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DOI: 10.14569/IJACSA.2019.0100978
PDF

Towards A Proactive System for Predicting Service Quality Degradations in Next Generation of Networks based on Time Series

Author 1: Errais Mohammed
Author 2: Rachdi Mohamed
Author 3: Al Sarem Mohammed
Author 4: Abdel Hamid Mohamed Emara

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 9, 2019.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: The architecture of Next Generation of networks (NGN) aims to diversify the offer of operators in added value services. To do this, NGN offers a heterogeneous architecture for the services deployment. This poses significant challenges in terms of end-to-end assurance of services. For this purpose, we propose in this work the establishment of a proactive autonomous system, capable of ensuring an acceptable quality level according to Service Level Agreement (SLA) requirements. A system that is able to predict any QoS degradation due to the prediction model based on time series adapted to NGN.

Keywords: Next Generation of Network (NGN); network management; enhanced Telecom Operation Management (eTOM) frameworks; prediction; time series; Ip Multimedia Subsystem (IMS); Service Level Agreement (SLA); Quality Of Service (QoS)

Errais Mohammed, Rachdi Mohamed, Al Sarem Mohammed and Abdel Hamid Mohamed Emara, “Towards A Proactive System for Predicting Service Quality Degradations in Next Generation of Networks based on Time Series” International Journal of Advanced Computer Science and Applications(IJACSA), 10(9), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100978

@article{Mohammed2019,
title = {Towards A Proactive System for Predicting Service Quality Degradations in Next Generation of Networks based on Time Series},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100978},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100978},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {9},
author = {Errais Mohammed and Rachdi Mohamed and Al Sarem Mohammed and Abdel Hamid Mohamed Emara}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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