Container-based Video Streaming Service

Vidieccan, Matus; Bobák, Martin

doi:10.1109/cinti-macro57952.2022.10029489

Cited by 2 publications

(2 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The experiments were conducted in the computer laboratory, and participants were given an introduction to the procedure, tools, and environment before beginning the experiments. To design the experiment sequence, the Taguchi orthogonal array L9(3 4 ) was chosen because we had four input variables, each with three different levels of variation. Each session lasted for 1 minute, and, at the end of each session, participants rated their viewing experience on a scale of bad, poor, average, good, and excellent.…”

Section: (A) Selection Of Input Variablesmentioning

confidence: 99%

“…platforms enable users to create various types of content, such as text, pictures, and video 1 . Audio and video streaming applications are the most preferred content on the internet and generate a significant amount of traffic over the internet [2][3][4] . Furthermore, these applications require a seamless transmission to deliver reliable and constant flow packets that depend on the condition of the network [5].…”

mentioning

confidence: 99%

See 1 more Smart Citation

Modeling Video Streaming Quality of Experience using Taguchi and Fuzzy Logic Methods

Mongi

2023

JICTS

View full text Add to dashboard Cite

The popularity of mobile video streaming has increased significantly in recent years, and is expected to account for two-thirds of global internet traffic in the near future. However, determining accurately end-users' satisfaction based on network parameters remains a challenge. Existing research often uses network parameters, such as packet loss, delay, and jitter, to estimate users' Quality of Experience (QoE). However, most models present QoE estimates in Mean Opinion Scores (MoS), which are not easily understood by the customers. In this study, we used the Taguchi approach to conduct QoE experiments over a wireless tested. We investigated the simultaneous effects of packet loss, corruption, delay, and jitter on video streaming QoE, as well as their interaction effects. Furthermore, we developed a Fuzzy logic model in MatlabR2016a to establish the relationship between input variables and video streaming QoE. The model presents the results in an easily understandable linguistic terms such as excellent, good, average, bad, and poor. Additionally, the proposed model achieves a correlation of 0.875 between the predicted and user scores, with a Root Mean Square Error of 0.344.

show abstract

Section: (A) Selection Of Input Variablesmentioning

confidence: 99%

mentioning

confidence: 99%