QoS aware traffic shaping for TikTok live streaming over congested LAN using MikroTik queue tree

Abstract

Real time video streaming applications such as TikTok Live are highly sensitive to network instability, especially under bandwidth contention on shared access networks. This paper evaluates a Quality of Service (QoS)-aware traffic shaping scheme for TikTok live streaming in a congested local area network using a MikroTik router with a queue tree configuration. TikTok traffic is identified and assigned minimum bandwidth guarantees and highest priority, while non streaming traffic is treated as best effort. Network performance is assessed under two scenarios: baseline (without shaping) and experiment (with shaping), sing the TIPHON standard and four QoS parameters: throughput, delay, jitter, and packet loss. The experimental results show that although the average throughput only increases slightly from 70.67 Kbps to 80 Kbps and remains in the “Poor” category, the proposed scheme significantly improves temporal QoS metrics: average delay is reduced from 88.65 ms to 45.16 ms (“Very Good”), jitter decreases from 95.61 ms to 89.80 ms (“Good”), and packet loss drops from 7.66% to 3.78% (“Good”). These findings indicate that priority-based traffic shaping using a queue tree can effectively stabilize latency and data delivery for TikTok live streaming on bandwidth-limited networks without requiring capacity upgrades.