7,065 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
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
MPEG-4 tools and applications: an overview
In this paper we present an overview of the software tools currently available for the creation and display of MPEG-4 content. We first describe tools for encoding raw video into MPEG-4 compliant bitstreams. We then describe how this content may be used to create a complete MPEG-4 scene containing both graphical and interactive elements in addition to the more usual video and audio elements. Clearly, MPEG-4 content cannot be viewed without appropriate decoders and players and these are addressed in the third section of this paper. Finally, we demonstrate how these tools may be combined together to create MPEG-4 applications by presenting the details of two sample applications we have developed
Optimized Adaptive Streaming Representations based on System Dynamics
Adaptive streaming addresses the increasing and heterogenous demand of
multimedia content over the Internet by offering several encoded versions for
each video sequence. Each version (or representation) has a different
resolution and bit rate, aimed at a specific set of users, like TV or mobile
phone clients. While most existing works on adaptive streaming deal with
effective playout-control strategies at the client side, we take in this paper
a providers' perspective and propose solutions to improve user satisfaction by
optimizing the encoding rates of the video sequences. We formulate an integer
linear program that maximizes users' average satisfaction, taking into account
the network dynamics, the video content information, and the user population
characteristics. The solution of the optimization is a set of encoding
parameters that permit to create different streams to robustly satisfy users'
requests over time. We simulate multiple adaptive streaming sessions
characterized by realistic network connections models, where the proposed
solution outperforms commonly used vendor recommendations, in terms of user
satisfaction but also in terms of fairness and outage probability. The
simulation results further show that video content information as well as
network constraints and users' statistics play a crucial role in selecting
proper encoding parameters to provide fairness a mong users and to reduce
network resource usage. We finally propose a few practical guidelines that can
be used to choose the encoding parameters based on the user base
characteristics, the network capacity and the type of video content
Joint On-the-Fly Network Coding/Video Quality Adaptation for Real-Time Delivery
This paper introduces a redundancy adaptation algorithm for an on-the-fly
erasure network coding scheme called Tetrys in the context of real-time video
transmission. The algorithm exploits the relationship between the redundancy
ratio used by Tetrys and the gain or loss in encoding bit rate from changing a
video quality parameter called the Quantization Parameter (QP). Our evaluations
show that with equal or less bandwidth occupation, the video protected by
Tetrys with redundancy adaptation algorithm obtains a PSNR gain up to or more 4
dB compared to the video without Tetrys protection. We demonstrate that the
Tetrys redundancy adaptation algorithm performs well with the variations of
both loss pattern and delay induced by the networks. We also show that Tetrys
with the redundancy adaptation algorithm outperforms FEC with and without
redundancy adaptation
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