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Notes on Barford SURGE paperNotes on Barford SURGE paper
Ken ChristensenDepartment of Computer Science and Engineering
College of EngineeringUniversity of South Florida
Tampa, FL [email protected]
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The PaperThe Paper
SIGMETRICS = Performance evaluation community
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The abstract – first halfThe abstract – first half
Continued on next slide…Abstract == paper summaryAbstract != paper introduction
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The abstract – second halfThe abstract – second half
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Goal of the workGoal of the work
Our goal is to imitate closely a stream of HTTP requestsoriginating 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 workloadOn-Off model of web workload
The key picture that “tells the story”
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Key properties of web reference streamsKey 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 parametersFinding 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 Fitting continuedcontinued
Some fits (eyeballing)…
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Fitting Fitting continuedcontinued
And finally…
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Testing against SPECWebTesting against SPECWeb
And finally…
SURGE
SPECWeb
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In conclusion…In conclusion…
