Crossover Scaling Effects in Aggregated TCP Traf c with Congestion Losses Institute for Security Technology Studies Dartmouth College 45 Lyme Rd., Suite 200 Hanover, NH 03755 Michael Liljenstam Renesys Corporation Hanover, NH 03755 Andy T. Ogielski ato@renesys.com mili@ists.dartmouth.edu ABSTRACT We critically examine the claims that TCP congestion control contributes to the observed self-similar tra c rate correlations. A simulation model is designed to analyze aggregated tra c of many TCP le transfers, with network topologies large enough so that each transfer has independent packet losses due to competition with other TCP traf c. To separate the e ects of session-level variability from network-level variability we examine tra c consisting of small xed-size les, and of heavy-tailed distribution of le sizes, with small variance of inter-session periods. We nd that, with increasing packet loss rate, tra c rate scaling crosses over from the regime dominated by le size distribution to another scaling regime that is independent of le sizes. That loss-dominated scaling stretches over the timescales from RTT to the longest consecutive TCP timeouts (hundreds of seconds), and is not asymptotic. Analysis at the ow level exposes the mechanism of the crossover, from scaling dominated by variability of
End of preview. The entire article is 12 pages. To view the full-text, please rent this article to continue.
/lp/association-for-computing-machinery/crossover-scaling-effects-in-aggregated-tcp-traffic-with-congestion-fZPhX2mDPN
Welcome to DeepDyve! Rent Premier Research Articles and Save Up to 90%
Crossover scaling effects in aggregated TCP traffic with congestion losses
Liljenstam, Michael; Ogielski, Andy T.
Follow ACM SIGCOMM Computer Communication Review
, Volume 32 (5)
Association for Computing Machinery – Nov 1, 2002
More Info
More Like This Article
View All dataSource[]=actageo&dataSource[]=aspet&dataSource[]=aaos&dataSource[]=aacc&dataSource[]=aacr&dataSource[]=aea&dataSource[]=aip&dataSource[]=ajnr&dataSource[]=ams&dataSource[]=aps_physical&dataSource[]=appi_book&dataSource[]=appi_journal&dataSource[]=apha&dataSource[]=asip&dataSource[]=asm&dataSource[]=asn&dataSource[]=aspb&dataSource[]=avs&dataSource[]=annual_reviews&dataSource[]=arxiv&dataSource[]=acm&dataSource[]=berghahn&dataSource[]=cabi&dataSource[]=clinical_trials&dataSource[]=dailymed&dataSource[]=degruyter&dataSource[]=du_press&dataSource[]=esa&dataSource[]=eu_press&dataSource[]=elsevier&dataSource[]=emerald&dataSource[]=ejtr&dataSource[]=emea&dataSource[]=epo&dataSource[]=faseb&dataSource[]=gsa&dataSource[]=health_affairs&dataSource[]=hindawi&dataSource[]=imanager&dataSource[]=imedpub&dataSource[]=informa_healthcare&dataSource[]=informs&dataSource[]=iop&dataSource[]=iucr&dataSource[]=iospress&dataSource[]=jbjs&dataSource[]=leftcoast&dataSource[]=lu_press&dataSource[]=mesharpe&dataSource[]=mary_ann_liebert&dataSource[]=medline&dataSource[]=mit_press&dataSource[]=nature&dataSource[]=oxford&dataSource[]=pier_professional&dataSource[]=pnas&dataSource[]=portlandpress&dataSource[]=psyc_articles&dataSource[]=psyc_books&dataSource[]=psyc_critiques&dataSource[]=plos_journal&dataSource[]=pubmed_central&dataSource[]=rsna&dataSource[]=rockefeller&dataSource[]=rcn&dataSource[]=ria&dataSource[]=rsc&dataSource[]=sage&dataSource[]=spie&dataSource[]=springer_journal&dataSource[]=springer&dataSource[]=taylor_francis&dataSource[]=aps&dataSource[]=the_scientist&dataSource[]=uc_press&dataSource[]=uspto_abstract&dataSource[]=wiley&dataSource[]=pct
© 2012 DeepDyve, Inc. All rights reserved.
Terms of Service | Privacy Policy
