Expertise-based peer selection in Peer-to-Peer networks

Peer-to-Peer systems have proven to be an effective way of sharing data. Modern protocols are able to efficiently route a message to a given peer. However, determining the destination peer in the first place is not always trivial. We propose a a message to a given peer. However, determining the destination peer in the first place is not always trivial. We propose a model in which peers advertise their expertise in the Peer-to-Peer network. The knowledge about the expertise of other peers forms a semantic topology. Based on the semantic similarity between the subject of a query and the expertise of other peers, a peer can select appropriate peers to forward queries to, instead of broadcasting the query or sending it to a random set of peers. To calculate our semantic similarity measure, we make the simplifying assumption that the peers share the same ontology. We evaluate the model in a bibliographic scenario, where peers share bibliographic descriptions of publications among each other. In simulation experiments complemented with a real-world field experiment, we show how expertise-based peer selection improves the performance of a Peer-to-Peer system with respect to precision, recall and the number of messages

Semantic Routing in Peer-to-Peer Systems

Currently search engines like Google, Yahoo and Excite are centralized, which means that all queries that users post are sent to some big servers (or server group) that handle them. In this way it is easy for the systems to relate IP-addresses with the queries posted from them. Clearly privacy is a problem here. Also censoring out certain information which is not 'appropriate' is simple, and shown in recent examples. To give more privacy to the users and make censoring information more difficult, Peer-to-Peer (P2P) systems are a good alternative to the centralized approach. In P2P systems the search functionality can be devided over a large group of autonomous computers (Peers), where each computer only has a very small piece of information instead of everything. Now the problem in such a distributed system is to make the search process efficient in terms of bandwith, storage, time and CPU usage. In this Ph.D. thesis, three approaches are described that try to reach goal of finding the short routes between seeker and providers with high efficiency. These routing algorithms are all applied on 'Semantic-Overlay-Networks' (SONs). In a SON, peers maintain pointers to semantically relevant peers based on content descriptions, which makes them able to choose the relevant peers for queries instead of, for example, choosing random peers. This work tries to show that decentralized search algorithms based on semantic routing are a good alternative to centralized approaches.Harmelen, F.A.H. van [Promotor