Challenges of future multimedia QoE monitoring for internet service providers
Open accessAbstract
The ever-increasing network traffic and user expectations at reduced cost make the delivery of high Quality of Experience (QoE) for multimedia services more vital than ever in the eyes of Internet Service Providers (ISPs). Real-time quality monitoring, with a focus on the user, has become essential as the first step in cost-effective provisioning of high quality services. With the recent changes in the perception of user privacy, the rising level of application-layer encryption and the introduction and deployment of virtualized networks, QoE monitoring solutions need to be adapted to the fast changing Internet landscape. In this contribution, we provide an overview of state-of-the-art quality monitoring models and probing technologies, and highlight the major challenges ISPs have to face when they want to ensure high service quality for their customers.
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In [36] authors developed a predictive model for quality evaluation in IoT based solely on data gathered from a survey performed on the users of the application.
“In [36] authors developed a predictive model for quality evaluation in IoT.The model is based on user experience from the IoT application.This model is solely based on data gathered from the survey performed on the users of the application.”
From QoE in IoT: a vision, survey and future directions (2021) · cites this paper as [36]
Section 3.4, “Virtual objects” (page unavailable), describes creating quality models for virtualized IoT services as a challenge, not a model the authors developed. The Conclusion (page unavailable) likewise says the major challenge lies in developing appropriate models. Neither passage describes a model built solely from a user survey. (LLM, conf=0.84)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredOne recently evolving method for measuring the quality of multimedia content involves both subjective and objective evaluation to obtain the best of two methods.
“One of the recently evolving methods for measuring the quality of multimedia content involves both subjective and objective evaluation to obtain the best of two methods [36].”
From QoE in IoT: a vision, survey and future directions (2021) · cites this paper as [36]
Section 2.2 (page unavailable) describes automated multimedia-quality models that estimate a value akin to a human observer’s rating, and §2.1 describes a shift toward predicting user-perceived quality. Neither passage says that a method combines subjective and objective evaluations to obtain the benefits of both. (LLM, conf=0.78)
Experimental — accuracy not yet measuredCollected network-level Key Performance Indicators (KPIs) and user-level Key Quality Indicators (KQIs) provide inputs for QoE estimation models.
“The collected network-level Key Performance Indicators (KPIs), e.g., throughput, packet loss, delay or user-level service/application specific Key Quality Indicators (KQIs), e.g., frame rate, video resolution, service usability, and reliability, provide inputs for QoE estimation models [48], [61].”
From QoE Management of Multimedia Streaming Services in Future Networks: A Tutorial and Survey (2020) · cites this paper as [61]
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Korchani, B., & Sethom, K. (2022) · Lecture notes in networks and systems · doi:10.1007/978-3-030-99619-2_2
Quality of experience recent trends and challenges
Al-Shammari, B. K. J., & Jaish, A. A. (2023) · AIP conference proceedings · doi:10.1063/5.0148077
Business practices vs. technical quality: What drives negative reviews in telecom
Teruel-Gutiérrez, R., & da Anunciação, P. F. (2026) · Quality Management Journal · doi:10.1080/10686967.2026.2696237
Sensitivity Analysis of Beta-Based System GoB Approximations from QoS and MoS Mappings
Hoßfeld, T., & Pérez, P. (2026) · International Conference on Quality of Multimedia Experience (QoMEX) · doi:10.1109/qomex69967.2026.11618339
- Authors
- Robitza, W., Ahmad, A., Kara, P. A., Atzori, L., Martini, M. G., Raake, A., & Sun, L.
- Affiliations
- Deutsche Telekom (Germany) (DE)
- University of Cagliari (IT)
- Kingston University London (GB)
- Technische Universität Ilmenau (DE)
- University of Plymouth (GB)
- Corresponding author
- Robitza, Werner
- ORCID
- Venue
- Multimedia Tools and Applications
- Published
- 2017-06-02
- Volume
- 76
- Issue
- 21
- Pages
- 22243-22266
- ISSN
- 1380-7501 (ISSN-L)
- 1573-7721
- OpenAlex
- W2620788719
- Cited by
- 57
- References
- 42
- Citations by year
- 2026: 3 · 2025: 1 · 2024: 3 · 2023: 4 · 2022: 11 · 2021: 8 · 2020: 7 · 2019: 11 · 2018: 8 · 2017: 1
- FWCI
- 3.07
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- Multimedia Tools and Applications (publishedVersion, cc-by)
- Research Repository (Kingston University London) (acceptedVersion)
- PEARL (University of Plymouth) (submittedVersion, cc-by)
- UNICA IRIS Institutional Research Information System (University of Cagliari) (submittedVersion, cc-by)
- PEARL (University of Plymouth) (submittedVersion)
- Funders
- Horizon 2020 (643072)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Video Quality Assessment
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Traffic and Congestion Control
- Physical Sciences › Computer Science › Computer Networks and Communications › Software-Defined Networks and 5G
- Keywords
- quality of experience, QoE monitoring, multimedia services, internet service providers, real-time quality monitoring, user privacy, virtual networks, network traffic
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