Abstract
In this paper, we examine how to efficiently process top-k queries in pure P2P network. First, we propose a distributed algorithm to evaluate a top-k query in a hierarchical way. Each peer does its local top-k query, and top k results from different peers are merged hierarchically from bottom to the top (the root peer is the query initiator). Ranking and merging of results are distributed across the peers to exploit the computing resources in the network. Second, to improve performance, we maintain histograms at each peer according to the top k results returned by the peers. The histograms are used to estimate the possible upper bound scores of peers so that a query only needs to be forwarded to the most promising neighbouring peers. Our experimental study shows that the top-k query algorithm improves the query effectiveness, while the use of histograms enhances the query efficiency.
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© 2004 Springer-Verlag Berlin Heidelberg
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He, Y., Shu, Y., Wang, S., Du, X. (2004). Efficient Top-k Query Processing in P2P Network. In: Galindo, F., Takizawa, M., Traunmüller, R. (eds) Database and Expert Systems Applications. DEXA 2004. Lecture Notes in Computer Science, vol 3180. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30075-5_37
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DOI: https://doi.org/10.1007/978-3-540-30075-5_37
Publisher Name: Springer, Berlin, Heidelberg
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