Many applications require the association of Internet numbering resources with an accurate geographic label at some granularity. For some applications, knowing the country of origin might be sufficient; for others a more precise indication at state, city or zip code granularity, or even a specific latitude/longitude is needed.

However, which method(s) work best? Which database sources and services are most reliable, at what geographic resolutions? If a data source provides the geographic location of the owner of an IP address, is this location the same as the location where the device is actually broadcasting and receiving packets? And, if different, can the difference be quantified?

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This month Internet2’s new UCAN project issued a call for white papers on how they could use their $65M BTOP grant in operationally sustainable ways, i.e., so the infrastructure they build will have a chance of surviving when the federal stimulus project money runs out.

We held a relevant workshop 5 years ago, part of which was published in CommLaw the following year. I’ve also written several other essays on related issues:

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Amidst the recent political unrest in the Middle East, researchers have observed significant changes in Internet traffic and connectivity. In this article we tap into a previously unused source of data: unsolicited Internet traffic arriving from Libya. The traffic data we captured shows distinct changes in unsolicited traffic patterns since 17 February 2011.

I post this article to describe the results of my five month visit to CAIDA and UC San Diego, and to thank the organizations that collaborated to make this work possible.

• CAIDA welcomed me as a visitor to UCSD’s renowned San Diego Supercomputer Center, to work on a new tool for Internet data visualization which we are calling “Caidagram”;
• RIPE NCC sponsored my visit at CAIDA, part of their continual efforts to cooperate with top Internet research groups in the world;
• Roma Tre is the University where I started a PhD program with the Compunet research group, after obtaining my Master’s degree accompanied by an internship held at the RIPE NCC.

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My recently submitted public comments on the increasingly controversial issue of ICANN’s plans to expand the generic Top Level Domain namespace indefinitely:

1. a repeat of my still unaddressed comments from the last (June 2010) economic report,
   
2. an attempt to summarize some public comments to that June 2010 report,
3. end an abbreviated historical timeline of ICANN’s economic research commitment to launching new gTLDs.

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Among the interesting meetings I attended in 2010 was the principal investigators (PI) meeting for NSF’s new “Future Internet Architecture” (FIA) program. The FIA program builds on the successes of NSF’s previous Future Internet Design (FIND) program, the recommendations of a review panel, and a community summit in October 2009. (The FIND program itself has been integrated into NSF’s new Network Science and Engineering research program, while the four FIA teams are attempting to implement some of the ideas developed thus far.) CAIDA is participating in one of these projects — Named Data Networking (NDN), led by Van Jacobson at Xerox Parc and Lixia Zhang at UCLA. (Background links to 2010 technical report describing the proposed architecture, Van’s August 2006 video lecture and 2009 ACM Queue Q&A on NDN ideas.)

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I recently attended my first FCC Technological Advisory Council meeting (video archives). A week before the meeting we received a memo from the chairman of the committee (Tom Wheeler) notifying the committee of a “clear and challenging mandate from Chairman Genachowski: to generate ideas and spur actions that lead to job creation and economic growth in the ICT [information and communication technologies] ecosystem.” Specifically, “The TAC will focus on the short term implementation of innovative ideas to create investment and jobs, as opposed to long term regulatory changes.”

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[Executive Summary from our annual report for 2009, which took longer than we expected to finish this year as we’ve been overly busy with material for 2010’s report..]

Our current research projects span topology, routing, traffic, economics, and policy. Our infrastructure activities support several measurement-based studies of the Internet’s core infrastructure, with focus on the health and integrity of the global Internet’s topology, routing, addressing, and naming systems.

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[I submitted the following public comment to ICANN in response to their second attempt at commissioning An Economic Framework for the Analysis of the Expansion of Generic Top-Level Domain Names. I’ll link to ICANN’s summary of all public comments on this report when available. -k]

This second economic report posted 16 june (pdf) is an improvement over the June 2009 reports by Dennis Carlton (pdf, pdf) but there are still too many — and too fundamental — flaws for it to serve as the basis of any ICANN policy on new gTLDs:

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We have performed an analysis of the IP-AS mapping obtained from Routeviews/RIPE collectors.

A crucial step in various research efforts that study the Internet infrastructure is to map an IP address to the Autonomous System (AS) to which it is assigned. The most common approach to map IP addresses to ASes is by using BGP table dumps from public repositories such as Routeviews and RIPE. We assign “ownership” of an IP address to the AS that originates the longest BGP prefix that matches the IP address. Routeviews and RIPE, however, have multiple collectors, each of which peers with a diverse set of ASes. Consequently, the IP-AS mapping obtained by using the BGP table dump from one collector could be different from that obtained from a different collector. The obvious solution is to aggregate views from as many vantage points as possible to obtain the most complete IP-AS mapping possible. In practice, however, it is common to use data from just one or two collectors, as it greatly simplifies the process of collecting and pre-processing data. The goal of our analysis is to compare different collectors, in terms of the different metrics that we are interested in, viz. address space coverage, IP-AS mapping, unique ASes, unique prefixes, unique more specific prefixes, AS links, and AS paths. Further, we study the utility of adding data from more collectors, in terms of the resulting change in the aforementioned metrics. Finally, we compare the IP-AS mapping from Routeviews and RIPE tables with that obtained from Team Cymru’s whois service.

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