Multimedia applications over the Internet are getting more and more popular. While
non-real-time streaming services, such as YouTube and Megavideo, are attracting
millions of visiting per day, real-time conferencing applications, of which some
instances are Skype and Yahoo Voice Chat, provide an interesting experience of
communication. Together, they make the fancy Internet world become more and more
amusing. Undoubtedly, multimedia flows will eventually dominate the computer
network in the future.
As the population of multimedia flows increases gradually on the Internet, quality of
their service (QoS) is more of a concern. At the moment, the Internet does not have any
guarantee on the quality of multimedia services. To completely surpass this limitation,
modifications to the network structure is a must. However, it will take years and billions
of dollars in investment to achieve this goal. Meanwhile, it is essential to find alternative
ways to improve the quality of multimedia services over the Internet.
In the past few years, many endeavors have been carried on to solve the problem.
One interesting approach focuses on the development of end-to-end congestion control strategies for UDP multimedia flows. Traditionally, packet losses and delays have been
commonly used to develop many known control schemes. Each of them only
characterizes some different aspects of network congestion; hence, they are not ideal as
feedback signals alone. In this research, the flow accumulation is the signal used in
feedback for flow control. It has the advantage of reflecting both packet losses and
delays; therefore, it is a better choice. Using network simulations, the accumulations of
real-time audio applications are collected to construct adaptive flow controllers. The
reason for choosing these applications is that they introduce more control challenges
than non-real-time services.
One promising flow control strategy was proposed by Bhattacharya and it was based
on Model Predictive Control (MPC). The controller was constructed from an ARX
predictor. It was demonstrated that this control scheme delivers a good QoS while
reducing bandwidth use in the controlled flows by 31 percent to 44 percent. However, the controller
sometime shows erratic response and bandwidth usage jumps frequently between lowest
and highest values. This is not desirable. For an ideal controller, the controlled
bandwidth should vary near its mean. To eliminate the deficiency in the strategy
proposed by Bhattacharya, it is proposed to introduce a feed forward term into the MPC
formulation, in addition to the feedback terms. Simulations show that the modified MPC
strategy maintains the benefits of the Bhattacharya strategy. Furthermore, it increases the
probability of bandwidth savings from 58 percent for the case of Bhattacharya model to about
99 percent for this work.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2010-12-8949 |
| Date | 2010 December 1900 |
| Creators | Duong, Thien Chi |
| Contributors | Parlos, Alexander G. |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Thesis, text |
| Format | application/pdf |
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