4,675 research outputs found
Traffic Profiling for Mobile Video Streaming
This paper describes a novel system that provides key parameters of HTTP
Adaptive Streaming (HAS) sessions to the lower layers of the protocol stack. A
non-intrusive traffic profiling solution is proposed that observes packet flows
at the transmit queue of base stations, edge-routers, or gateways. By analyzing
IP flows in real time, the presented scheme identifies different phases of an
HAS session and estimates important application-layer parameters, such as
play-back buffer state and video encoding rate. The introduced estimators only
use IP-layer information, do not require standardization and work even with
traffic that is encrypted via Transport Layer Security (TLS). Experimental
results for a popular video streaming service clearly verify the high accuracy
of the proposed solution. Traffic profiling, thus, provides a valuable
alternative to cross-layer signaling and Deep Packet Inspection (DPI) in order
to perform efficient network optimization for video streaming.Comment: 7 pages, 11 figures. Accepted for publication in the proceedings of
IEEE ICC'1
Anticipatory Buffer Control and Quality Selection for Wireless Video Streaming
Video streaming is in high demand by mobile users, as recent studies
indicate. In cellular networks, however, the unreliable wireless channel leads
to two major problems. Poor channel states degrade video quality and interrupt
the playback when a user cannot sufficiently fill its local playout buffer:
buffer underruns occur. In contrast to that, good channel conditions cause
common greedy buffering schemes to pile up very long buffers. Such
over-buffering wastes expensive wireless channel capacity.
To keep buffering in balance, we employ a novel approach. Assuming that we
can predict data rates, we plan the quality and download time of the video
segments ahead. This anticipatory scheduling avoids buffer underruns by
downloading a large number of segments before a channel outage occurs, without
wasting wireless capacity by excessive buffering. We formalize this approach as
an optimization problem and derive practical heuristics for segmented video
streaming protocols (e.g., HLS or MPEG DASH). Simulation results and testbed
measurements show that our solution essentially eliminates playback
interruptions without significantly decreasing video quality
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