Optimizing Low-Latency Video Streaming: AI-Assisted Codec-Network Coordination

Coimbra, Portugal, September 8 – 11, 2025.

Tutorial speakers:

Farzad Tashtarian (Alpen-Adria-Universität – AAU)
Zili Meng (Hong Kong University of Science and Technology – HKUST)
Abdelhak Bentaleb (Concordia University)
Mahdi Dolati (Sharif University of Technology)

This tutorial focuses on the emerging need for ultra-low-latency video streaming and how AI-assisted coordination between codecs and network infrastructure can significantly improve performance. Traditional end-to-end streaming pipelines are often disjointed, leading to inefficiencies under tight latency constraints. We present a cross-layer approach that leverages AI for real-time encoding parameter adaptation, network-aware bitrate selection, and joint optimization across codec behavior and transport protocols. The tutorial examines the integration of AI models with programmable network architectures (e.g., SDN, P4) and modern transport technologies such as QUIC and Media over QUIC (MoQ) to minimize startup delay, stall events, and encoding overhead. Practical use cases and experimental insights illustrate how aligning codec dynamics with real-time network conditions enhances both QoE and system efficiency. Designed for both researchers and engineers, this session provides a foundation for developing next-generation intelligent video delivery systems capable of sustaining low-latency performance in dynamic environments.