Survey on Machine Learning-based QoE-QoS Correlation Models - Archive ouverte HAL Access content directly
Conference Papers Year : 2014

Survey on Machine Learning-based QoE-QoS Correlation Models

S. Aroussi
  • Function : Author
A Mellouk
  • Function : Author
CIR

Abstract

The machine learning provides a theoretical and methodological framework to quantify the relationship between user OoE (Quality of Experience) and network QoS (Quality of Service). This paper presents an overview of QoE-QoS correlation models based on machine learning techniques. According to the learning type, we propose a categorization of correlation models. For each category, we review the main existing works by citing deployed learning methods and model parameters (QoE measurement, QoS parameters and service type). Moreover, the survey will provide researchers with the latest trends and findings in this field.
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Dates and versions

hal-01567533 , version 1 (24-07-2017)

Identifiers

  • HAL Id : hal-01567533 , version 1

Cite

S. Aroussi, A Mellouk. Survey on Machine Learning-based QoE-QoS Correlation Models. Proc. Of the IEEE 2nd International Conference on Computing, Management and Telecommunications, ComManTel 2014, 2014, Da Nang, Vietnam. pp.200-204. ⟨hal-01567533⟩

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