Abstract
Continuous Nearest Neighbor (NN) monitoring in road networks has recently received many attentions. In many scenarios, there are two kinds of continuous k-NN queries with different semantics. For instance, query “finding the nearest neighbor from me along my moving direction” may return results different from query “finding the nearest neighbor from my current location”. However, most existing continuous k-NN monitoring algorithms only support one kind of the above semantic queries. In this paper, we present a novel directional graph model for road networks to simultaneously support these two kinds of continuous k-NN queries by introducing unidirectional network distance and bidirectional network distance metrics. Considering the computational capability of mobile client to locate the edge containing it, we use memory-resident hash table and linear list structures to describe the moving objects and store the directional model. We propose the unidirectional network expansion algorithm and bidirectional network expansion algorithm to reduce the CPU cost of continuous k-NN queries processing. Experimental results show that the above two algorithms outperform existing algorithms including IMA and MKNN algorithms.
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References
Wolfson, O.: Moving objects information management: The database challenge. In: Halevy, A.Y., Gal, A. (eds.) NGITS 2002. LNCS, vol. 2382, pp. 75–89. Springer, Heidelberg (2002)
Jensen, C.S., Kolárvr, J., Pedersen, T.B., Timko, I.: Nearest Neighbor Queries in Road Networks. In: Proc. ACM Intl. Symposium on Advances in Geographic Information Systems(ACM GIS 2003), pp. 1–8 (2003)
Mouratidis, K., Yiu, M.L., Papadias, D., Mamoulis, N.: Continuous Nearest Neighbor Monitoring in Road Networks. In: Proc. Intl. Conf. on Very Large Data Bases (VLDB 2006), pp. 43–54 (2006)
Wang, H., Zimmermann, R.: Location-based Query Processing on Moving Objects in Road Networks. In: Proc. Intl. Conf. on Very Large Data Bases (VLDB 2007), pp. 321–332 (2007)
Papadias, D., Zhang, J., Mamoulis, N., Tao, Y.: Query Processing in Spatial Network Databases. In: Proc. Intl. Conf. on Very Large Data Bases, pp. 802–813 (2003)
Kolahdouzan, M.R., Shahabi, C.: Voronoi-Based K Nearest Neighbor Search for Spatial Network Databases. In: Proc. Intl. Conf. on Very Large Data Bases (VLDB 2004), pp. 840–851 (2004)
Mokbel, M.F., Xiong, X., Aref, W.G.: SINA: Scalable Incremental Processing of Continuous Queries in Spatiotemporal Databases. In: Proc. Intl. Conf. on Management of Data (SIGMOD 2004), pp. 623–634 (2004)
Xiong, X., Mokbel, M.F., Aref, W.G.: SEA-CNN: Scalable Processing of Continuous K-Nearest Neighbor Queries in Spatio-temporal Databases. In: Proc. Intl. Conf. on Data Engineering (ICDE 2005), pp. 643–654 (2005)
Yu, X., Pu, K.Q., Koudas, N.: Mointoring k-Nearest Neighbour Queries over Moving Objects. In: Proc. Intl. Conf. on Data Engineering (ICDE 2005), pp. 631–642 (2005)
Mouratidis, K., Hadjieleftheriou, M., Papadias, D.: Conceptual Partitioning: An Efficient Method for Continuous Nearest Neighbor Monitoring. In: Proc. Intl. Conf. on Management of Data, Baltimore (SIGMOD 2005), pp. 634–645 (2005)
Brinkhoff, T.: A Framework for Generating Network based Moving Objects. GeoInformatica 6, 153–180 (2002)
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Liao, W., Wu, X., Yan, C., Zhong, Z. (2009). Processing of Continuous k Nearest Neighbor Queries in Road Networks. In: Lee, R., Ishii, N. (eds) Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. Studies in Computational Intelligence, vol 209. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01203-7_3
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DOI: https://doi.org/10.1007/978-3-642-01203-7_3
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