Abstract
Video streaming services have gradually become the dominant use case on the Internet, where people's focus has shifted from a service-centric approach to a user-centric approach. This paper proposes a continuous Quality of Experience (QoE) evaluation method based on Quality of Service (QoS) parameters, which combines the advantages of subjective and objective research methods. The proposed method can accurately calculate the achievable QoE based on user QoS. Additionally, we develop a QoE-Ensemble MLP prediction model, employing ensemble learning and MLP techniques, to overcome limitations of the QoE evaluation method and accurately predict user QoE based on QoS parameters. Furthermore, we propose a low-complexity network bandwidth allocation algorithm based on a QoE prediction model to help service providers minimize network bandwidth waste while meeting user QoE requirements. Finally, the experiments show that our QoE evaluation model and network bandwidth allocation algorithm have better performance. And according to the result analysis, we also got the connection between QoS parameters and QoE.
| Original language | English |
|---|---|
| Pages (from-to) | 413-428 |
| Number of pages | 16 |
| Journal | IEEE Transactions on Broadcasting |
| Volume | 70 |
| Issue number | 2 |
| DOIs | |
| State | Published - 1 Jun 2024 |
| Externally published | Yes |
Keywords
- QoS-to-QoE mapping
- UHD cloud performing arts live streaming
- bandwidth resource optimization
- ensemble learning
- recommendation algorithm
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