Survey on machine learning for traffic-driven service provisioning in optical networks

T Panayiotou, M Michalopoulou… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
The unprecedented growth of the global Internet traffic, coupled with the large spatio-
temporal fluctuations that create, to some extent, predictable tidal traffic conditions, are …

Multi visual GRU based survivable computing power scheduling in metro optical networks

T Yu, H Yang, Q Yao, A Yu, Y Zhao… - … on Network and …, 2023 - ieeexplore.ieee.org
The computing power network (CPN) has emerged as a promising networking paradigm in
recent times. Since the characteristics of high bandwidth, low delay and high reliable …

Computational intelligence and soft computing paradigm for cheating detection in online examinations

S Kaddoura, S Vincent… - … Intelligence and Soft …, 2023 - Wiley Online Library
Covid‐19 has been a life‐changer in the sphere of online education. With complete
lockdown in various countries, there has been a tumultuous increase in the need for …

Extending P4 in-band telemetry to user equipment for latency-and localization-aware autonomous networking with AI forecasting

D Scano, F Paolucci, K Kondepu… - Journal of Optical …, 2021 - opg.optica.org
In beyond-5G networks, detailed end-to-end monitoring of specific application traffic will be
required along with the access-backhaul-cloud continuum to enable low latency service due …

Short-Term Network Traffic Prediction with Multilayer Perceptron

A Ganowicz, B Starosta, A Knapińska… - 2022 6th SLAAI …, 2022 - ieeexplore.ieee.org
The constantly increasing internet traffic and rising network requirements trigger fast
development and implementation of new networking architectures and technologies …

Liquid Neural Network-based Adaptive Learning vs. Incremental Learning for Link Load Prediction amid Concept Drift due to Network Failures

O Ayoub, D Andreoletti, A Knapińska… - arXiv preprint arXiv …, 2024 - arxiv.org
Adapting to concept drift is a challenging task in machine learning, which is usually tackled
using incremental learning techniques that periodically re-fit a learning model leveraging …

A Multimodal Network Security Framework for Healthcare Based on Deep Learning

QQ Chen, JP Li, A Haq, BLY Agbley… - Computational …, 2023 - Wiley Online Library
As the network is closely related to people's daily life, network security has become an
important factor affecting the physical and mental health of human beings. Network flow …

Multi-Step Traffic Prediction for Multi-Period Planning in Optical Networks

H Maryam, T Panayiotou, G Ellinas - arXiv preprint arXiv:2404.08314, 2024 - arxiv.org
A multi-period planning framework is proposed that exploits multi-step ahead traffic
predictions to address service overprovisioning and improve adaptability to traffic changes …

Highly reliable and large-scale optical circuit switch for intra-datacentre networks

T Mitsuya, T Ochiai, T Kuno, Y Mori… - … and Exhibition on …, 2022 - opg.optica.org
We propose a novel optical circuit switch architecture offering high reliability and high
capacity. The proposed scheme substantially reduces the annual downtime of the switch …

Prediction of multiple types of traffic with a novel evaluation metric related to bandwidth blocking

A Knapińska, P Lechowicz… - GLOBECOM 2022-2022 …, 2022 - ieeexplore.ieee.org
With the ever-increasing traffic load, the prediction of future traffic patterns can bring
significant benefits to network optimization. The appropriate choice of a forecasting model is …