Data-driven evaluation of anticipatory networking in LTE networks

N Bui, J Widmer - IEEE Transactions on Mobile Computing, 2018 - ieeexplore.ieee.org
Anticipatory networking is a recent branch of network optimization based on prediction of the
system state. Our work specifically tackles prediction-driven resource allocation for mobile …

Modelling throughput prediction errors as Gaussian random walks

N Bui, J Widmer - The 1st KuVS Workshop on …, 2014 - dspace.networks.imdea.org
One of the most critical aspects of anticipatory networking is assuming that future system
conditions can be estimated. In this paper we address how accurate the current state of the …

Forecasting mobile service demands for anticipatory MEC

S Ntalampiras, M Fiore - … Symposium on" A World of Wireless …, 2018 - ieeexplore.ieee.org
The accurate estimation of future traffic loads is a key enabler for anticipatory mobile
networking. In this paper, we investigate the prediction of the traffic generated by different …

Lossleap: Learning to predict for intent-based networking

A Collet, A Banchs, M Fiore - IEEE INFOCOM 2022-IEEE …, 2022 - ieeexplore.ieee.org
Intent-Based Networking mandates that high-level human-understandable intents are
automatically interpreted and implemented by network management entities. As a key part in …

Mobile network resource optimization under imperfect prediction

N Bui, J Widmer - 2015 IEEE 16th International Symposium on …, 2015 - ieeexplore.ieee.org
A highly interesting trend in mobile network optimization is to exploit knowledge of future
network capacity to allow mobile terminals to prefetch data when signal quality is high and to …

Anticipatory quality-resource allocation for multi-user mobile video streaming

N Bui, S Valentin, J Widmer - 2015 IEEE Conference on …, 2015 - ieeexplore.ieee.org
Mobile video delivery forms the largest part of the traffic in cellular networks. Thus optimizing
the resource allocation to satisfy a user's quality of experience is becoming paramount in …

Spatial-temporal graph attention networks: A deep learning approach for traffic forecasting

C Zhang, JQ James, Y Liu - Ieee Access, 2019 - ieeexplore.ieee.org
Traffic speed prediction, as one of the most important topics in Intelligent Transport Systems
(ITS), has been investigated thoroughly in the literature. Nonetheless, traditional methods …

Advancing 6G Network Performance: AI/ML Framework for Proactive Management and Dynamic Optimal Routing

PM Tshakwanda, ST Arzo… - IEEE Open Journal of …, 2024 - ieeexplore.ieee.org
As 6G networks proliferate, they generate vast volumes of data and engage diverse devices,
pushing the boundaries of traditional network management techniques. The limitations of …

A machine-learning-based framework for optimizing the operation of future networks

C Fiandrino, C Zhang, P Patras… - IEEE …, 2020 - ieeexplore.ieee.org
5G and beyond are not only sophisticated and difficult to manage, but must also satisfy a
wide range of stringent performance requirements and adapt quickly to changes in traffic …

PROTEUS: network performance forecast for real-time, interactive mobile applications

Q Xu, S Mehrotra, Z Mao, J Li - Proceeding of the 11th annual …, 2013 - dl.acm.org
Real-time communication (RTC) applications such as VoIP, video conferencing, and online
gaming are flourishing. To adapt and deliver good performance, these applications require …