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A methodology for estimating interdomain web traffic demand
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Source Internet Measurement Conference archive
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement table of contents
Taormina, Sicily, Italy
SESSION: Bandwidth and traffic estimation techniques table of contents
Pages: 322 - 335  
Year of Publication: 2004
ISBN:1-58113-821-0
Authors
Anja Feldmann  Technische Universität München
Nils Kammenhuber  Technische Universität München
Olaf Maennel  Technische Universität München
Bruce Maggs  Carnegie Mellon University, Pittsburgh, PA and Akamai Technologies
Roberto De Prisco  Università di Salerno and Akamai Technologies
Ravi Sundaram  Northeastern University and Akamai Technologies
Sponsors
SIGCOMM: ACM Special Interest Group on Data Communication
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
Bibliometrics
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ABSTRACT

This paper introduces a methodology for estimating interdomain Web traffic lows between all clients worldwide and the ervers belonging to over one housand content providers. The idea is to use the server logs from a large ontent Delivery Network (CDN) to identify client downloads of content provider (i.e., publisher) Web pages. For each of these Web pages, a client typically downloads some objects from the content provider, some from the CDN, and perhaps some from third parties such as banner advertisement agencies. The sizes and sources of the non-CDN downloads associated with each CDN download are estimated separately by examining Web accesses in packet traces collected at several universities.

The methodology produces a (time-varying) interdomain HTTP traffic demand matrix pairing several hundred thousand blocks of client IP addresses with over ten thousand individual Web servers. When combined with geographical databases and routing tables, the matrix can be used to provide (partial) answers to questions such as "How do Web access patterns vary by country?", "Which autonomous systems host the most Web content?", and "How stable are Web traffic flows over time?".


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Collaborative Colleagues:
Anja Feldmann: colleagues
Nils Kammenhuber: colleagues
Olaf Maennel: colleagues
Bruce Maggs: colleagues
Roberto De Prisco: colleagues
Ravi Sundaram: colleagues