Nonlinearity Modelling of QoE for Video Streaming over Wireless and Mobile Network

Abstract

Quality of Service (QoS) of video streaming service over wireless and mobile network is determined by many intermingled factors. Some of the factors can be adjusted. Video resolution, audio rate, and bandwidth are among of them. Other factors are not fully controllable such as network throughput, delay, and packet lost probability. In order to increase user satisfaction, efforts to make better quality of video services should consider these factors. However,userperceived quality of the service is not only determined by QoS factors. User experience, user expectation and user interest to specific content are among factors that influence level of user satisfaction. In this context, customer satisfaction is known as Quality of user Experience (QoE). Moreover, there is a nonlinearity issue regarding improvement of QoS and QoE. This paper will discuss a holistic view of video service quality in order to elaborate the nonlinearity of QoS and QoE factors and their contribution to enhance user satisfaction.

A Case of Soft System Methodology (SSM): Interacting Aspect Modelling of Customer Satisfaction in Video Stream Service over Wireless and Mobile Network

“…They can be categorized into intrinsic factors (customer experience, customer expectation, and customer interest) and extrinsic factors (saliency awareness, frame rate-to-frame loss awareness, and frame loss distribution awareness). These factors contribute to bring nonlinearity in customer satisfaction [18]. This second aspect influences how well the service quality is perceived by the mobile customer.…”

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

“…This makes the NR model an ideal solution for predicting the QoE of video streaming accessed over a network and estimating customers' satisfaction with the service. Various research studies have put forth no-reference (NR) models for predicting QoE of video streaming [12][13][14]. They utilize numeric input variables to provide QoE scores in terms of Mean Opinion Score (MOS), which is a metric used to measure viewers' satisfaction [15][16][17] .…”