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An Analysis of Internet Content Delivery Systems (2002)

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by Stefan Saroiu , Krishna P. Gummadi , Richard J. Dunn , Steven D. Gribble , Henry M. Levy
Citations:239 - 10 self
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Metadata Version 1

DatumValueSource
TITLE An Analysis of Internet Content Delivery Systems INFERENCE
AUTHOR NAME Stefan Saroiu SVM HeaderParse 0.2
AUTHOR AFFIL Department of Computer Science & Engineering; University of Washington SVM HeaderParse 0.2
AUTHOR NAME Krishna P. Gummadi SVM HeaderParse 0.2
AUTHOR AFFIL Department of Computer Science & Engineering; University of Washington SVM HeaderParse 0.2
AUTHOR NAME Richard J. Dunn SVM HeaderParse 0.2
AUTHOR AFFIL Department of Computer Science & Engineering; University of Washington SVM HeaderParse 0.2
AUTHOR NAME Steven D. Gribble SVM HeaderParse 0.2
AUTHOR AFFIL Department of Computer Science & Engineering; University of Washington SVM HeaderParse 0.2
AUTHOR NAME Henry M. Levy SVM HeaderParse 0.2
AUTHOR AFFIL Department of Computer Science & Engineering; University of Washington SVM HeaderParse 0.2
ABSTRACT In the span of only a few years, the Internet has experienced an astronomical increase in the use of specialized content delivery systems, such as content delivery networks and peer-to-peer file sharing systems. Therefore, an understanding of content delivery on the Internet now requires a detailed understanding of how these systems are used in practice. This paper examines content delivery from the point of view of four content delivery systems: HTTP web traffic, the Akamai content delivery network, and Kazaa and Gnutella peer-to-peer file sharing traffic. We collected a trace of all incoming and outgoing network traffic at the University of Washington, a large university with over 60,000 students, faculty, and staff. From this trace, we isolated and characterized traffic belonging to each of these four delivery classes. Our results (1) quantify the rapidly increasing importance of new content delivery systems, particularly peerto-peer networks, (2) characterize the behavior of these systems from the perspectives of clients, objects, and servers, and (3) derive implications for caching in these systems. 1 SVM HeaderParse 0.2
YEAR 2002 INFERENCE
VENUE TYPE CONFERENCE INFERENCE
CITATIONS 33 found ParsCit 1.0
The National Science Foundation
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