Forecasting network traffic: A survey and tutorial with open-source comparative evaluation
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 …
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 …
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
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 …
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
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 …
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
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 …
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
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 …
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
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 …
resource allocation, which plays a key role in guaranteeing the quality of service (QoS) in …
Predicting future traffic using hidden markov models
Network traffic volume estimation and prediction is an important research topic that attracts
persistent attention from the networking community and the machine learning community …
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
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 …
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 …
serves as proactive methods for network resource planning, allocation, and management …