• Journal of KIISE:Information Networking
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• v.30 no.2
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• pp.167-178
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• 2003

In mobile computing environments, queries based on the location of mobile clients (MCs) may cause different results. We say that the data of these results are location dependent data (LDD). Location-dependent queries to LDD need to be processed in conjunction with the geographical distance. The efficiency of query processing may also be increased by LDD relationship, etc. But there is the problem of fuzziness about how the distance used in location-dependent queries is evaluated and the data regions are organized. In this paper, we quantify the fuzziness of a location-dependent fuery on LDD. And we propose data regions for LDD, called LDD regions, by relationship of accessed data and the degree of distance between data objects and MCs' locations. In simulation studies we show that the number of database access for location-dependent queries, which have several settings on MCs' favor and two granularity of regions, can be smaller in proposed LDD regions than that in geographical regions.

• Journal of KIISE:Databases
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• v.30 no.3
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• pp.320-335
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• 2003

Location-Based Services(LBS) give rise to location-based queries of which results depend on the locations of moving objects. One of important applications of LBS is to examine tracks of continuously moving objects. Moving objects databases need to provide 3-dimensional indexing for efficiently processing range queries on the movement of continuously changing positions. An extension of the 2-dimensional R-tree to include time dimension shows low space utilization and poor search performance, because of high overlap of index nodes and their dead space. To solve these problems, we propose a new R-tree based indexing technique, namely TR-tree. To increase storage utilization, we assign more entries to the past node by using the unbalanced splitting policy. If two nodes are highly overlapped, these nodes are forcibly merged. It is the forced merging policy that reduces the dead space and the overlap of nodes. Since big line segments can also affect the overlap of index nodes to be increased, big line segments should be clipped by the clipping policy when splitting overfull nodes. The TR-tree outperforms the 3DR-tree and TB-tree in all experiments. Particularly, the storage utilization of the TR-tree is higher than the R-tree and R*-tree.