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

  • Authors:
  • Peter Haase;Ronny Siebes;Frank van Harmelen

  • Affiliations:
  • University of Karlsruhe, Institute AIFB, 76128, Karlsruhe, Germany;Vrije Universiteit Amsterdam, Department of Computer Science, 1081HV, De Boelelaan, The Netherlands;Vrije Universiteit Amsterdam, Department of Computer Science, 1081HV, De Boelelaan, The Netherlands

  • Venue:
  • Knowledge and Information Systems
  • Year:
  • 2008

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Abstract

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 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.