1,414 research outputs found
QoE-Based Low-Delay Live Streaming Using Throughput Predictions
Recently, HTTP-based adaptive streaming has become the de facto standard for
video streaming over the Internet. It allows clients to dynamically adapt media
characteristics to network conditions in order to ensure a high quality of
experience, that is, minimize playback interruptions, while maximizing video
quality at a reasonable level of quality changes. In the case of live
streaming, this task becomes particularly challenging due to the latency
constraints. The challenge further increases if a client uses a wireless
network, where the throughput is subject to considerable fluctuations.
Consequently, live streams often exhibit latencies of up to 30 seconds. In the
present work, we introduce an adaptation algorithm for HTTP-based live
streaming called LOLYPOP (Low-Latency Prediction-Based Adaptation) that is
designed to operate with a transport latency of few seconds. To reach this
goal, LOLYPOP leverages TCP throughput predictions on multiple time scales,
from 1 to 10 seconds, along with an estimate of the prediction error
distribution. In addition to satisfying the latency constraint, the algorithm
heuristically maximizes the quality of experience by maximizing the average
video quality as a function of the number of skipped segments and quality
transitions. In order to select an efficient prediction method, we studied the
performance of several time series prediction methods in IEEE 802.11 wireless
access networks. We evaluated LOLYPOP under a large set of experimental
conditions limiting the transport latency to 3 seconds, against a
state-of-the-art adaptation algorithm from the literature, called FESTIVE. We
observed that the average video quality is by up to a factor of 3 higher than
with FESTIVE. We also observed that LOLYPOP is able to reach a broader region
in the quality of experience space, and thus it is better adjustable to the
user profile or service provider requirements.Comment: Technical Report TKN-16-001, Telecommunication Networks Group,
Technische Universitaet Berlin. This TR updated TR TKN-15-00
A control theoretic approach to achieve proportional fairness in 802.11e EDCA WLANs
This paper considers proportional fairness amongst ACs in an EDCA WLAN for
provision of distinct QoS requirements and priority parameters. A detailed
theoretical analysis is provided to derive the optimal station attempt
probability which leads to a proportional fair allocation of station
throughputs. The desirable fairness can be achieved using a centralised
adaptive control approach. This approach is based on multivariable statespace
control theory and uses the Linear Quadratic Integral (LQI) controller to
periodically update CWmin till the optimal fair point of operation. Performance
evaluation demonstrates that the control approach has high accuracy performance
and fast convergence speed for general network scenarios. To our knowledge this
might be the first time that a closed-loop control system is designed for EDCA
WLANs to achieve proportional fairness
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