QoE Management of Multimedia Streaming Services in Future Networks: A Tutorial and Survey
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Abstract (arXiv)
We provide in this paper a tutorial and a comprehensive survey of QoE management solutions in current and future networks. We start with a high level description of QoE management for multimedia services, which integrates QoE modelling, monitoring, and optimization. This followed by a discussion of HTTP Adaptive Streaming (HAS) solutions as the dominant technique for streaming videos over the best-effort Internet. We then summarize the key elements in SDN/NFV along with an overview of ongoing research projects, standardization activities and use cases related to SDN, NFV, and other emerging applications. We provide a survey of the state-of-the-art of QoE management techniques categorized into three different groups: a) QoE-aware/driven strategies using SDN and/or NFV; b) QoE-aware/driven approaches for adaptive streaming over emerging architectures such as multi-access edge computing, cloud/fog computing, and information-centric networking; and c) extended QoE management approaches in new domains such as immersive augmented and virtual reality, mulsemedia and video gaming applications. Based on the review, we present a list of identified future QoE management challenges regarding emerging multimedia applications, network management and orchestration, network slicing and collaborative service management in softwarized networks. Finally, we provide a discussion on future research directions with a focus on emerging research areas in QoE management, such as QoE-oriented business models, QoE-based big data strategies, and scalability issues in QoE optimization.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 28 Dec 2019.
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Citing papers per year: 2022: 1; 2023: 1; 2024: 1; 2025: 1.
4 papers.
- 2023Edge-Based Video Analytics: A Surveycited by 8
- 2022Supervised Learning based QoE Prediction of Video Streaming in Future Networks: A Tutorial with Comparative Studycited by 4
- 2024Machine Learning-Driven Open-Source Framework for Assessing QoE in Multimedia Networkscited by 1
- 2025Bridging Subjective and Objective QoE: Operator-Level Aggregation Using LLM-Based Comment Analysis and Network MOS Comparisoncited by 0
- 2025Bridging Subjective and Objective QoE: Operator-Level Aggregation Using LLM-Based Comment Analysis and Network MOS Comparison1 Jun 2025
- 2024Machine Learning-Driven Open-Source Framework for Assessing QoE in Multimedia Networks12 Jun 2024
- 2023Edge-Based Video Analytics: A Survey25 Mar 2023
- 2022Supervised Learning based QoE Prediction of Video Streaming in Future Networks: A Tutorial with Comparative Study3 Jan 2022