Tiziana Refice
Tiziana received a Master's Degree in computer engineering at Roma Tre University in 2005 and a Ph.D. in networking at the same university in 2008 with a thesis on root cause analysis in inter-domain routing. She has worked as research engineer at the RIPE NCC on analysis of registration and routing data. She is currently working on Internet performance measurement.
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An Argument for Increasing TCP's Initial Congestion Window
Jerry Chu
Tom Herbert
Amit Agarwal
Arvind Jain
Natalia Sutin
ACM SIGCOMM Computer Communications Review, 40 (2010), pp. 27-33
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TCP flows start with an initial congestion window of at most four segments or approximately 4KB of data. Because most Web transactions are short-lived, the initial congestion window is a critical TCP parameter in determining how quickly flows can finish. While the global network access speeds increased dramatically on average in the past decade, the standard value of TCP’s initial congestion window has remained unchanged.
In this paper, we propose to increase TCP’s initial congestion window to at least ten segments (about 15KB). Through large-scale Internet experiments, we quantify the latency benefits and costs of using a larger window, as functions of network bandwidth, round-trip time (RTT), bandwidthdelay product (BDP), and nature of applications. We show that the average latency of HTTP responses improved by approximately 10% with the largest benefits being demonstrated in high RTT and BDP networks. The latency of low bandwidth networks also improved by a significant amount in our experiments. The average retransmission rate increased by a modest 0.5%, with most of the increase coming from applications that effectively circumvent TCP’s slow start algorithm by using multiple concurrent connections. Based on the results from our experiments, we believe the initial congestion window should be at least ten segments and the same be investigated for standardization by the IETF.
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Access and Analyze Broadband Measurements Collected using M-Lab
Summer 2010 ESCC/Internet2 Joint Techs
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Measurement Lab (M-Lab) is an open, distributed server platform for researchers, to deploy Internet measurement tools. Everybody can use M-Lab's tools to measure their own broadband connection performance. The M-Lab servers collect logs of all the users' tests and make them publicly available. As of July 2010, users have run millions of tests that have generated many terabytes of measurement data.
This talk will present the public repositories of M-Lab data and will explain how to analyze M-Lab data using Google's BigQuery. BigQuery stores M-Lab's measurements logs in a table with more than 60 billions of rows. It takes less than 1 minute to run a query against the whole dataset.
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As IPv4 address space approaches exhaustion, large networks are deploying IPv6 or preparing for deployment. However, there is little data available about the quantity and quality of IPv6 connectivity. We describe a methodology to measure IPv6 adoption from the perspective of a Web site operator and to evaluate the impact that adding IPv6 to a Web site will have on its users. We apply our methodology to the Google Web site and present results collected over the last year. Our data show that IPv6 adoption, while growing significantly, is still low, varies considerably by country, and is heavily influenced by a small number of
large deployments. We find that native IPv6 latency is comparable to IPv4 and provide statistics on IPv6 transition mechanisms used.
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