Abstract
The exponential increase in Dynamic Adaptive Streaming over HTTP (DASH) based video traffic with endto-end encryption poses many challenges for Mobile Network Operators (MNOs). To improve user-perceived video quality, MNOs must be aware of the end user’s Quality of Experience (QoE) by exploring network level Quality of Service (QoS). On the contrary, the network edge facility provides proximity for performing an intelligent operation to maintain smooth QoE from the network level QoS measurement. Therefore, in this work, we propose EFFECTOR, a framework to showcase lightweight in-band QoS features measurement technique at edge nodes from encrypted DASH video traffic. EFFECTOR uses an emulated environment with real 4G and 5G drive test traces to generate video traffic. Moreover, this work provides a massive dataset for analyzing the impact of 4G and 5G technology on video quality in the form of Interactive Jupyter Notebooks. The proposed framework is ideal for investigating QoS extracted from the network’s edge and finding its relations with QoE to ensure better video quality for end-users.
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