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.
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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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Iqbal, A.A., Ott, M., Seneviratne, A. (2010). Removing the Redundancy from Distributed Semantic Web Data. In: Bringas, P.G., Hameurlain, A., Quirchmayr, G. (eds) Database and Expert Systems Applications. DEXA 2010. Lecture Notes in Computer Science, vol 6261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15364-8_44
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DOI: https://doi.org/10.1007/978-3-642-15364-8_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15363-1
Online ISBN: 978-3-642-15364-8
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