Delivering high-quality of video to end users over the best-effort Internet is a
challenging task since quality of streaming video is highly subject to network conditions. A fundamental issue in this area is how real-time applications cope with
network dynamics and adapt their operational behavior to offer a favorable streaming environment to end users.
As an effort towards providing such streaming environment, the first half of
this work focuses on analyzing the performance of video streaming in best-effort
networks and developing a new streaming framework that effectively utilizes unequal
importance of video packets in rate control and achieves a near-optimal performance
for a given network packet loss rate. In addition, we study error concealment methods
such as FEC (Forward-Error Correction) that is often used to protect multimedia
data over lossy network channels. We investigate the impact of FEC on the quality of
video and develop models that can provide insights into understanding how inclusion
of FEC affects streaming performance and its optimality and resilience characteristics
under dynamically changing network conditions.
In the second part of this thesis, we focus on measuring bandwidth of network
paths, which plays an important role in characterizing Internet paths and can benefit
many applications including multimedia streaming. We conduct a stochastic analysis of an end-to-end path and develop novel bandwidth sampling techniques that
can produce asymptotically accurate capacity and available bandwidth of the path
under non-trivial cross-traffic conditions. In addition, we conduct comparative performance study of existing bandwidth estimation tools in non-simulated networks
where various timing irregularities affect delay measurements. We find that when
high-precision packet timing is not available due to hardware interrupt moderation,
the majority of existing algorithms are not robust to measure end-to-end paths with
high accuracy. We overcome this problem by using signal de-noising techniques in
bandwidth measurement. We also develop a new measurement tool called PRC-MT
based on theoretical models that simultaneously measures the capacity and available
bandwidth of the tight link with asymptotic accuracy
