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Removing the Redundancy from Distributed Semantic Web Data

  • Ahmad Ali Iqbal
  • Maximilian Ott
  • Aruna Seneviratne
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6261)

Abstract

Peer-to-peer databases have proven to be an effective way for sharing data. However, distributed knowledge management in P2P databases brings a variety of non-trivial challenges along with its benefits. Such challenges include determining the right content provider(s) and removing the duplicate data transfer if a relatively larger portion of data is redundant and is made available in distributed providers. The aim of this paper is to address data redundancy removal problem such that excessive bandwidth usage due to in-network duplicate data transfer can be minimized. We provide analytical and experimental evaluation of our schemes in terms of the number and size of the packets that flow in the network while keeping confidence level of results high.

Keywords

Resource Description Framework Average Response Time Resource Selection Information Receiver False Positive Probability 
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 2010

Authors and Affiliations

  • Ahmad Ali Iqbal
    • 1
    • 2
  • Maximilian Ott
    • 2
  • Aruna Seneviratne
    • 1
    • 2
  1. 1.School of EE&TUniversity of New South Wales (UNSW)Australia
  2. 2.National Information and Communication Technology Australia (NICTA) 

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