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Efficient Content Location in Massively Distributed Triplespaces

  • Kia Teymourian
  • Lyndon Nixon
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5333)

Abstract

Triple Space Computing is a new middleware paradigm [11,13] based on semantics and tuplespaces which can be used for the coordination of Semantic Web clients and services. To achieve scalability of Triple Space infrastructure distribution of triplespaces is necessary. A major problem within massively distributed triplespaces is to find the best suited triplespaces to answer a certain query. In this paper we introduce a novel approach for efficient content location of triplespaces given a certain query. We use a Peer-to-Peer overlay based on Distributed Hash Tables and three semantic overlay layers which are used to score the known triplespaces according to their probability to answer queries. This combination approach is introduced to solve the triplespace selection problem more efficiently and support high performance operation handling in triplespaces.

Keywords

Distribute Hash Table Read Operation Content Location SPARQL Query Triple Pattern 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Kia Teymourian
    • 1
  • Lyndon Nixon
    • 1
  1. 1.Institut for Computer Science, AG Networked Information SystemsFree University of BerlinBerlinGermany

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