Transcript HSSG CFI - University of South Florida

Notes on Barford SURGE paper
Ken Christensen
Department of Computer Science and Engineering
College of Engineering
University of South Florida
Tampa, FL 33620
[email protected]
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The Paper
SIGMETRICS = Performance
evaluation community
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The abstract – first half
Abstract == paper summary
Abstract != paper introduction
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Continued on next slide…
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The abstract – second half
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Goal of the work
Our goal is to imitate closely a stream of HTTP requests
originating from a fixed population of Web users.
For doing this better than anyone else Paul Barford earned a PhD.
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On-Off model of web workload
The key picture that “tells the story”
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Key properties of web reference streams
Six key properties
1) File size
2) Request size
3) Popularity
4) Embedded references
5) Temporal locality
6) Off times (inactive and active)
Need to understand distribution and distribution parameters
of each of the above.
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Finding distributions and parameters
More-or-less did curve fitting
• Matched measurements from traces to distributions
• Used statistical tests to gauge goodness of fit
An eyeball test for matching curves (histograms) is
sometimes the best statistical test!
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Fitting continued
Some fits (eyeballing)…
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Fitting continued
And finally…
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Testing against SPECWeb
And finally…
SURGE
SPECWeb
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In conclusion…
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