In …

FDF-HybridFS: Towards design of a failure detection framework using hybrid feature selection method for IP core networks that connect 5G core in NFV-based test …

A Rajak, R Tripathi - Computer Standards & Interfaces, 2024 - Elsevier
With the advancement of recent technologies, high-speed and secure internet connectivity is
required for 5th-generation mobile networks. A massive number of smart devices connected …

A survey of fault management in network virtualization environments: Challenges and solutions

S Cherrared, S Imadali, E Fabre… - … on Network and …, 2019 - ieeexplore.ieee.org
The advent of 5G and the ever increasing stringent requirements in terms of bandwidth,
latency, and quality of service pushes the boundaries of what is feasible with legacy Mobile …

Data clustering using unsupervised machine learning

B Chander, K Gopalakrishnan - Statistical Modeling in Machine Learning, 2023 - Elsevier
Artificial intelligence (AI) and machine learning (ML) have been active in various research
fields and improved results. However, most of them applied or focused on supervised …

Network threat detection based on group CNN for privacy protection

Y Xu, X Zhang, C Lu, Z Qiu, C Bi, Y Lai… - Wireless …, 2021 - Wiley Online Library
The Internet of Things (IoT) contains a large amount of data, which attracts various types of
network attacks that lead to privacy leaks. With the upgrading of network attacks and the …

Comparative analysis of network fault classification using machine learning

J Kawasaki, G Mouri, Y Suzuki - NOMS 2020-2020 IEEE/IFIP …, 2020 - ieeexplore.ieee.org
The recent evolution in network technologies such as network function virtualization (NFV)
and cloud-native network function (CNF) is expected to enable the delivery of on-demand …