QoE Evaluation of BPP Packet Wash Using ROI-Based Scalable Video Coding
Latency-sensitive multimedia applications, such as cloud gaming, require advanced streaming solutions that provide both low latency and high visual quality to ensure seamless user experience. Conventional transport protocols often struggle under sudden bandwidth fluctuations, resulting in latency spikes, packet loss, and ultimately gameplay interruptions. To address these limitations, this work explores the capabilities of the Big Packet Protocol (BPP) packet wash mechanism combined with Region of Interest (ROI) coding by Scalable Video Coding (SVC) for <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\text{2 K}$</tex> video games to satisfy the Quality of Experience (QoE) under network congestion. BPP packet wash dynamically discards non-critical enhancement layer chunks at the network edge during congestion, ensuring a critical Quality of Service (QoS)-preserving remediation before the application's Control Congestion Algorithm (CCA) comes into play to adapt the bitrate. Comparative experiments for various coding strategies after applying packet wash show that ROI SVC can handle bandwidth drops more efficiently, up to <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\text{5 2} {\%}$</tex> reduction, while still maintaining uninterrupted gameplay and satisfactory visual quality in the most critical regions of the game, according to QoE evaluation involving real users. These results indicate that packet wash with ROI SVC provides an effective solution for real-time interactive multimedia streaming, such as cloud gaming.
Authors
- Thibault Cholez (ORCID: https://orcid.org/0000-0002-0435-3909)
- Mohammadreza Ghafari (ORCID: https://orcid.org/0000-0002-5043-0944)
Institutions
- Centre National de la Recherche Scientifique (FR)
- Laboratoire Lorrain de Recherche en Informatique et ses Applications (FR)
- Université de Lorraine (FR)
Publication Details
- Published
- 2025-12-08
- DOI
- https://doi.org/10.1109/ism66958.2025.00014
- Primary Topic
- Image and Video Quality Assessment
- Type
- article
- Field-Weighted Citation Impact
- 0.00