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Notes on Barford SURGE paper

Notes on Barford SURGE paper. Ken Christensen Department of Computer Science and Engineering College of Engineering University of South Florida Tampa, FL 33620 christen@cse.usf.edu. The Paper. SIGMETRICS = Performance evaluation community. The abstract – first half.

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Notes on Barford SURGE paper

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  1. Notes on Barford SURGE paper Ken Christensen Department of Computer Science and Engineering College of Engineering University of South Florida Tampa, FL 33620 christen@cse.usf.edu

  2. The Paper SIGMETRICS = Performance evaluation community

  3. The abstract – first half Continued on next slide… Abstract == paper summary Abstract != paper introduction

  4. The abstract – second half

  5. 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.

  6. On-Off model of web workload The key picture that “tells the story”

  7. Key properties of web reference streams Six key properties • File size • Request size • Popularity • Embedded references • Temporal locality • Off times (inactive and active) Need to understand distribution and distribution parameters of each of the above.

  8. 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!

  9. Fitting continued Some fits (eyeballing)…

  10. Fitting continued And finally…

  11. Testing against SPECWeb And finally… SURGE SPECWeb

  12. In conclusion…

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