Characterizing QoE in Large-Scale Live Streaming
| Autor: | Jussara M. Almeida, Italo Cunha, Alex Borges Vieira, Idilio Drago, Thiago Guarnieri |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Internet
Multimedia video streaming business.industry Computer science streaming media 020206 networking & telecommunications 020207 software engineering 02 engineering and technology quality of experience computer.software_genre Live streaming Server Bit rate 0202 electrical engineering electronic engineering information engineering The Internet Quality of experience business computer |
| Zdroj: | GLOBECOM |
| Popis: | Understanding the impact of performance degradation on users' QoE during live Internet streaming is key to maximize the audience and increase content providers' revenues. It is known that some problems have a strong correlation with low QoE--e.g., users experiencing video stalls tend to leave video sessions earlier. It is, however, mostly unknown whether such observations hold for live streaming of large-scale events (e.g., the FIFA World Cup). Such events are particular due to the widespread interest in the streamed content, reaching an impressively high audience worldwide. We study whether and to what extent performance degradation during live streaming of large-scale events affects users' QoE. We leverage a unique dataset collected from a major content provider in South America during the 2014 FIFA Soccer World Cup. We first extract performance metrics from the logs: stream bitrate, bitrate switches, playback stalls, and playback startup latency. We then correlate these performance metrics with session duration, which we use as a QoE indicator. We confirm the strong correlations between the metrics and QoE indicators; in particular, frequent stalls are often accompanied by higher probability of early session termination. Moreover, we quantify how such correlations vary according to broadcast matches and client terminals. Some of our findings challenge intuition--e.g., we find that PC users seem more tolerant to problems than users on mobile terminals. Our results provide better understanding of user QoE and are an important step towards user QoE models in large-scale events. |
| Databáze: | OpenAIRE |
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