Abstract
In recent years, there is an increasing need to monitor k nearest neighbor (k-NN) in a road network. There are existing solutions on either monitoring k-NN objects from a single query point over a road network, or computing the snapshot k-NN objects over a road network to minimize an aggregate distance function with respect to multiple query points. In this paper, we study a new problem that is to monitor k-NN objects over a road network from multiple query points to minimize an aggregate distance function with respect to the multiple query points. We call it a continuous aggregate k-NN (CANN) query. We propose a new approach that can significantly reduce the cost of computing network distances when monitoring aggregate k-NN objects on road networks. We conducted extensive experimental studies and confirmed the efficiency of our algorithms.
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Qin, L., Yu, J.X., Ding, B., Ishikawa, Y. (2008). Monitoring Aggregate k-NN Objects in Road Networks. In: Ludäscher, B., Mamoulis, N. (eds) Scientific and Statistical Database Management. SSDBM 2008. Lecture Notes in Computer Science, vol 5069. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69497-7_13
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DOI: https://doi.org/10.1007/978-3-540-69497-7_13
Publisher Name: Springer, Berlin, Heidelberg
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