Review on Machine Learning for Intelligent Routing, Key Requirement and Challenges Towards 6G

B Langpoklakpam, LK Murry - Computer Networks and …, 2023 - ojs.wiserpub.com
The constant desire for faster data rates, lower latency, improved reliability, global device
integration, and pervasiveness are some of the factors driving the development of next …

Human-perception-oriented pseudo analog video transmissions with deep learning

XW Tang, XL Huang, F Hu, Q Shi - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Recently, pseudo analog transmission has gained increasing attentions due to its ability to
alleviate the cliff effect in video multicast scenarios. The existing pseudo analog systems are …

Intelligent traffic management and load balance based on spike ISDN-IoT

NAS Al-Jamali, HS Al-Raweshidy - IEEE Systems Journal, 2020 - ieeexplore.ieee.org
An intelligent software defined network (ISDN) based on an intelligent controller can
manage and control the network in a remarkable way. In this article, a methodology is …

Vehicle-assisted data delivery in smart city: A deep learning approach

W Liu, Y Watanabe, Y Shoji - IEEE Transactions on Vehicular …, 2020 - ieeexplore.ieee.org
Collecting the massive internet of things data produced in a large smart city is quite
challenging, and recent advances in vehicle-to-everything communication makes urban …

Location Privacy Threats and Protections in Future Vehicular Networks: A Comprehensive Review

B Ma, X Wang, X Lin, Y Jiang, C Sun, Z Wang… - arXiv preprint arXiv …, 2023 - arxiv.org
Location privacy is critical in vehicular networks, where drivers' trajectories and personal
information can be exposed, allowing adversaries to launch data and physical attacks that …

Sdpredictnet-a topology based sdn neural routing framework with traffic prediction analysis

S Sanagavarapu, S Sridhar - 2021 IEEE 11th Annual …, 2021 - ieeexplore.ieee.org
Software Defined Networking is an intelligent network management approach for monitoring
and improving performance such as in cloud computing. These networks follow separation …

Deep learning for SDN-enabled campus networks: proposed solutions, challenges and future directions

WC Chanhemo, MH Mohsini, MM Mjahidi… - International Journal of …, 2023 - emerald.com
Purpose This study explores challenges facing the applicability of deep learning (DL) in
software-defined networks (SDN) based campus networks. The study intensively explains …

Traffic-aware optimal routing in software defined networks by predicting traffic using neural network

MA Gunavathie, S Umamaheswari - Expert Systems with Applications, 2024 - Elsevier
Network infrastructure management has been completely transformed by Software-Defined
Networking (SDN), allowing for centralized control and programmability. The significant …

Advancing Malware Detection in Network Traffic With Self-Paced Class Incremental Learning

X Xu, X Zhang, Q Zhang, Y Wang… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
Ensuring network security, effective malware detection is of paramount importance.
Traditional methods often struggle to accurately learn and process the characteristics of …

Low-Resource Scenario Classification Through Model Pruning Towards Refined Edge Intelligence

X Shan, J Wang, X Yan, C Wang… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
The implementation of Scenario Classification (SC) plays a pivotal role in various edge
intelligence applications, notably in fields such as autonomous driving, navigation, and …