Peer selection for query routing is a core task in peer-to-peer networks. Unstructured peer-to-peer systems (like Gnutella) ignore this problem, leading to an abundance of network traffic. Structured peer-to-peer systems (like Chord) enforce a particular, global way of distributing data among the peers in order to solve this problem, but then encounter problems of network volatility and conflicts with the autonomy of the peer data management. In this paper, we propose a new mechanism, INGA, which is based on the observation that query routing in social networks is made possible by locally available knowledge about the expertise of neighbors and a semantics-based peer selection function. We validate INGA by simulation experiments with different data sets. We compare INGA with competing peer selection mechanisms on resulting parameters like recall, message gain or number of messages produced.

In peer-to-peer networks, finding the appropriate answer for an information request, such as the answer to a query for RDF(S) data, depends on selecting the right peer in the network. We hereinvestigate how social metaphors can be exploited effectively andefficiently to solve this task. To this end, we define a method for query routing, REMINDIN', that lets (i) peers observewhich queries are successfully answered by other peers,(ii), memorizes this observation, and, (iii),subsequently uses this information in order to select peers to forward requests to.REMINDIN' has been implemented for the SWAP peer-to-peer platformas well as for a simulation environment. We have used the simulation environment in order to investigate how successfulvariations of REMINDIN' are and how they compare to baseline strategies in terms of number of messages forwarded in the networkand statements appropriately retrieved.