Measuring, modeling and integrating time-varying video quality in end-to-end multimedia service delivery: A review and open challenges

CTER Hewage, A Ahmad, T Mallikarachchi… - IEEE …, 2022 - ieeexplore.ieee.org
The multimedia delivery chain consists of multiple stages such as content preparation,
content delivery via Over-The-Top delivery network and Internet Service Providers network …

[HTML][HTML] On attacking future 5g networks with adversarial examples: Survey

M Zolotukhin, D Zhang, T Hämäläinen, P Miraghaei - Network, 2022 - mdpi.com
The introduction of 5G technology along with the exponential growth in connected devices is
expected to cause a challenge for the efficient and reliable network resource allocation …

Ml-based qoe estimation in 5g networks using different regression techniques

S Schwarzmann, CC Marquezan… - … on Network and …, 2022 - ieeexplore.ieee.org
Monitoring and providing customers with a satisfying Quality of Experience (QoE) is a crucial
business incentive for mobile network operators (MNOs). While the MNO is capable of …

Distributed service provisioning for disaggregated 6g network infrastructures

VM Alevizaki, M Anastasopoulos… - … on Network and …, 2022 - ieeexplore.ieee.org
6G Systems are expected to support a variety of services over a common infrastructure that
is efficiently shared through slicing. Novel Quality of Experience (QoE) architectural models …

AI/ML-aided capacity maximization strategies for URLLC in 5G/6G wireless systems: A survey

RB Shaik, P Nagaradjane, I Ioannou, V Sittakul… - Computer Networks, 2024 - Elsevier
Ultra-reliable low-latency communication (URLLC) refers to cellular applications in fifth and
sixth-generation (5G/6G) networks with specific latency, reliability, and availability demands …

基于深度强化学习的智能路由技术研究.

黄万伟, 郑向雨, 张超钦, 王苏南… - Journal of Zhengzhou …, 2023 - search.ebscohost.com
针对现有智能路由算法收敛速度慢, 平均时延高, 带宽利用率低等问题, 提出了一种基于深度强化
学习(DRL) 的多路径智能路由算法RDPG-Route. 该算法采用循环确定性策略梯度(RDPG) …

Domain adaptation for network performance modeling with and without labeled data

H Larsson, F Moradi, J Taghia, X Lan… - NOMS 2023-2023 …, 2023 - ieeexplore.ieee.org
Network performance modeling using machine learning (ML) has proven to be essential for
proactive network and service management. Dynamic changes and re-configurations in the …

Improving the Transfer of Machine Learning-Based Video QoE Estimation Across Diverse Networks

M Seufert, I Orsolic - IEEE Transactions on Network and …, 2023 - ieeexplore.ieee.org
With video streaming traffic generally being encrypted end-to-end, there is a lot of interest
from network operators to find novel ways to evaluate streaming performance at the …

A novel system to control and forecast QoX performance in IoT‐based monitoring platforms

JM Martinez‐Caro, I Tasic… - IET Wireless Sensor …, 2023 - Wiley Online Library
Communication architectures based on the Internet of Things (IoT) are increasingly frequent.
Commonly, these solutions are used to carry out control and monitoring activities. It is easy …

Robust Deep Learning against Corrupted Data in Cognitive Autonomous Networks

M Kajó, J Schnellbach, SS Mwanje… - NOMS 2022-2022 IEEE …, 2022 - ieeexplore.ieee.org
Neural-net-based deep learning algorithms are starting to be utilized in many network
functions. Deep neural nets are traditionally not resistant against missing or corrupted …