  A substantial amount of work has recently gone into localizing BitTorrent
traffic within an ISP in order to avoid excessive and often times unnecessary
transit costs. Several architectures and systems have been proposed and the
initial results from specific ISPs and a few torrents have been encouraging. In
this work we attempt to deepen and scale our understanding of locality and its
potential. Looking at specific ISPs, we consider tens of thousands of
concurrent torrents, and thus capture ISP-wide implications that cannot be
appreciated by looking at only a handful of torrents. Secondly, we go beyond
individual case studies and present results for the top 100 ISPs in terms of
number of users represented in our dataset of up to 40K torrents involving more
than 3.9M concurrent peers and more than 20M in the course of a day spread in
11K ASes. We develop scalable methodologies that permit us to process this huge
dataset and answer questions such as: "\emph{what is the minimum and the
maximum transit traffic reduction across hundreds of ISPs?}", "\emph{what are
the win-win boundaries for ISPs and their users?}", "\emph{what is the maximum
amount of transit traffic that can be localized without requiring fine-grained
control of inter-AS overlay connections?}", "\emph{what is the impact to
transit traffic from upgrades of residential broadband speeds?}".
