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A P2P Technique for Continuous k-Nearest-Neighbor Query in Road Networks

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Database and Expert Systems Applications (DEXA 2007)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4653))

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Abstract

Due to the high frequency in location updates and the expensive cost of continuous query processing, server computation capacity and wireless communication bandwidth are the two limiting factors for large-scale deployment of moving object database systems.  Many techniques have been proposed to address the server bottleneck including one using distributed servers.  To address both of the scalability factors, P2P computing has been considered.  These schemes enable moving objects to participate as a peer in query processing to substantially reduce the demand on server computation, and wireless communications associated with location updates.  Most of these techniques, however, assume an open-space environment.  In this paper, we investigate a P2P computing technique for continuous kNN queries in a network environment.   Since network distance is different from Euclidean distance, techniques designed specifically for an open space cannot be easily adapted for our environment.   We present the details of the proposed technique, and discuss our simulation study.  The performance results indicate that this technique can significantly reduce server workload and wireless communication costs.

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Roland Wagner Norman Revell Günther Pernul

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© 2007 Springer-Verlag Berlin Heidelberg

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Liu, F., Hua, K.A., Do, T.T. (2007). A P2P Technique for Continuous k-Nearest-Neighbor Query in Road Networks. In: Wagner, R., Revell, N., Pernul, G. (eds) Database and Expert Systems Applications. DEXA 2007. Lecture Notes in Computer Science, vol 4653. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74469-6_27

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  • DOI: https://doi.org/10.1007/978-3-540-74469-6_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74467-2

  • Online ISBN: 978-3-540-74469-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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