VQEG White Paper on Quality of Experience-Aware Management for Collaboration Between Network and Application Providers
| Type | Technical Report |
|---|---|
| Title | VQEG White Paper on Quality of Experience-Aware Management for Collaboration Between Network and Application Providers |
| Author | P. Pérez, F. Blouin, B. Adsumilli, S. Baldoni, F. Battisti, N. Birkbeck, K. Brunnström, L. M. Contreras, M. Fiedler, J. Folgueira, N. García, E. Halepovic, T. Hoßfeld, T. Karagioules, I. Katsavounidis, K. Koniuch, D. Lindero, S. Nadas, M. Orduna, P. Rojo, A. Raake, R. Rao Ramachandra Rao, W. Robitza, T. Tsou, and M. Zorzi |
| Institution | Video Quality Experts Group (VQEG) |
| Year | 2026 |
| Month | March |
| Number | VQEG_TR_2026_001 |
| Type detail | Technical Report |
| DOI | 10.66537/OLKA7578 |
| Document | PDF file |
Executive Summary
This VQEG white paper addresses the challenge of improving end-user Quality of Experience (QoE) for Internet services. It begins by outlining the core problem: Content and Application Providers (CAPs) and Communication Service Providers (CSPs) operate largely independently without a common view of their users' experience, given that the default Internet connectivity provided is Best-Effort. This separation makes it difficult to diagnose end-user issues and optimize performance from an end-to-end perspective.
The goal of the white paper is establishing a framework which facilitates a common view of the end-user’s experience of service quality. Then, exchanging respective information between CAPs and CSPs allows for managing those services efficiently.
While aiming for broad applicability, it offers a more in-depth analysis of specific services to provide practical insights: short-form video, long-form video, and interactive services such as cloud gaming and video conferencing.
The white paper first establishes a common foundation by reviewing existing QoS and QoE definitions, QoE models and relevant industry standards. It presents a layered model to define key concepts, separating network-level Key Performance Indicators (KPIs), applicationspecific Key Quality Indicators (KQIs), and the user-centric QoE, proposing clear definitions for some important QoE-related terms, such as user-reported QoE, modeled QoE, or system QoE. This provides a common language for understanding the remainder of the paper and discussions in the research community.
The potential benefits of QoE management are discussed with respect to typical issues and common information gaps, making the case for closer collaboration between CAPs and CSPs. The core proposal is a framework for structured information exchange between those stakeholders. This mechanism, described as a shared state table, allows for the exchange of relevant metrics – either in near real-time or periodically, and with different granularity (e.g. aggregated) – to create a shared view of service and network performance.
This exchange of information enables cooperative optimization. CSPs, on the one hand, can use QoE-related data from CAPs (e.g., video fidelity scores, stalling events) to better understand the impact of network conditions and adjust resource management accordingly. CAPs, on the other hand, can use network status information from CSPs (e.g., congestion levels, available throughput) to make network-aware adaptation decisions, such as selecting an appropriate video quality to avoid stalls.
To demonstrate the framework's real-world value, the white paper also illustrates its application through practical use cases for short and long-form video streaming, as well as interactive services like cloud gaming. These examples show how specific metrics can be used to improve startup times, reduce stalling, and manage latency. Finally, the framework addresses key privacy considerations, proposing a voluntary, opt-in system that uses practices such as temporary, pseudonymized session identifiers.
In conclusion, this VQEG white paper presents a structured approach for improving QoE through enhanced cooperation between CAPs and CSPs. The proposed framework provides a foundation for developing and sharing metrics that can lead to more efficient and effective service delivery. The recommended next steps include further development and validation of the proposed models through a proof-of-concept, with the long-term goal of contributing the findings to relevant standardization bodies such as ITU-T and IETF.