On the predictability of next generation mobile network traffic using artificial neural networks

Author:

Loumiotis I.1,Adamopoulou E.1,Demestichas K.1,Stamatiadi T.1,Theologou M.1

Affiliation:

1. School of Electrical and Computer Engineering; National Technical University of Athens; Athens Greece

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computer Networks and Communications

Reference20 articles.

1. Cisco Cisco Visual Networking Index: Forecast and Methodology 2011-2016, (white paper) 2012

2. 3D video communications: challenges and opportunities;Su;International Journal of Communication Systems,2013

3. A QoE management system to improve the IPTV network;Lloret;International Journal of Communication Systems,2011

4. A personalized mobile IPTV system with seamless video reconstruction algorithm in cloud networks;Lai;International Journal of Communication Systems,2011

5. Integrating multimedia streaming from heterogeneous sources to JavaME mobile devices;Calvo-Flores;International Journal of Communication Systems,2012

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1. Traffic forecasting in cellular networks using the LSTM RNN;Proceedings of the 22nd Pan-Hellenic Conference on Informatics;2018-11-29

2. A Proportional Multi-resource Scheduling Model in SDCloud;2016 IEEE 14th Intl Conf on Dependable, Autonomic and Secure Computing, 14th Intl Conf on Pervasive Intelligence and Computing, 2nd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech);2016-08

3. P-Aware: a proportional multi-resource scheduling strategy in cloud data center;Cluster Computing;2016-07-09

4. Artificial Neural Networks for Traffic Prediction in 4G Networks;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2015

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