Scalable p2p based RDF querying

In large-scale distributed systems, information is typically generated decentralized. However, for many applications it is desirable to have a unified view on this knowledge, allowing to query it without regarding the heterogeneity of the underlying systems. In this context, two main requirements have to be fulfilled. On the one hand, we need a flexible knowledge representation, and on the other hand the underlying infrastructure and query evaluation algorithm has to be highly scalable.The combination of p2p networks as basic infrastructure with RDF as a knowledge representation is a promising approach to this problem. Within this paper, we focus on the evaluation of RDF queries with respect to RDF data stored in a DHT-based p2p network. We propose a query algorithm and research different optimizations based on a look-ahead technique and Bloom filters which aim at maximizing the throughput and scalability of the entire system.