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An analysis of Internet content delivery systems

Saroiu, Stefan, Gummadi, Krishna P., Dunn, Richard J., Gribble, Steven D., Levy, Henry M.·2002·ACM SIGOPS Operating Systems Review

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 lnternet 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 peer-to-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.

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Metadata

Authors
Saroiu, S., Gummadi, K. P., Dunn, R. J., Gribble, S. D., & Levy, H. M.
Venue
ACM SIGOPS Operating Systems Review
Published
2002-12-31
Volume
36
Issue
SI
Pages
315-327
ISSN
0163-5980 (ISSN-L)
OpenAlex
W1972699782
Cited by
546
References
0
FWCI
57.09
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: An analysis of Internet content delivery systems. https://app.cochat.ai/papers/10.1145/844128.844158
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Saroiu, S., Gummadi, K. P., Dunn, R. J., Gribble, S. D., & Levy, H. M. (2002). An analysis of Internet content delivery systems. ACM SIGOPS Operating Systems Review. https://doi.org/10.1145/844128.844158

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.