Real-Time MPC for Adaptive Video Streaming - Vito Andrea Racanelli; Gioacchino Manfredi; Luca De Cicco; Saverio Mascolo (2025 IEEE 22nd Consumer Communications & Networking Conference (CCNC), 2025)
Dynamic Adaptive Streaming over HTTP (DASH) is the standard for video streaming applications such as YouTube and Netflix. According to DASH, the video player must include an Adaptive Bit-Rate (ABR) controller designed to maximize users’ Quality of Experience (QoE). The controller must avoid playback interruptions, due to buffer underflow, while at the same time selecting the maximum video encoding quality compatible with the available time-varying bandwidth. This paper proposes a controller designed using a nicely constrained Model Predictive Control (MPC) which employs Bellman Dynamic Programming (DP) to reduce the computational cost of the algorithm from exponential to polynomial. Compared with state-of-the-art ABR algorithms, the proposed Real-Time MPC (RT-MPC) improves QoE while remarkably reducing the computational time, so that the algorithm can be used for both live-video streaming and real-time conferencing.
Keywords: Video on demand; Heuristic algorithms; Prediction algorithms; Real-time systems; Encoding; Dynamic programming; Quality of experience; Web sites; Standards; Predictive control