Cellular traffic prediction with machine learning: A survey

W Jiang - Expert Systems with Applications, 2022 - Elsevier
Cellular networks are important for the success of modern communication systems, which
support billions of mobile users and devices. Powered by artificial intelligence techniques …

Prediction of traffic generated by IoT devices using statistical learning time series algorithms

SP Khedkar, RA Canessane… - … and Mobile Computing, 2021 - Wiley Online Library
An IoT is the communication of sensing devices linked to the Internet in order to
communicate data. IoT devices have extremely critical reliability with an efficient and robust …

A Survey on Deep Learning for Cellular Traffic Prediction

X Wang, Z Wang, K Yang, Z Song, C Bian… - Intelligent …, 2024 - spj.science.org
With the widespread deployment of 5G networks and the proliferation of mobile devices,
mobile network operators are confronted not only with massive data growth in mobile traffic …

[Retracted] Prediction of IoT Traffic Using the Gated Recurrent Unit Neural Network‐(GRU‐NN‐) Based Predictive Model

SA Patil, LA Raj, BK Singh - Security and Communication …, 2021 - Wiley Online Library
Prediction of IoT traffic in the current era has attracted noteworthy attention to utilize the
bandwidth and channel capacity optimally. In this paper, the problem of IoT traffic prediction …

Deep learning based mobile traffic flow prediction model in 5G cellular networks

E Selvamanju, VB Shalini - 2022 3rd International Conference …, 2022 - ieeexplore.ieee.org
Due to drastic development of smart phone devices, there is a considerable increase in
mobile traffic flow that is provided difficulty on the fifth generation (5G) cellular networks. The …

Multi-weighted graph 3D convolution network for traffic prediction

Y Liu, C Wang, S Xu, W Zhou, Y Chen - Neural Computing and …, 2023 - Springer
Predicting future traffic state (eg, traffic speed, volume, travel time, etc.) accurately is highly
desirable for traffic management and control. However, network-wide traffic flow has …

Mobile network traffic analysis based on probability-informed machine learning approach

A Gorshenin, A Kozlovskaya, S Gorbunov… - Computer Networks, 2024 - Elsevier
The paper proposes an approach to the joint use of statistical and machine learning (ML)
models to solve the problems of the precise reconstruction of historical events, real-time …

Deep recurrent neural network for optical fronthaul dimensioning and proactive vBBU placement in CF-RAN

MRP dos Santos, RI Tinini, TO Januario… - Photonic Network …, 2022 - Springer
In this paper, we solve virtualized passive optical network (VPON) assignment and
virtualized baseband unit (vBBU) placement using an integer linear programming …

Deep Learning Based Traffic Prediction in Mobile Network-A Survey

X Wang, Z Wang, K Yang, Z Song, J Feng, L Zhu… - Authorea …, 2023 - techrxiv.org
With broad deployment of 5G network and pro-liferation of mobile devices, mobile network
operators are not only facing massive data growth in mobile traffic, and also observing very …

[PDF][PDF] Network Traffic Prediction Using Radial Kernelized-Tversky Indexes-Based Multilayer Classifier.

M Govindarajan, V Chandrasekaran… - … Systems Science & …, 2022 - cdn.techscience.cn
Internet services for various devices at any time. With the use of mobile devices,
communication services generate numerous data for every moment. Given the increasing …