Quality of experience prediction model for video streaming in SDN networks
| Autor: | Asma Ben Letaifa, Tasnim Abar, Sadok El Asmi |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Service (systems architecture)
Measure (data warehouse) Multimedia General Computer Science Computer science Quality of service 020206 networking & telecommunications 02 engineering and technology Service provider computer.software_genre Video quality 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Network performance Metric (unit) Quality of experience Electrical and Electronic Engineering computer |
| Zdroj: | International Journal of Wireless and Mobile Computing. 18:59 |
| ISSN: | 1741-1092 1741-1084 |
| DOI: | 10.1504/ijwmc.2020.104769 |
| Popis: | To evaluate the network performance, network operators rely on quality of service. This measure has shown limits and great deal of effort has been put into putting in place a new metric that more accurately reflects the quality of service offered. This measure is known as Quality of Experience (QoE). QoE reflects the user's satisfaction for a service. Today, evaluating the QoE has become paramount for service providers and content providers. This necessity pushed us to innovate and design new methods to estimate the QoE. This paper comprises two parts: the first part defines our subjective method which evaluates the video quality over SDN networks. In the second part we try to cover the impairments of subjective methods by a novel method that predicts the QoE (MOS) based on machine learning, so we employ ML-classifiers, then we calculate the performance metrics to measure the performance of each algorithm to deduce the best algorithm. |
| Databáze: | OpenAIRE |
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