@inproceedings{TD:100150,
	att_abstract={This paper presents a new approach to determine the geographical
footprint of individual eyeball Autonomous Systems
(ASes). The key idea is to leverage the geo-location of
end-users associated with an eyeball AS to identify its geographical
footprint. We leverage the kernel density estimation
method to estimate the density of users across individual
eyeball ASes. This method enables us to cope with the error
associated with the location of end-users while controlling
the level of aggregation among data points to capture a geo-footprint
at the desired resolution. We use the resulting geo-footprint
of individual eyeball ASes to identify their likely
Point-of-Presence (PoP) locations. To demonstrate our proposed
technique, we use the inferred geo-locations of 48million
users from three popular P2P applications and assess
the geo- and PoP-level footprints of 1229 eyeball ASes. The
validation of the identified PoP locations by our technique
against online information and prior results by a commonly-used
technique based on traceroute shows a very high accuracy.
Leveraging the acquired PoP locations, we examine the
implications of geo-footprint of eyeball ASes on their connectivity
to the rest of the Internet. In particular, we present
a case study that reveals a much more complex picture of
AS-level connectivity as compared to what the more traditional
but geography-agnostic BGP- or traceroute-based approaches
show.},
	att_authors={ww9241},
	att_categories={},
	att_copyright={ACM},
	att_copyright_notice={(c) ACM, 2010. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Internet Measurement Conference {{, 2010-11-01}}{{, http://conferences.sigcomm.org/imc/2010/papers/p192.pdf}}},
	att_donotupload={},
	att_private={false},
	att_projects={},
	att_tags={{geo-location, geographic and connectivity of ASes, Autonomous Systems (ASes), end users ('eye balls')}},
	att_techdoc={true},
	att_techdoc_key={TD:100150},
	att_url={http://web1.research.att.com:81/techdocs_downloads/TD:100150_DS1_2010-11-08T04:16:26.477Z.pdf},
	author={Amir Rasti AND Nazanin Magharei AND Reza Rejaie AND Walter Willinger},
	booktitle={{Proc. of the 2010 ACM Internet Measurement Conference (IMC '10)}},
	institution={{IMC'10: Proceedings of the 2010 ACM  Internet Measurement Conference (IMC)}},
	month={November},
	pager={{192--198}},
	title={{Eyeball ASes: From Geography to Connectivity}},
	year=2010,
}