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  4. Improving Streaming Performance over Wired and Wireless networks : A Similarity Based Frame Discard Algorithm and A Trend Based Loss Differentiation Algorithm
 
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Improving Streaming Performance over Wired and Wireless networks : A Similarity Based Frame Discard Algorithm and A Trend Based Loss Differentiation Algorithm

Date Issued
2004
Date
2004
Author(s)
Hsu, Ming-Wei
DOI
en-US
URI
http://ntur.lib.ntu.edu.tw//handle/246246/53966
Abstract
Streaming is more challenging in a wireless network than in a wired network, because wireless networks have their own characteristics such as low bandwidth and high bit error rate. We propose two schemes to address these issues. When we deliver a video stream across a bandwidth-constrained network, loss of frames may be unavoidable. To maximize the perceived quality-of-service at the client side, it is desirable to find a server transmission schedule that can transmit important frames first and utilize the network resources efficiently. To address this issue, we develop Similarity-based Frame Discard (SimFD). Unlike previous works, we select frames into transmission schedule by taking both frame similarity and inter-frame dependency into account. The frames that are less similar with their previous frame will get higher priority. TCP Friendly Rate Control (TFRC) is a widely accepted rate control method for streaming in the Internet. It assumes that packet losses are primarily due to congestion, and reduces sending rate in the present of packet losses. But this is not applicable to wireless networks in which the bulk of packet losses are due to wireless channel error and not relative to congestion. To help TFRC differentiate the losses caused by wireless channel error and avoid reducing sending rate blindly, we develop an end-to-end approach, Trend and Loss Density based Loss Differentiation Algorithm (TD). Our approach is based on the observation that congestion losses often occur after the ROTT peak and always appear in burst.
Subjects
無線
網路
串流
wireless
streaming
frame
network
Type
thesis
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ntu-93-R91922064-1.pdf

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23.31 KB

Format

Adobe PDF

Checksum

(MD5):cf85e20090e67318d9626e7277a90c88

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