Dr Taha Mansouri T.Mansouri@salford.ac.uk
Lecturer in AI
A practical model for ensemble estimation of QoS and QoE in VoIP services via fuzzy inference systems and fuzzy evidence theory
Mansouri, T; Nabavi, A; Ravasan, AZ; Ahangarbahan, H
Authors
A Nabavi
AZ Ravasan
H Ahangarbahan
Abstract
Nowadays, there is an increasing number of Voices over IP (VoIP) services offered in telecommunication networks with specific quality requirements. Such requirements impact upon both the objective quality of service (QoS) of the end-to end connection as well as the subjective quality of experience (QoE) as perceived by the end user. In this study, we have proposed an integrated QoS and QoE evaluation system based on the combination of fuzzy inference systems and fuzzy evidence theory. For quality criteria, we have used QoS as a technical source from the viewpoint of service provider and QoE as the end user approach in front of service. We have divided the positive and negative variables of QoE into two distinct systems. At the same time, a parameter has been proposed as quality, which is the total quality of a service according to the objective and subjective viewpoints. To calculate the parameters mentioned above, a fuzzy inference system has been utilized. In addition, to obtain all data sources as an evidence of quality, Dempster–Shafer evidence theory has been employed. Finally, the proposed approach evaluated through the quality of VoIP services in three real cases and the results are discussed.
Citation
Mansouri, T., Nabavi, A., Ravasan, A., & Ahangarbahan, H. (2016). A practical model for ensemble estimation of QoS and QoE in VoIP services via fuzzy inference systems and fuzzy evidence theory. Telecommunication Systems, 61(4), 861-873. https://doi.org/10.1007/s11235-015-0041-6
Journal Article Type | Article |
---|---|
Online Publication Date | Apr 29, 2015 |
Publication Date | Apr 1, 2016 |
Deposit Date | Jun 9, 2021 |
Journal | Telecommunication Systems |
Print ISSN | 1018-4864 |
Electronic ISSN | 1572-9451 |
Publisher | Springer Verlag |
Volume | 61 |
Issue | 4 |
Pages | 861-873 |
DOI | https://doi.org/10.1007/s11235-015-0041-6 |
Publisher URL | https://doi.org/10.1007/s11235-015-0041-6 |
Related Public URLs | http://link.springer.com/journal/11235 |
You might also like
Review of farmer-centered AI systems technologies in livestock operations
(2024)
Journal Article
Identifying the threshold concepts in teaching marketing: A pedagogic research
(2024)
Presentation / Conference
The Intersection of Generative AI and Healthcare: Addressing Challenges to Enhance Patient Care
(2024)
Conference Proceeding
A Comprehensive Review of AI Techniques for Addressing Algorithmic Bias in Job Hiring
(2024)
Journal Article
Downloadable Citations
About USIR
Administrator e-mail: library-research@salford.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search