Abstract
We study the effect of semantic overlay structure on the performance of decentralized search. Semantic overlays create communities of nodes that share particular interests. In peer-to-peer systems these communities can be designed to improve the recall of search algorithms. Such communities also play a role in balancing load between agents. An examination of these two performance metrics on some basic semantic overlay topologies shows that the choice of the best decentralized search algorithm can be influenced by differing design goals. We present an extensive experimental evaluation using data sets from eDonkey and Movielens. We find that, in general, these data sets do not exhibit obvious semantic clusters of nodes. For this reason, using a best-neighbors overlay, in which nodes individually choose their neighbors, to implement search produces better recall values than using an overlay that specifically clusters nodes into groups. Using best-neighbors overlays, on the other hand, can lead to highly unbalanced load distributions, a problem avoided in clustered overlays. We also find that forwarding search queries to “friends” in best-neighbors overlays does little to improve recall while further unbalancing load distributions.
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Ogston, E. (2008). An Analysis of Interest-Community Facilitated Peer-to-Peer Search. In: Joseph, S., Despotovic, Z., Moro, G., Bergamaschi, S. (eds) Agents and Peer-to-Peer Computing. AP2PC 2006. Lecture Notes in Computer Science(), vol 4461. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79705-0_9
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DOI: https://doi.org/10.1007/978-3-540-79705-0_9
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