TrustXQoE is a large-scale, human-annotated dataset for HTTP Live Streaming research, collected in an SDN-CDN edge environment. The dataset includes synchronized measurements from multiple layers of the video delivery chain, such as client playback, network QoS, server metrics, and MOS/QoE labels. It was authored by Abdelhak Heroucha and published on Harvard Dataverse in May 2026.
Use Cases
- Predicting Mean Opinion Score (MOS) based on synchronized multi-layer measurements.
- Analyzing Quality of Experience (QoE) and Quality of Service (QoS) relationships in edge video streaming.
- Researching trust-aware networking and explainable AI models for video delivery systems.
- Evaluating the performance of SDN-CDN architectures for video streaming.
Strengths
- Dataset is described as large-scale and human-annotated.
- Includes synchronized measurements from multiple layers of the video delivery chain.
- Designed for research on multiple specific topics, including QoE/QoS analysis and MOS prediction.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count and file size are unknown, which may limit suitability assessment.
- Data may reflect temporal or source bias inherent to the collection environment.
Provenance
- Source
- Harvard Dataverse
- Collection Method
- Collected in an SDN-CDN edge video streaming environment.
- Time Range
- null
- Freshness
- Last updated 2026-05-07 13:29:28; freshness should be verified.
- Geography
- null