Forecasting network traffic: A survey and tutorial with open-source comparative evaluation

GO Ferreira, C Ravazzi, F Dabbene… - IEEE …, 2023 - ieeexplore.ieee.org
This paper presents a review of the literature on network traffic prediction, while also serving
as a tutorial to the topic. We examine works based on autoregressive moving average …

[PDF][PDF] Metaheuristic Optimization of Time Series Models for Predicting Networks Traffic

R Alkanhel, ESM El-kenawy… - CMC-COMPUTERS …, 2023 - researchgate.net
Traffic prediction of wireless networks attracted many researchers and practitioners during
the past decades. However, wireless traffic frequently exhibits strong nonlinearities and …

A hybrid prediction method for realistic network traffic with temporal convolutional network and LSTM

J Bi, X Zhang, H Yuan, J Zhang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Accurate and real-time prediction of network traffic can not only help system operators
allocate resources rationally according to their actual business needs but also help them …

Network traffic prediction based on deep belief network in wireless mesh backbone networks

L Nie, D Jiang, S Yu, H Song - 2017 IEEE Wireless …, 2017 - ieeexplore.ieee.org
Wireless mesh network is prevalent for providing a decentralized access for users. For a
wireless mesh backbone network, it has obtained extensive attention because of its large …

Intelligent hybrid model to enhance time series models for predicting network traffic

THH Aldhyani, M Alrasheedi, AA Alqarni… - IEEE …, 2020 - ieeexplore.ieee.org
Network traffic analysis and predictions have become vital for monitoring networks. Network
prediction is the process of capturing network traffic and examining it deeply to decide what …

A meta-learning scheme for adaptive short-term network traffic prediction

Q He, A Moayyedi, G Dán… - IEEE Journal on …, 2020 - ieeexplore.ieee.org
Network traffic prediction is a fundamental prerequisite for dynamic resource provisioning in
wireline and wireless networks, but is known to be challenging due to non-stationarity and …

Interactive temporal recurrent convolution network for traffic prediction in data centers

X Cao, Y Zhong, Y Zhou, J Wang, C Zhu… - IEEE Access, 2017 - ieeexplore.ieee.org
Accurately predicting future service traffic would be of great help for load balancing and
resource allocation, which plays a key role in guaranteeing the quality of service (QoS) in …

Predicting future traffic using hidden markov models

Z Chen, J Wen, Y Geng - 2016 IEEE 24th international …, 2016 - ieeexplore.ieee.org
Network traffic volume estimation and prediction is an important research topic that attracts
persistent attention from the networking community and the machine learning community …

Spatio-temporal network traffic estimation and anomaly detection based on convolutional neural network in vehicular ad-hoc networks

L Nie, Y Li, X Kong - IEEE Access, 2018 - ieeexplore.ieee.org
Over the last decade, vehicular ad-hoc networks (VANETs) have received a greater attention
in academia and industry due to their influence in intelligent transportation systems …

Deep learning based traffic prediction method for digital twin network

J Lai, Z Chen, J Zhu, W Ma, L Gan, S Xie, G Li - Cognitive Computation, 2023 - Springer
Network traffic prediction (NTP) can predict future traffic leveraging historical data, which
serves as proactive methods for network resource planning, allocation, and management …