Demonstrating a Framework for KPI/KQI Analysis of Network Management on a Short-Form Video Use Case

Delivering popular short video streaming services like TikTok, Instagram Reels, or YouTube Shorts, poses substantial challenges for service providers and network operators. This is not only due to high download volumes but also due to high-volume pre-loading strategies that cause high bandwidth demand variations. These strategies, designed to reduce initial delays, can additionally lead to bandwidth excess when users swipe quickly through videos and consume only a fraction of downloaded content. This creates inefficiencies and unbalanced network resource utilization, particularly in competitive bandwidth environments. To address these challenges, we investigate the effectiveness of bandwidth capping in this paper, i.e., limiting the throughput of video flows in the network. We first propose a novel framework for measuring network Key Performance Indicators (KPIs) and application Key Quality Indicators (KQIs), before we conduct experimental studies to analyze the impact of capping on network interactions and KQIs of three popular short video services in different scenarios. We find that capping substantially reduces download volume (15% – 45% median reduction) and bandwidth excess (18% – 52% mean reduction), while bandwidth utilization fairness improves. Meanwhile, KQIs surprisingly remain nearly unaffected in most cases, with only minor statistical differences in a few scenarios. Finally, we reflect on our measurement methdology, and discuss potential enhancements.