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188 For long paths, we use landmark routing to reach the destination’s neighborhood. A small subset of the user population is chosen as landmarks, and every user in the network determines her hop distance and the next hop to each of these landmarks. The landmarks are selected such that every user is within three hops of at least one landmark. Then, the resultant coordinate system can be used to route to within three hops of any destination user, and the bloom filters to reach the destination. Thus, given a destination user’s coordinate, a user can first route to a landmark user who is “near” the destination, and this landmark user can then use bloom filter routing for the last few hops. We describe these in terms of an interval I, which is the frequency with which the bloom filters and coordinates are recomputed and updated. Typical values of I are on the order of a few days. 8.5.3 Bloom filter routing Bloom filters are a space-efficient probabilistic data structure for representing set membership. When testing whether an element is in the set, bloom filters have no false negatives, but have a configurable false positive rate [21]. In Ostra, each user U makes available two separate bloom filters: a one-hop bloom filter F1 and a two-hop bloom filter F2. The one-hop bloom filter contains all of the direct friends of U, and the two-hop bloom filter contains all of U’s friends-of-friends.PDF Image | Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems
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