StreamGuard: Exploring a 5G Architecture for Efficient, Quality of Experience-Aware Video Conferencing

TL;DR

StreamGuard is a practical 5G architecture that enhances video conferencing QoE by subflow-level prioritization, monitoring, and application shaping, achieving significant QoE improvements and fairness.

Contribution

It introduces a novel, real-time QoE-aware prioritization framework for 5G networks, integrating deep packet inspection and application control mechanisms.

Findings

QoE improved by up to 70% over baseline methods.

Achieves better QoE-fairness tradeoff in 5G video conferencing.

Supports higher background throughput while maintaining QoE.

Abstract

Video conferencing over 5G is increasingly prevalent, yet its Quality of Experience (QoE) often degrades under limited radio resources. This has two causes: 5G networks must serve many users, while interactive traffic requires careful handling. Motivated by the insight that different subflows within an interactive session have a disproportionate effect on QoE, we present the design and implementation of StreamGuard, a practical 5G architecture for subflow-level, QoE-aware prioritization. StreamGuard forms a closed control loop with three components: (1) a monitor in the Radio Access Network (RAN) that uses deep packet inspection to infer QoE and RAN state, (2) a controller that selects prioritization actions to balance QoE and fairness, and (3) a marking module that applies these decisions by marking packets to steer subflows into appropriate priority queues. StreamGuard further shapes application behaviors via mechanisms including selective subflow dropping and probe-based rate control, to align application behavior with radio constraints. Implemented in a real 5G testbed, StreamGuard achieves a superior QoE-fairness tradeoff compared to vanilla 5G and prior state-of-the-art approaches, improving QoE by up to 70% at comparable background throughput or preserving up to 2x higher background throughput at similar QoE.