Exploiting Locality of Interest in Online Social Networks
Mike P. Wittie
Veljko Pejovic
Lara Deek
Kevin Almeroth
Ben Y. Zhao
ACM Conference on emerging Networking EXperiments and Technologies (CoNEXT 2010)
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Paper Abstract
Online Social Networks (OSN) are fun, popular, and socially significant.
An integral part of their success is the immense size of their global
user base. To provide a consistent service to all users, Facebook, the
world's largest OSN, is heavily dependent on centralized U.S. data
centers, which renders service outside of the U.S. sluggish and wasteful
of Internet bandwidth. In this paper, we investigate the detailed causes
of these two problems and identify mitigation opportunities. Because
details of Facebook's service remain proprietary, we treat the OSN as a
black box and reverse engineer its operation from publicly available
traces. We find that contrary to current wisdom, OSN state is amenable
to partitioning and that its fine grained distribution and processing
can significantly improve performance without loss in service
consistency. Through simulations of reconstructed Facebook traffic over
measured Internet paths, we show that user requests can be processed
79% faster and use 91% less bandwidth. We conclude that the
partitioning of OSN state is an attractive scaling strategy for Facebook
and other OSN services.