Impact of flow-level dynamics on QoE of video streaming in wireless networks
Résumé
The Quality of Experience (QoE) of streaming service is often degraded by frequent playback interruptions. To mitigate the interruptions, the media player prefetches streaming contents before starting playback, at a cost of delay. We study the QoE of streaming from the perspective of flow dynamics. First, a framework is developed for QoE when streaming users join the network randomly and leave after downloading completion. We compute the distribution of prefetching delay using partial differential equations (PDEs), and the probability generating function of playout buffer starvations using ordinary differential equations (ODEs). Second, we extend our framework to characterize the throughput variation caused by opportunistic scheduling at the base station in the presence of fast fading. Our study reveals that the flow dynamics is the fundamental reason of playback starvation. The QoE of streaming service is dominated by the average throughput of opportunistic scheduling, while the variance of throughput has very limited impact on starvation behavior.
Mots clés
mobile radio
partial differential equations
probability
quality of experience
radio networks
video streaming
ODE
PDE
QoE
base station
fast fading presence
flow-level dynamics impact
frequent playback interruptions
interruption mitigation
media player
mobile networks
opportunistic scheduling
ordinary differential equations
playout buffer starvations
prefetching delay distribution
probability generating function
quality-of-experience
starvation behavior
streaming contents
video streaming service
wireless networks
Delays
Markov processes
Mathematical model
Prefetching
Streaming media
Throughput
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