1 research outputs found
Mechanisms for Resilient Video Transmission
Wireless networks are envisaged to be one of the most important technologies
to provide cost-efficient content delivery, including for video applications.
They will allow thousands of thousands of fixed and mobile users to access,
produce, share, and consume video content in a ubiquitous way. Real-time video
services over these networks are becoming a part of everyday life and have been
used to spread information ranging from education to entertainment content.
However, the challenge of dealing with the fluctuating bandwidth, scarce
resources, and time-varying error rate of these networks, highlights the need
for error-resilient video transmission. In this context, the combination of
Forward Error Correction (FEC) and Unequal Error Protection (UEP) approaches is
known to provide the distribution of video applications for wireless users with
Quality of Experience (QoE) assurance. This thesis proposed a procedure to
assess the video characteristics and their related impact on the perceived
quality to end-users. This thesis proposes a series of cross-layer video-aware
and FEC-based mechanisms with UEP to enhance video transmission in several
types of wireless networks. A number of methods to set an adaptive amount of
redundancy were used in these mechanisms, such as heuristic techniques, random
neural networks, ant colony optimisation, and fuzzy logic. In the first one,
heuristic techniques, the mechanisms rely on human experience to define the
best strategy. The advantages and drawbacks of the proposed mechanisms were
demonstrated in realistic simulations using real video sequences and actual
network traces. The assessments were conducted with well-known QoE metrics. The
results show that all the proposed mechanisms were able to outperform the
competitors on both perceived video quality and network footprint.Comment: PhD Thesis, 196 pages http://hdl.handle.net/10316/3688