Logistic regression based in-service assessment of mobile web browsing service quality acceptability

In this paper, we presented a logistic regression model that we applied for assessment of the users’ quality of experience with web browsing service over mobile network. With this regard, we chose the Average-Time-to-Connect-TCP network service quality parameter as an independent predictor, obtained by passive monitoring of live traffic data, captured by a passive probe on the mobile network Gn interface, and related to detailed records of the Transport Control Protocol. In parallel with in-service measuring the selected network parameter, we conducted simultaneous subjective tests of the quality of experience acceptability to users, specifically for web browsing service. Particularly, it was found that the model provided correct acceptability classification in 84.5% of cases, while reducing the chosen independent predictor for 100 ms implied increasing the chance of the service acceptability by factor of 1.65. Based on the obtained results, it comes out that the applied logistic regression model provides satisfactory estimation of the web browsing service quality experience acceptability.

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