A Comparison of Bandwidth Smoothing Techniques for the Transmission of Prerecorded Compress.pdf
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A Comparison of Bandwidth Smoothing Techniques for the Transmission of Prerecorded Compress
A Comparison of Bandwidth Smoothing Techniques for the Transmission of
Prerecorded Compressed Video
Wu-chi Feng
Dept. of Comp. and Info. Sci.
The Ohio State University
Columbus, OH 43210
wuchi@
Jennifer Rexford
Networking and Distributed Systems
ATT Labs Research
Murray Hill, NJ 07974
jrex@
Abstract
The transfer of prerecorded, compressed video requires
multimedia services to support large fluctuations in band-
width requirements on multiple time scales. Bandwidth
smoothing techniques can reduce the burstiness of a vari-
able-bit-rate stream by prefetching data at a series of fixed
rates, simplifying the allocation of resources in video serv-
ers and the communication network. Given a fixed client-
side prefetch buffer, several bandwidth smoothing algo-
rithms have been introduced that are provably optimal
under certain constraints. This paper presents a collection
of metrics for comparing these smoothing algorithms and
evaluating their cost-performance trade-offs. Due to the
scarcity of available trace data, we have constructed a
video capture testbed and generated a collection of twenty
full-length, motion-JPEG encoded video clips. Using these
video traces and a range of client buffer sizes, we investi-
gate the interplay between the performance metrics through
simulation experiments. The results highlight the unique
strengths and weaknesses of each algorithm.
1. Introduction
Many emerging multimedia applications, such as digital
libraries and video-on-demand services, rely on the effi-
cient transfer of prerecorded video. Effective compression
techniques, such as MPEG [1] and motion-JPEG, can sub-
stantially reduce the resource requirements for storing and
transmitting video streams. However, compressed video
traffic typically exhibits significant burstiness on multiple
time scales, due to the frame structure of the compression
algorithm as well as natural variations within and between
scenes[2-4]. This bursty, variable-bit-rate traffic compli-
cates the effort
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