3 research outputs found
Multi-Stream Rate Adaptation using Scalable Video Coding with Medium Grain Scalability
Multiple video streaming in a shared channel with constant
bandwidth requires rate adaptation in order to optimize the overall qual-
ity. In this paper we propose a multi-stream rate adaptation frame-
work with reference to the scalable video coding (SVC) extension of the
H.264/AVC standard with medium grain scalability (MGS) and qual-
ity layer (QL). We first provide a general discrete multi-objective prob-
lem formulation with the aim to maximize the sum of assigned rates
while minimizing the differences among distortions under a total bit-
rate constraint. A single-objective problem formulation is then derived
by applying a continuous relaxation to the problem. We also propose
a simplified continuous semi-analytical model that accurately estimates
the rate-distortion relationship and allows us to derive an optimal and
low-complexity procedure to solve the relaxed problem. The numerical
results show the goodness of our framework in terms of error gap between
the relaxed and its related discrete solutions, the significant performance
improvement with respect to an equal-rate adaptation scheme, and the
lower complexity with respect to a sub-optimal algorithm proposed in
the literature
Quality of Experience and Adaptation Techniques for Multimedia Communications
The widespread use of multimedia services on the World Wide Web and the advances
in end-user portable devices have recently increased the user demands for better quality.
Moreover, providing these services seamlessly and ubiquitously on wireless networks and
with user mobility poses hard challenges. To meet these challenges and fulfill the end-user
requirements, suitable strategies need to be adopted at both application level and network
level. At the application level rate and quality have to be adapted to time-varying bandwidth
limitations, whereas on the network side a mechanism for efficient use of the network
resources has to be implemented, to provide a better end-user Quality of Experience (QoE)
through better Quality of Service (QoS). The work in this thesis addresses these issues by
first investigating multi-stream rate adaptation techniques for Scalable Video Coding (SVC)
applications aimed at a fair provision of QoE to end-users. Rate Distortion (R-D) models
for real-time and non real-time video streaming have been proposed and a rate adaptation
technique is also developed to minimize with fairness the distortion of multiple videos
with difference complexities. To provide resiliency against errors, the effect of Unequal
Error protection (UXP) based on Reed Solomon (RS) encoding with erasure correction has
been also included in the proposed R-D modelling. Moreover, to improve the support of
QoE at the network level for multimedia applications sensitive to delays, jitters and packet
drops, a technique to prioritise different traffic flows using specific QoS classes within an
intermediate DiffServ network integrated with a WiMAX access system is investigated.
Simulations were performed to test the network under different congestion scenarios
Cross-layer Optimization for Video Delivery over Wireless Networks
As video streaming is becoming the most popular application of Internet mo-
bile, the design and the optimization of video communications over wireless
networks is attracting increasingly attention from both academia and indus-
try. The main challenges are to enhance the quality of service support, and to
dynamically adapt the transmitted video streams to the network condition.
The cross-layer methods, i.e., the exchange of information among different
layers of the system, is one of the key concepts to be exploited to achieve this
goals. In this thesis we propose novel cross-layer optimization frameworks
for scalable video coding (SVC) delivery and for HTTP adaptive streaming
(HAS) application over the downlink and the uplink of Long Term Evolution
(LTE) wireless networks. They jointly address optimized content-aware rate
adaptation and radio resource allocation (RRA) with the aim of maximiz-
ing the sum of the achievable rates while minimizing the quality difference
among multiple videos. For multi-user SVC delivery over downlink wireless
systems, where IP/TV is the most representative application, we decompose
the optimization problem and we propose the novel iterative local approxi-
mation algorithm to derive the optimal solution, by also presenting optimal
algorithms to solve the resulting two sub-problems. For multiple SVC de-
livery over uplink wireless systems, where healt-care services are the most
attractive and challenging application, we propose joint video adaptation
and aggregation directly performed at the application layer of the transmit-
ting equipment, which exploits the guaranteed bit-rate (GBR) provided by
the low-complexity sub-optimal RRA solutions proposed. Finally, we pro-
pose a quality-fair adaptive streaming solution to deliver fair video quality
to HAS clients in a LTE cell by adaptively selecting the prescribed (GBR)
of each user according to the video content in addition to the channel condi-
tion. Extensive numerical evaluations show the significant enhancements of
the proposed strategies with respect to other state-of-the-art frameworks