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Application Flow Control In YouTube Video Streams
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Categories and Subject Descriptors
C.2.0 [Computer Communications Networks]: General
General Terms
Measurement, Performance
1. INTRODUCTION
YouTube [1] is a video-on-demand service that allows users to stream user-generated video content through their web
browser. According to the Alexa traffic rank [2], YouTube
is currently the third most popular website on the Internet
and has been noted in literature as being one of the primary
causes behind the recent increases in HTTP traffic observed
in measurement studies [3]. As a significant contributor to
traffic observed on the Internet, it is especially important
that YouTube traffic patterns are understood and modelled
correctly by Internet researchers. There has been a notable
quantity of work examining client behaviour, e.g. trends in
YouTube video popularity [4] [5], but there has been little
research into the behaviour of the YouTube servers them-
selves. Rather, there seems to be an implicit assumption
in the research community that YouTube traffic behaves in
much the same way as any other large HTTP download.
This paper presents an initial look at the application flow
control utilised by YouTube servers to conserve bandwidth
and prevent the client connection from being saturated. We
use passive packet header traces of YouTube traffic captured
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Thanks
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C.2.0 [Computer Communications Networks]: General
General Terms
Measurement, Performance
1. INTRODUCTION
YouTube [1] is a video-on-demand service that allows users to stream user-generated video content through their web
browser. According to the Alexa traffic rank [2], YouTube
is currently the third most popular website on the Internet
and has been noted in literature as being one of the primary
causes behind the recent increases in HTTP traffic observed
in measurement studies [3]. As a significant contributor to
traffic observed on the Internet, it is especially important
that YouTube traffic patterns are understood and modelled
correctly by Internet researchers. There has been a notable
quantity of work examining client behaviour, e.g. trends in
YouTube video popularity [4] [5], but there has been little
research into the behaviour of the YouTube servers them-
selves. Rather, there seems to be an implicit assumption
in the research community that YouTube traffic behaves in
much the same way as any other large HTTP download.
This paper presents an initial look at the application flow
control utilised by YouTube servers to conserve bandwidth
and prevent the client connection from being saturated. We
use passive packet header traces of YouTube traffic captured
-----
Not
After receive payment you will receive download link in paypal email address
Thanks
---
