1,335 research outputs found
Q-AIMD: A Congestion Aware Video Quality Control Mechanism
Following the constant increase of the multimedia traffic, it seems necessary to allow transport protocols to be aware of the video quality of the transmitted flows rather than the throughput. This paper proposes a novel transport mechanism adapted to video flows. Our proposal, called Q-AIMD for video quality AIMD (Additive Increase Multiplicative Decrease), enables fairness in video quality while transmitting multiple video flows. Targeting video quality fairness allows improving the overall video quality for all transmitted flows, especially when the transmitted videos provide various types of content with different spatial resolutions. In addition, Q-AIMD mitigates the occurrence of network congestion events, and dissolves the congestion whenever it occurs by decreasing the video quality and hence the bitrate. Using different video quality metrics, Q-AIMD is evaluated with different video contents and spatial resolutions. Simulation results show that Q-AIMD allows an improved overall video quality among the multiple transmitted video flows compared to a throughput-based congestion control by decreasing significantly the quality discrepancy between them
Distributed Rate Allocation Policies for Multi-Homed Video Streaming over Heterogeneous Access Networks
We consider the problem of rate allocation among multiple simultaneous video
streams sharing multiple heterogeneous access networks. We develop and evaluate
an analytical framework for optimal rate allocation based on observed available
bit rate (ABR) and round-trip time (RTT) over each access network and video
distortion-rate (DR) characteristics. The rate allocation is formulated as a
convex optimization problem that minimizes the total expected distortion of all
video streams. We present a distributed approximation of its solution and
compare its performance against H-infinity optimal control and two heuristic
schemes based on TCP-style additive-increase-multiplicative decrease (AIMD)
principles. The various rate allocation schemes are evaluated in simulations of
multiple high-definition (HD) video streams sharing multiple access networks.
Our results demonstrate that, in comparison with heuristic AIMD-based schemes,
both media-aware allocation and H-infinity optimal control benefit from
proactive congestion avoidance and reduce the average packet loss rate from 45%
to below 2%. Improvement in average received video quality ranges between 1.5
to 10.7 dB in PSNR for various background traffic loads and video playout
deadlines. Media-aware allocation further exploits its knowledge of the video
DR characteristics to achieve a more balanced video quality among all streams.Comment: 12 pages, 22 figure
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
Performance evaluation of MPEG-4 video streaming over UMTS networks using an integrated tool environment
Universal Mobile Telecommunications System (UMTS) is a third-generation mobile communications system that supports wireless wideband multimedia applications. This paper investigates the video quality attained in streaming MPEG-4 video over UMTS networks using an integrated tool environment, which comprises an MPEG-4 encoder/decoder, a network simulator and video quality evaluation tools. The benefit of such an integrated tool environment is that it allows the evaluation of real video sources compressed using an MPEG-4 encoder. Simulation results show that UMTS Radio Link Control (RLC) outperforms the unacknowledged mode. The latter mode provides timely delivery but no error recovery. The acknowledged mode can deliver excellent perceived video quality for RLC block error rates up to 30% utilizing a playback buffer at the streaming client. Based on the analysis of the performance results, a self-adaptive RLC acknowledged mode protocol is proposed
- âŠ