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 it’s 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. Second, we go beyond individual case studies and
present results for few thousands ISPs represented in our data set 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. Finally, we develop scalable methodologies
that allow us to process this huge data set and derive accurate traffic
matrices of torrents. Using the previous methods we obtain the following main findings:
i) Although there are a large number of very small ISPs without enough
resources for localizing traffic, by analyzing the 100 largest ISPs we show
that Locality policies are expected to significantly reduce the transit traffic
with respect to the default random overlay construction method in these ISPs;
ii) contrary to the popular belief, increasing the access speed of the clients
of an ISP does not necessarily help to localize more traffic; iii) by studying
several real ISPs, we have shown that soft speed-aware locality policies
guarantee win-win situations for ISPs and end users. Furthermore, the maximum
transit traffic savings that an ISP can achieve without limiting the number of
inter-ISP overlay links is bounded by “unlocalizable” torrents with few local
clients. The application of restrictions in the number of inter-ISP links leads
to a higher transit traffic reduction but the QoS of clients downloading
“unlocalizableȁ- ; torrents would be severely harmed.
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