Oct 22, 2024 · This work focuses on the design, the empirical evaluation and the analysis of the behavior of training-based models for predicting the throughput of a single ...

Via experimentation on real network traffic of different links, we study the effect of some parameters on the predic- tion performance in terms of error. These ...

On the predictability of next generation mobile network traffic using artificial neural networks · Computer Science, Engineering. Int. J. Commun. Syst. · 2015.

Network traffic analysis and prediction is a proactive approach to ensure secure, reliable and qualitative network communication. Various techniques are ...

Real-time and accurate prediction of network traffic plays an important role in network resource allocation, abnormal traffic detection and other works.

Mar 21, 2024 · The aim of this work is to make time series predictions for real network traffic data by using long short-term memory neural networks (LSTMs).

Jul 2, 2022 · This proposed work is coining a new method using an enhanced deep reinforcement learning (EDRL) algorithm to improve network traffic analysis and prediction.

Abstract: We study power and performance characteristics of different traffic predictors for online one-step-ahead predictions.

We propose a novel approach for network traffic prediction, which integrates the Butterworth filter, Convolutional Neural Network and Long Short-Term Memory ...

Analysis and prediction of network traffic has applications in wide comprehensive set of areas and has newly. attracted significant number of studies.